JP6914090B2 - Radar device and information transfer method - Google Patents

Description

The present invention relates to a process of deriving a target of a radar device.

In a radar device, a target related to an object is detected by receiving a received signal that arrives by reflecting a transmitted signal transmitted from the radar device on the object.

An example of a radar device is a millimeter wave radar. Further, the radar device detects a target related to an object existing in the vicinity of the vehicle by using, for example, FM-CW (Frequency Modulated Continuous Wave) which is mounted on the vehicle and is a frequency-modulated continuous wave.

Objects to be detected by radar devices mounted on vehicles are roughly classified into, for example, stationary objects and moving objects. Examples of stationary objects include traffic lights, poles, pedestrian bridges, utility poles, traffic signs, guardrails, road information boards, etc. installed on road surfaces, roadside belts, sidewalks, and the like. Further, as an example of a moving object, another vehicle (hereinafter, may be referred to as a "preceding vehicle") or the like that travels in front of the own vehicle in the same direction as the own vehicle can be mentioned.

In addition, the radar device mounted on the vehicle calculates the "reliability" of the target, which is the data related to the type of each target. As a target with relatively low reliability, for example, a stationary object (hereinafter sometimes referred to as an "upper object") installed at a position higher than the vehicle height of a vehicle equipped with a radar device by a predetermined distance. Such a target, a target related to a stationary object (hereinafter, may be referred to as a "lower object") installed at a position lower than the bottom of the vehicle on which the radar device is mounted, and the like can be mentioned. Examples of upper objects include pedestrian bridges and road information boards, and examples of lower objects include road studs installed in medians and curves of roads. In addition, as targets with relatively high reliability, for example, a target related to a vehicle stopped in the own lane (hereinafter, may be referred to as a "stopped vehicle"), a target related to a preceding vehicle, etc. Can be mentioned. The radar device outputs information about a target whose reliability is equal to or higher than the threshold value to the vehicle control device which controls the behavior of the vehicle, and does not output information about a target whose reliability is lower than the threshold value to the vehicle control device.

Japanese Unexamined Patent Publication No. 2016-006383

When the radar device detects a target related to a stopped vehicle (for example, a truck) having a relatively long overall length, the transmitted wave may be reflected at a plurality of points of the stopped vehicle. In this case, a plurality of reflected waves from one stopped vehicle arrive at the radar device. For example, the received signal R1 is received by the radar device by reflecting the transmitted wave at the position of the rear bumper installed at the rear end of the stopped vehicle, while the transmitted wave is installed near the driver's seat at the front of the truck. The received signal R2 is received by the radar device by reflecting at the position of the side mirror. When the received signal R1 and the received signal R2 are received from one stopped vehicle, the radar device has two targets, P1 related to the reflection point of the rear bumper and P2 related to the reflection point of the side mirror. A target is detected. In this way, the detection of a plurality of targets for one object is sometimes called "vertical cracking". In the following, an object in which vertical cracks occur may be referred to as a "vertical cracked object".

On the other hand, in the vehicle control device, a target related to the rear end (for example, the rear bumper) of the stopped vehicle is often used as a reference point for vehicle control. For example, AEBS (Advanced Emergency Braking System), which is one of the vehicle control devices, operates the brake of the own vehicle to stop when the distance between the own vehicle and the rear end of the stopped vehicle becomes less than the threshold value. Prevent rear-end collisions with vehicles.

However, some of the reflected waves from the stopped vehicle are not only the direct wave directly received from the reflection point to the radar device, but also the multipath that is reflected from the reflection point to the ground and indirectly received to the radar device. There are also waves. Then, the direct wave from the rear bumper may interfere with the multipath wave from other than the rear end of the stopped vehicle, the power of the received signal R1 may decrease, and the target P1 may not be detected.

Then, when the target P2 is detected without the power of the received signal R2 being interfered by the multipath wave, the radar device is faster than the target P1 related to the rear bumper of the stopped vehicle, and the side mirror. The target P2 according to the above is detected. As a result, the position of the target P2 is detected as the position of the stopped vehicle, and the determination process of the type of the target P1 used as the reference point in the vehicle control device is delayed. In this way, if the radar device determines the type of target, the vehicle control device delays the process of determining whether the target is a target that requires control of the vehicle, resulting in a delay. In the case of a target that requires control of the vehicle, control of the vehicle (for example, the start of braking of the vehicle by AEBS) is delayed.

The disclosed technique has been made in view of the above, and an object thereof is to determine the type of a target at an early stage.

In the disclosed aspect, the radar device has a determination means and a takeover means. The radar device derives information related to a target based on a received signal obtained by receiving a transmitted wave transmitted to the periphery of the own vehicle and reflected by an object existing in the periphery. The determination means determines whether or not a plurality of targets belong to the same object. When it is determined that the plurality of targets belong to the same object, the takeover means means that the first target among the plurality of targets exists at a position closer to the second target. When the second target is a target derived earlier than the first target in terms of time, the information regarding the type of the second target and the information regarding the type of the first target are obtained. Take over as.

According to the aspect of disclosure, the type of the target can be determined at an early stage.

FIG. 1 is a diagram showing an example of a vehicle equipped with the vehicle control system of the first embodiment. FIG. 2 is a diagram showing a configuration example of the vehicle control system of the first embodiment. FIG. 3 is a diagram showing a configuration example of the radar device of the first embodiment. FIG. 4 is a diagram showing an example of the relationship between the transmission signal and the reception signal of the first embodiment. FIG. 5 is a functional block diagram showing the functions of the processor of the first embodiment. FIG. 6 is a flowchart provided for explaining an example of processing of the radar device of the first embodiment. FIG. 7 is a diagram for explaining an operation example of the signal processing unit of the first embodiment. FIG. 8 is a diagram provided for explaining an operation example of the signal processing unit of the first embodiment. FIG. 9 is a flowchart provided for explaining an example of the pairing process of the first embodiment. FIG. 10 is a flowchart provided for explaining an example of the history pairing process of the first embodiment. FIG. 11 is a flowchart provided for explaining an example of the normal history peak determination process of the first embodiment. FIG. 12 is a diagram for explaining an operation example of the signal processing unit of the first embodiment. FIG. 13 is a diagram for explaining an operation example of the signal processing unit of the first embodiment. FIG. 14 is a flowchart for explaining an example of the reliability inheritance process of the first embodiment. FIG. 15 is a diagram for explaining an operation example of the signal processing unit of the first embodiment. FIG. 16 is a diagram for explaining an operation example of the signal processing unit of the first embodiment. FIG. 17 is a diagram for explaining an operation example of the signal processing unit of the first embodiment. FIG. 18A is a diagram for explaining an operation example of the signal processing unit of the second embodiment. FIG. 18B is a diagram for explaining an operation example of the signal processing unit of the second embodiment. FIG. 19 is a diagram for explaining an operation example of the signal processing unit of the second embodiment. FIG. 20 is a diagram provided for explaining an operation example of the signal processing unit of the second embodiment. FIG. 21A is a schematic diagram illustrating factor 1 of the extrapolation process. FIG. 21B is a schematic diagram illustrating factor 2 of the extrapolation process. FIG. 21C is a schematic diagram illustrating factor 3 of the extrapolation process. FIG. 21D is a schematic diagram illustrating factor 4 of the extrapolation process. FIG. 22 is a diagram schematically showing the state of the reflected wave when the vertically cracked object is an upper object.

The radar device disclosed in the present application transmits a transmission signal whose transmission frequency changes at a predetermined cycle, and receives a reception signal that arrives when the transmission signal is reflected by an object. Further, the radar device disclosed in the present application is a signal (hereinafter referred to as "beat signal") indicating a difference frequency (hereinafter, may be referred to as "beat frequency") between the transmission frequency of the transmission signal and the reception frequency of the reception signal. The peaks of the frequency spectrum of (sometimes) are referred to as an ascending section of the transmission frequency (hereinafter sometimes referred to as "UP interval") and a descending section of the transmission frequency (hereinafter sometimes referred to as "DOWN interval"). Get it with. The radar device disclosed in the present application includes a peak in the UP section (hereinafter sometimes referred to as "UP peak") and a peak in the DOWN section (hereinafter sometimes referred to as "DOWN peak"). Information on the target (hereinafter sometimes referred to as "target information") is derived based on the data by the pair (association). In this way, the data obtained by associating the UP peak with the DOWN peak is referred to as a "target". One target corresponds to one reflection point of one object.

Hereinafter, examples of the radar device and the reliability inheritance method disclosed in the present application will be described with reference to the drawings. It should be noted that this embodiment does not limit the radar device and the reliability inheritance method disclosed in the present application. In the following, the same reference numerals are given to the configurations having the same functions and the steps for performing the same processing in each embodiment.

[Example 1]
<Vehicle control system configuration>
FIG. 1 is a diagram showing an example of a vehicle equipped with the vehicle control system of the first embodiment, and FIG. 2 is a diagram showing a configuration example of the vehicle control system of the first embodiment.

In FIG. 1, the vehicle CR is equipped with a radar device 1 and a vehicle control device 2. The radar device 1 and the vehicle control device 2 are included in the vehicle control system 10 as shown in FIG. The vehicle control device 2 is realized by, for example, an ECU (Electronic Control Unit). The vehicle CR is equipped with the radar device 1 in the vicinity of the front bumper of the vehicle CR, for example. The radar device 1 transmits, for example, a transmission signal having a beam pattern NA of the central axis BL to scan a predetermined scanning range, and a distance between the vehicle CR and the target in the vehicle traveling direction (hereinafter, “vertical”). By deriving the distance (sometimes called "distance") and the distance in the vehicle lateral direction (vehicle width direction) (hereinafter sometimes called "lateral distance"), the position information of the target with respect to the vehicle CR is derived. do. Further, the radar device 1 derives the speed of the target (hereinafter sometimes referred to as "relative velocity") with respect to the speed of the vehicle CR (hereinafter sometimes referred to as "own vehicle speed").

In FIG. 2, the vehicle control system 10 includes a radar device 1 and a vehicle control device 2. The radar device 1 outputs the target information to the vehicle control device 2. The target information output from the radar device 1 includes a vertical distance, a horizontal distance, and a relative velocity.

A vehicle speed sensor 40, a steering sensor 41, a brake 50, and a throttle 51 are connected to the vehicle control device 2. The vehicle speed sensor 40, the steering sensor 41, the brake 50, and the throttle 51 are mounted on the vehicle CR.

The vehicle speed sensor 40 detects the vehicle speed and outputs the detected information on the vehicle speed (hereinafter, may be referred to as “vehicle speed information”) to the radar device 1 and the vehicle control device 2. The steering sensor 41 detects the steering angle of the vehicle CR and outputs the detected steering angle information to the vehicle control device 2. The brake 50 reduces the own vehicle speed according to the control from the vehicle control device 2. The throttle 51 increases the own vehicle speed according to the control from the vehicle control device 2.

The vehicle control device 2 controls the operation of the brake 50 and the operation of the throttle 51 based on the target information, the own vehicle speed detected by the vehicle speed sensor 40, and the steering angle of the vehicle CR detected by the steering sensor 41. , Control the behavior of the vehicle CR. For example, the vehicle control device 2 controls the brake 50 and the throttle 51 based on the target information, the own vehicle speed, and the steering angle of the vehicle CR, so that the vehicle CR keeps the distance between the vehicle CR and the preceding vehicle constant. Achieves ACC (Adaptive Cruise Control) that allows the vehicle to follow the preceding vehicle. Further, for example, the vehicle control device 2 controls the brake 50 based on the target information, the own vehicle speed, and the steering angle of the vehicle CR, thereby reducing the own vehicle speed when there is a risk that the vehicle CR collides with an obstacle. Realize AEBS.

<Structure of radar device>
FIG. 3 is a diagram showing a configuration example of the radar device of the first embodiment. In FIG. 3, the radar device 1 includes a processor 17, a memory 18, an oscillator 11, a transmitting antenna 12, receiving antennas 13a, 13b, 13c, mixers 14a, 14b, 14c, and an ADC (Analog to Digital Converter). It has 16a, 16b, and 16c. The processor 17 outputs the target information. The receiving antennas 13a, 13b, and 13c are arranged in a straight line at equal intervals to form a receiving antenna array. Examples of the processor 17 include a CPU (Central Processing Unit), a DSP (Digital Signal Processor), an FPGA (Field Programmable Gate Array), and the like. Further, as an example of the memory 18, a RAM such as SDRAM, a ROM, a flash memory, and the like can be mentioned. In the following, the receiving antennas 13a, 13b and 13c may be collectively referred to as the “receiving antenna 13”, the mixers 14a, 14b and 14c may be collectively referred to as the “mixer 14”, and the ADCs 16a, 16b and 16c may be collectively referred to as the “ADC16”.

The oscillator 11 frequency-modulates a continuous wave signal based on the modulation signal input from the processor 17 to generate a transmission signal whose frequency changes with the passage of time, and the generated transmission signal is transmitted to the transmission antenna 12. And output to the mixer 14.

The transmitting antenna 12 transmits a transmission signal frequency-modulated by the oscillator 11 as a transmission wave.

The receiving antenna 13 acquires the received signal by receiving the reflected wave as the transmitted wave reflected by the object existing in the vicinity of the radar device 1 as the received signal.

The mixer 14 mixes the transmission signal input from the oscillator 11 and the reception signal input from the reception antenna 13. By mixing the mixer 14, a beat signal indicating a beat frequency, which is a difference frequency between the transmission frequency of the transmission signal and the reception frequency of the reception signal, is generated. The mixer 14 outputs the beat signal generated by the mixing to the ADC 16.

The ADC 16 converts an analog beat signal into a digital beat signal, and outputs the converted digital beat signal to the processor 17.

<Relationship between transmission signal and reception signal>
FIG. 4 is a diagram showing an example of the relationship between the transmission signal and the reception signal of the first embodiment. Hereinafter, the FM-CW method will be described as an example. However, the method to which the technique disclosed in the present application is applied is not limited to the FM-CW method. The method to which the technique disclosed in the present application is applied can be applied to all methods for detecting a target using an UP section in which the transmission frequency of the transmission signal rises and a DOWN section in which the transmission frequency of the transmission signal falls. be.

In the following, "f _r" is the distance frequency, "f _d" is the speed frequency, "f _0" is the center frequency of the transmission signal, "△ F" is the frequency shift width, "f _m" is the repetition frequency of the modulation signal , "c" is the speed of light (speed of radio waves), "T" wave of the round-trip time between the radar device 1 and the target, "f _s" is the transmit / receive frequency, "R" is the vertical distance, "V Is the relative speed, "θ _m " is the angle of the target with respect to the radar device 1, "θ _up " is the angle corresponding to the UP peak, "θ _dn " is the angle corresponding to the DOWN peak, and "D" is the radar device 1. The distance from to the target is shown respectively. Further, in the following, the transmission signals TX1 and TX2 may be collectively referred to as "transmission signal TX", the reception signals RX1 and RX2 may be collectively referred to as "reception signal RX", and the beat signals BS1 and BS2 may be collectively referred to as "beat signal BS".

In the upper part of FIG. 4, at time t0 to t4, the transmission frequency of the transmission signal TX1 is the center frequency _{f 0,} descends to the lower limit frequency DOWN interval D1 after rising to the upper limit frequency UP section U1, UP as that descends after rising up to the upper limit frequency to the lower limit frequency DOWN section D2 in interval U2, repeating the raising and lowering in a predetermined cycle "1 / f _m." For example, the center frequency f ₀ is 76.5 GHz, the upper limit frequency is 76.6 GHz, and the lower limit frequency is 76.4 GHz. In this way, the radar device 1 sets a section in which one UP section and one DOWN section are combined as one cycle, and transmits a transmission signal TX corresponding to two cycles in one transmission. Further, the received signal RX1 transmitted from the transmitting antenna 12 arrives at the radar device 1 due to reflection on the object and is received by the receiving antenna 13, also having a predetermined period “1”, similarly to the transmitting signal TX1. / f _m "in repeating the rising and falling.

Next, in the processor processing section PA at times t4 to t5, the processor 17 performs signal processing for deriving the target information using the transmission signal TX1 and the reception signal RX1.

Then, at time t5 to t9, similarly to the time t0 to t4, the transmission frequency of the transmission signal TX2 is a center frequency _{f 0,} it descends to the lower limit frequency DOWN section D3 after rising to the upper limit frequency UP section U3 , and so lowers to the lower limit frequency DOWN section D4 after rising to the upper limit frequency uP section U4, repeating the raising and lowering in a predetermined cycle "1 / f _m." Further, the received signal RX2 transmitted from the transmitting antenna 12 arrives at the radar device 1 due to reflection on the object and is received by the receiving antenna 13, also having a predetermined period “1”, similarly to the transmitting signal TX2. / f _m "in repeating the rising and falling.

Then, in the processor processing section PB at times t9 to t10, the processor 17 performs signal processing for deriving the target information by using the transmission signal TX2 and the reception signal RX2.

After the time t10, the same process as the time t0 to t10 is repeated. As described above, in the radar device 1, the transmission of the transmission signal TX, the reception of the reception signal RX, and the derivation of the target information are sequentially repeated.

The received signal RX has a delay time τ with respect to the transmitted signal TX. This delay time τ corresponds to the distance D from the radar device 1 to the target. Further, when there is a speed difference between the own vehicle speed and the target speed, a frequency difference corresponding to the Doppler shift occurs in the received signal RX with respect to the transmitted signal TX.

The lower figure of FIG. 4 shows the beat signal BS. The beat signal BS1 is generated by mixing the transmission signal TX1 and the reception signal RX1, and the beat signal BS2 is generated by mixing the transmission signal TX2 and the reception signal RX2. The beat signal BS indicates a difference frequency (that is, a beat frequency) between the transmission frequency of the transmission signal TX and the reception frequency of the reception signal RX. For example, the beat frequency in the UP sections U1, U2, U3, U4 is BF1, and the beat frequency in the DOWN sections D1, D2, D3, D4 is BF2. In this way, the beat frequency is derived in each section.

Then, in the processor 17, the beat signal BS input from the ADC 16 is subjected to FFT (Fast Fourier Transform), so that the beat signal BS is converted into a frequency spectrum which is data in the frequency domain, and the UP section and DOWN In each of the sections, the frequency spectrum of the beat signal BS is obtained. Hereinafter, the frequency spectrum of the beat signal BS may be referred to as “FFT data”.

Then, using the FFT data derived in this way, the vertical distance, the relative velocity, and the horizontal distance of the target with respect to the radar device 1 are derived. For example, the distance of the target to the radar device 1 is derived by the equation (1), and the relative velocity of the target to the radar device 1 is derived by the equation (2). Further, for example, the angle of the target with respect to the radar device 1 is derived by the equation (3). Then, based on the distance derived by the equation (1) and the angle derived by the equation (3), the vertical distance and the lateral distance of the target with respect to the radar device 1 are derived by the calculation using the trigonometric function. NS.

<Processor function>
FIG. 5 is a functional block diagram showing the functions of the processor of the first embodiment. In FIG. 5, the processor 17 has a signal processing unit 201, a transmission control unit 202, a signal generation unit 203, and a target information output unit 204 as functions of the processor 17.

The signal generation unit 203 generates a modulation signal whose voltage changes in a triangular wave shape according to the control from the transmission control unit 202, and outputs the generated modulation signal to the oscillator 11.

The signal processing unit 201 acquires peaks of FFT data in each of the UP section and the DOWN section, and generates target information based on the UP peak and the DOWN peak. At this time, the signal processing unit 201 extracts a peak in which the power of the FFT data in the UP section exceeds a predetermined threshold from the FFT data to acquire the UP peak, and the peak in which the power of the FFT data in the DOWN section exceeds the predetermined threshold. Is extracted from the FFT data to obtain the DOWN peak. Then, the signal processing unit 201 derives the target information based on the pair of the UP peak and the DOWN peak, and outputs the derived target information to the target information output unit 204. Details of the processing by the signal processing unit 201 will be described later.

The target information output unit 204 selects a predetermined number of target information having a high priority and a reliability of a predetermined threshold value or more from the target information input from the signal processing unit 201. The selected target information is output to the vehicle control device 2. The details of the processing in the target information output unit 204 will be described later.

Here, the "reliability" is information regarding the type of the target. Specifically, it is a value used when determining whether the target is a target related to a stopped vehicle or a target related to an upper object from a plurality of parameters of the target. When the reliability is equal to or higher than the threshold value in a plurality of scanning processes of the radar device, the target is determined to be a target related to a stopped vehicle. When the reliability is less than the threshold value, the target is determined to be a target related to an upper object. By making such a determination, it is possible to accurately determine whether or not the object having the target is an object that collides when the own vehicle moves in the traveling direction.

The memory 18 stores FFT data, target information, and the like derived by the signal processing unit 201. For example, the memory 18 contains FFT data and target information derived in each of the previous processing section (for example, processor processing section PA (FIG. 4)) and the current processing section (for example, processor processing section PB (FIG. 4)). It will be remembered. That is, the memory 18 stores a plurality of time-series FFT data and a plurality of time-series target information.

The transmission control unit 202 outputs a modulation signal generation instruction to the signal generation unit 203 based on the instruction from the signal processing unit 201. For example, the signal processing unit 201 gives an output instruction of a modulation signal generation instruction to the transmission control unit 202 at the times t0, t5, and t10 shown in FIG.

<Processing of radar device>
FIG. 6 is a flowchart provided for explaining an example of processing of the radar device of the first embodiment. In the flowchart of FIG. 6, the process of step S101 is executed at time t0 to t4 and time t5 to t9 (FIG. 4), and the process of steps S103 to S133 is the processor processing section PA (time t4 to t5) and the processor process. It is executed in the interval PB (time t9 to t10). Further, for each of the processes of steps S103 to S133 in the flowchart of FIG. 6, when the "previous process" is executed in the processor processing section PA, the "current process" is executed in the processor processing section PB.

First, in step S101, the transmission signal TX transmitted from the transmission antenna 12 arrives at the radar device 1 by being reflected by the object, and is received as the reception signal RX by the reception antenna 13. An analog beat signal BS is generated by mixing the transmission signal TX and the reception signal RX with the mixer 14. The analog beat signal BS is converted into a digital beat signal BS by the ADC 16, and the converted digital beat signal BS is input to the signal processing unit 201.

Next, in step S103, the signal processing unit 201 acquires FFT data in each of the UP section and the DOWN section by applying the FFT to the beat signal BS input from the ADC 16.

Next, in step S105, the signal processing unit 201 performs peak extraction processing to acquire peaks of FFT data in each of the UP section and the DOWN section. In the peak extraction process, the signal processing unit 201 extracts a peak in which the power of the FFT data in the UP section exceeds a predetermined threshold from the FFT data to acquire the UP peak, and the power of the FFT data in the DOWN section sets the predetermined threshold. The exceeding peak is extracted from the FFT data to acquire the DOWN peak.

Next, in step S107, the signal processing unit 201 has a peak having temporal continuity with the peak related to the past target from the peaks extracted in the current peak extraction process (step S105) (hereinafter, "" Performs "history peak extraction processing" to extract (sometimes called "history peak").

That is, in step S107, the signal processing unit 201 sets the predicted value of the peak derived in the “next prediction process (step S121)” executed in the previous processing section of the processor 17 for each of the UP section and the DOWN section ( In the following, peaks within a predetermined frequency range based on the frequency of (sometimes referred to as “predicted peak”) are extracted as historical peaks. Hereinafter, the predicted value of the UP peak may be referred to as a “predicted UP peak”, and the predicted value of the DOWN peak may be referred to as a “predicted DOWN peak”. Further, in the following, the history peak of the UP section may be referred to as a “history UP peak”, and the history peak of the DOWN section may be referred to as a “history DOWN peak”. Hereinafter, the process of step S107 will be described in more detail.

7 and 8 are diagrams for explaining an operation example of the signal processing unit of the first embodiment. FIG. 7 shows the UP peak in the FFT data, and FIG. 8 shows the DOWN peak in the FFT data. 7, the signal processing unit 201 searches the history UP peak within a range of ± 3Bin around the frequency _{f eup} predicted UP peak. Case shown in Figure 7, within ± 3Bin frequency _{f eup,} since power is present threshold value TH or more UP peak _{f Stay up-is,} the signal processing unit 201 extracts the UP peak _{f Stay up-as} history UP Peak .. For example, 1 bin is about 468 Hz.

Similarly, in FIG. 8, the signal processing unit 201 searches the history DOWN peak within a range of ± 3Bin around the frequency _{f edn} prediction DOWN peak. The case shown in FIG. 8, within ± 3Bin frequency _{f edn,} since power is present threshold value TH or more DOWN peak _{f dn} is, the signal processing unit 201 extracts the DOWN peak _{f dn} as history DOWN peak ..

If there are a plurality of peaks whose power is equal to or higher than the threshold value TH within ± 3 bin with respect to the frequency of the predicted peak, the signal processing unit 201 records the peak existing at the frequency position closest to the frequency of the predicted peak as a historical peak. Extract as.

Next, in step S109, the signal processing unit 201 sets the peak in each section in which the frequency difference between the UP peak and the DOWN peak corresponds to the own vehicle speed as a stationary object based on the own vehicle speed information input from the vehicle speed sensor 40. It is extracted as a corresponding peak (hereinafter sometimes referred to as a "stationary object peak"). Here, the stationary object is an object having a relative speed of about the same magnitude as the own vehicle speed, and the moving object is an object having a relative speed of a magnitude different from the own vehicle speed.

The history peak extraction process (step S107) and the resting object peak extraction process (step S109) are performed on the target that the radar device 1 needs to give priority to the vehicle control device 2. This is to select the corresponding peak. For example, among the targets corresponding to the peaks extracted in the current peak extraction process (step S105), the targets corresponding to the peaks having temporal continuity with the peaks of the previous target are selected in this process. Compared to the target corresponding to the newly extracted peak, the probability of existence is high. Therefore, peaks with temporal continuity may have a higher priority than newly extracted peaks. Further, for example, since a moving object is more likely to collide with the vehicle CR than a stationary object, the peak corresponding to the moving object may have a higher priority than the peak corresponding to the stationary object.

Next, in step S111, the signal processing unit 201 calculates the orientation of the target based on the extracted peaks in each of the UP section and the DOWN section. For example, the signal processing unit 201 derives the direction (angle) of the target by using a predetermined direction calculation algorithm such as ESPRIT (Estimation of Signal Parameters via Rotational Invariance Techniques). When ESPRIT is used, the signal processing unit 201 calculates the eigenvalues of the correlation matrix, the eigenvectors, etc. from the phase information of the received signal RX in the receiving antenna 13, and corresponds to the angle θ _up corresponding to the UP peak and the DOWN peak. Derivation of the angle θ _dn. Then, the signal processing unit 201 _{derives the angle of the target from the angle θ up} and the angle θ _dn according to the equation (3). Note that one peak may contain information on a plurality of targets. For example, in the position information of the target with respect to the radar device 1, the information of a plurality of targets having the same distance but different angles may be included in the peaks of the same frequency. In such a case, since the phases of the plurality of received signals RX arriving from different angles are different from each other, the signal processing unit 201 has a plurality of targets for one peak based on the phase of each received signal RX. A plurality of angles corresponding to each are derived.

Next, in step S113, the signal processing unit 201 performs a "pairing process" of pairing the UP peak and the DOWN peak. In this pairing process, among all the peaks extracted in the peak extraction process (step S105), the history peaks extracted in the history peak extraction process (step S107) are the history UP peak and the history DOWN peak. It is done in between. Of all the peaks extracted in the peak extraction process (step S105), the stationary peaks extracted in the stationary peak extraction process (step S109) are the stationary peaks in the UP section (hereinafter, “stationary UP peaks”). ”) And the stationary peak in the DOWN section (hereinafter, may be referred to as“ stationary DOWN peak ”). Further, among all the peaks extracted in the peak extraction process (step S105), the remaining peaks excluding the historical peak and the resting object peak (hereinafter, may be referred to as “residual peak”) are in the UP section. The pairing process is performed between the remaining peak of DOWN (hereinafter sometimes referred to as "remaining UP peak") and the remaining peak of the DOWN section (hereinafter sometimes referred to as "remaining DOWN peak").

The pairing process of the UP peak and the DOWN peak is performed using, for example, an operation using the “Mahalanobis distance”. For example, before mounting the radar device 1 on the vehicle CR, the UP peak and the DONW peak are paired on a trial basis, and the pair data is paired with the correct combination in a plurality of pairings, which is "normal pair". , Acquire a plurality of "mispairs", which are pair data paired with an incorrect combination in a plurality of pairings. Then, in each of the plurality of normal pairs, the three parameter values of "frequency spectrum power difference", "angle difference", and "angle spectrum power difference" between the UP peak and the DOWN peak are obtained. The average value for each of the three parameters is derived from the plurality of normal pairs and stored in the memory 18 in advance.

Then, when the processor 17 derives the target information after mounting the radar device 1 on the vehicle CR, the signal processing unit 201 has three parameter values in all combinations of the UP peak and the DOWN peak, and a plurality of parameter values. _{The Mahalanobis distance D M} (x) is derived by Eq. (4) using the average value for each of the three parameters between the normal pairs. The signal processing unit 201 derives a pair Mahalanobis distance D _M in the current processing (x) is minimum as the duplex. Here, the Mahalanobis distance D _M (x) is the average is μ = (μ1, μ2, μ3 ) in ^T, expressed in multivariate vector such as the covariance matrix is Σ x = (x1, x2, x3) It is for a group of values and is derived by Eq. (4). The elements μ1, μ2, and μ3 indicate the three parameter values of the normal pair, and the elements x1, x2, and x3 indicate the three parameter values of the pair of this processing.

Then, in this pairing process, the signal processing unit 201 derives the vertical distance, the relative speed, and the horizontal distance of the normal pair by using the parameter values of the normal pair and the equations (1) to (3). The pairing process using the history peak will be described later.

Next, in step S115, the signal processing unit 201 combines the pair data paired by the current pairing process (step S113) (hereinafter, may be referred to as “this time pair”) with the previous pairing process (step). It is determined whether or not there is temporal continuity with the pair data paired by S113) (hereinafter, may be referred to as a "previous pair"). Here, when there is a temporal continuity between the current pair and the previous pair, for example, the current pair predicted based on the previous pair (hereinafter, may be referred to as "predicted pair") and the actual pair. This is the case where the difference in vertical distance, the difference in lateral distance, and the difference in relative velocity between the pair and the pair acquired in the above are all within the predetermined values. In this case, it is determined that the target detected by the current process and the target detected by the previous process are the same target. When a plurality of current pairs exist within a predetermined value, the signal processing unit 201 has temporal continuity with the previous pair for the current pair having the smallest difference from the predicted pair among the plurality of current pairs. Judge as pair data.

On the other hand, when the difference in vertical distance, the difference in lateral distance, or the difference in relative speed between the predicted pair and the actually acquired current pair is not within a predetermined value, the signal processing unit 201 sets the current pair. It is determined that there is no temporal continuity between the pair and the previous pair. Then, the current pair, which is determined to have no temporal continuity with the previous pair in this way, becomes the pair data derived for the first time in this processing (hereinafter, may be referred to as a "new pair").

Then, in step S117, the signal processing unit 201 increases the vertical distance, relative speed, lateral distance, and power between the current pair and the predicted pair when there is temporal continuity between the current pair and the previous pair. The value of is filtered to derive the filtered pair data (hereinafter sometimes referred to as "filter data").

For example, when there is a temporal continuity between the current pair and the previous pair, the signal processing unit 201 weights the lateral distance of the predicted pair by 0.75 for the lateral distance, and the lateral distance of the current pair. The distance is weighted by 0.25, and the weighted lateral distances are added together to derive the lateral distance of the filter data in this process. The signal processing unit 201 also filters the values of the vertical distance, the relative speed, and the power in the same manner as the horizontal distance.

Next, in step S119, the signal processing unit 201 determines whether the target is a target related to a moving object or a stationary object based on the own vehicle speed and the relative speed of the target. Perform "moving object determination process". In the moving object determination process, the signal processing unit 201 sets the "moving object flag" of the pair data corresponding to the target related to the moving object to ON, and sets the "moving object flag" of the pair data corresponding to the target related to the stationary object to ON. Set "Flag" to OFF. That is, the "moving object flag" is a flag indicating whether the detected target is a target related to a moving object or a target related to a stationary object. In the target information output unit 204, the pair data in which the moving object flag is set to ON is recognized as the pair data corresponding to the moving object, and the pair data in which the moving object flag is set to OFF corresponds to the stationary object. It is recognized as pair data to be processed.

Next, in step S121, the signal processing unit 201 uses the filter data, the filter data corresponding to the preceding vehicle, and another vehicle traveling in front of the own vehicle in the direction opposite to the own vehicle (hereinafter, "oncoming vehicle"). It is classified into filter data corresponding to (sometimes called) and filter data corresponding to a stationary object. For example, the signal processing unit 201 classifies the filter data having a relative speed larger than the reverse speed of the own vehicle speed into the filter data corresponding to the preceding vehicle, and has a relative speed smaller than the reverse speed of the own vehicle speed. The filter data is classified into the filter data corresponding to the oncoming vehicle, and the filter data having a relative speed substantially the same as the speed in the opposite direction of the own vehicle speed is classified into the filter data corresponding to the stationary object.

Next, in step S123, the signal processing unit 201 derives predicted values (predicted vertical distance, predicted relative velocity, predicted lateral distance, etc.) to be used in the next history peak extraction process (step S107). For example, the signal processing unit 201 identifies a predetermined number of filter data having a high priority in controlling the vehicle CR, derives each predicted peak of the UP peak and the DOWN peak corresponding to the specified filter data, and derives the predicted peaks. Using the derived predicted peak, the history peak extraction process (step S107) in the next processing section of the processor 17 is performed. Regarding the priority of filter data, in ACC, the vehicle CR has a horizontal position corresponding to the lane in which the vehicle CR is traveling (hereinafter, may be referred to as "own lane"), and the vertical distance from the vehicle CR is large. The priority of the filter data which is relatively small is high, the priority of the filter data which has a horizontal position corresponding to the lane adjacent to the own lane and the vertical distance to the vehicle CR is relatively large is low.

For example, the signal processing unit 201 executes a process reverse to the process of pairing the UP peak and the DOWN peak to separate the filter data into the UP peak and the DOWN peak. Then, the signal processing unit 201 derives the predicted UP peak using the frequency information and the angle information of the UP peak, and derives the predicted DOWN peak using the frequency information and the angle information of the DOWN peak.

Next, in step S125, the signal processing unit 201 removes filter data that does not need to be output to the vehicle control device 2 as target information from the filter data derived in the processing so far. For example, the signal processing unit 201 corresponds to a stationary object (for example, a cantilever type or gate type road sign provided above the roadway) existing at a position higher than the vehicle height of the vehicle CR by a predetermined distance. The filter data is removed from the filter data derived in the previous processing. Further, for example, the signal processing unit 201 has so far used filter data corresponding to a stationary object (for example, a road stud installed on a median strip of a road or a curve) existing at a position lower than the bottom of the vehicle CR. It is removed from the filter data derived by the process of. Further, for example, the signal processing unit 201 has an interval between a peak corresponding to a target actually existing at a position equal to or more than a predetermined distance from the radar device 1 and switching noise in the DC-DC converter of the power supply device of the radar device 1. The filter data corresponding to the ghost peak caused by interference (intermodulation) is removed from the filter data derived by the processing so far. Therefore, the stationary object existing at a position higher than the vehicle height of the vehicle CR by a predetermined distance, the stationary object existing at a position lower than the bottom of the vehicle CR, and the filter data corresponding to the ghost peak are used as target information for vehicle control. Not output to device 2.

Next, in step S127, the signal processing unit 201 calculates the reliability of the target derived in this processing, and weights the calculated reliability with the reliability of the target derived up to the previous processing. to add. It should be noted that such addition processing is performed for each target. In the following, the reliability weighted and added for each target may be referred to as "additional reliability". Here, the reliability of the target is an index indicating whether or not the target information of the target is appropriate as the target information output to the vehicle control device 2, and the higher the reliability of the target information of the target, the more the vehicle. It is considered to be more appropriate as the target information output to the control device 2. In other words, a target with relatively high reliability is a target related to an object that collides with the vehicle when it travels in the direction of travel. Further, a target having a relatively low reliability is a target related to an object that does not collide when the own vehicle moves in the traveling direction.

For example, the reliability of the target is calculated based on the received signal level, and the higher the received signal level, the larger the reliability of the value is calculated. For example, the target information related to the target information related to the stopped vehicle or the preceding vehicle is more suitable as the target information output to the vehicle control device 2 than the target information related to the target information related to the upper object or the lower object. Therefore, the reliability of the target for the stopped vehicle or the preceding vehicle is calculated to be larger than the reliability of the target for the upper object or the lower object. The reliability of the target is sometimes called the "confidence level".

Next, in step S129, the signal processing unit 201 takes over the reliability between the pair data (that is, between the targets). The reliability inheritance process in step S129 will be described later.

Next, in step S131, the signal processing unit 201 performs a "combination process" of combining a plurality of filter data corresponding to one object into one. For example, when the radar device 1 receives a plurality of received signals that are reflected by a plurality of reflection points of the same object and arrive, the signal processing unit 201 has a plurality of received signals having different position information from each other based on the received signals. Derived the filter data of. However, since these plurality of filter data are originally filter data corresponding to one object, the signal processing unit 201 combines these plurality of filter data into one, so that a plurality of filters corresponding to the same object can be obtained. The data is treated as one group data. Therefore, for example, if the relative speed of each filter data is substantially the same among the plurality of filter data and the vertical distance and the horizontal distance of each filter data are within a predetermined range, the signal processing unit 201 performs the plurality of filters. The data are regarded as related to the same object, and the plurality of filter data are combined into one group data corresponding to one object. The "combination process" is sometimes referred to as a "grouping process" or a "grouping process".

Then, in step S133, the target information output unit 204 selects a predetermined number of group data having a high priority from the group data after the join processing (step S131) is performed, and targets the selected group data. It is output to the vehicle control device 2 as information. Further, the target information output unit 204 selects group data having an addition reliability equal to or higher than the threshold value from the group data after the combination process (step S131) is performed, and uses the selected group data as the target information for vehicle control. Output to device 2. That is, the target information output unit 204 outputs only the group data corresponding to the target whose addition reliability is equal to or higher than the threshold value to the outside of the radar device 1 as the target information. As the addition reliability after the combination processing, for example, it is preferable to use the maximum value among the plurality of addition reliabilitys of the plurality of targets corresponding to the plurality of filter data to be combined.

<Pairing process>
FIG. 9 is a flowchart provided for explaining an example of the pairing process of the first embodiment. The series of pairing processes shown in FIG. 9 corresponds to the process of step S113 shown in FIG.

In FIG. 9, first, in step S301, the signal processing unit 201 derives a “history pair” which is pair data obtained by pairing the history UP peak and the history DOWN peak extracted in the history peak extraction process (step S107). ..

Here, the history pairing process in step S301 will be described in more detail. FIG. 10 is a flowchart provided for explaining an example of the history pairing process of the first embodiment.

In FIG. 10, in step S311, the signal processing unit 201 extracts the history UP peak and the history DOWN peak corresponding to the predicted UP peak and the predicted DOWN peak from the history peaks included in the predetermined frequency range, respectively. "History peak determination processing" is performed.

FIG. 11 is a flowchart provided for explaining an example of the normal history peak determination process of the first embodiment.

In FIG. 11, in step S329, the signal processing unit 201 uses an angle derived from the history peak and an angle derived from the predicted peak (hereinafter referred to as “predicted angle”) from the history peaks extracted in step S107. The historical peak whose difference from (may be) is 4 degrees or less is extracted. For example, the signal processing unit 201 derives the angle by performing the same processing as the above-mentioned directional calculation using the history UP peak extracted in step S107. Then, the signal processing unit 201 compares the derived angle with the predicted angle derived from the predicted UP peak, and the history UP peak in which the angle difference between the two is within ± 4 degrees (hereinafter, “normal history UP”). (Sometimes called "peak") is extracted. Further, the signal processing unit 201 compares the angle derived from the history DOWN peak with the predicted angle derived from the predicted DOWN peak for the history DOWN peak as well as the history UP peak, and the angle difference between the two is 4 The history DOWN peak within the degree (hereinafter, may be referred to as "normal history DOWN peak") is extracted. Hereinafter, the “normal history UP peak” and the “normal history DOWN peak” may be collectively referred to as the “normal history peak”. Hereinafter, the process of step S329 will be described in more detail.

12 and 13 are diagrams for explaining an operation example of the signal processing unit of the first embodiment. The signal processing unit 201 derives the _{angle θ up} by the directional calculation based on _{the history UP peak f up} extracted in the process of step S107. FIG. 12 shows an angle spectrum derived from the _{history UP peak up.} 12, the signal processing unit 201, within ± 4 degrees from the prediction angle theta _eup derived from predicted UP peak determines whether power is included the threshold TH or more angles theta _{Stay up-. Then, when the angle θ up} whose power is equal to or higher than the threshold value TH is within ± 4 degrees from the predicted angle θ _eup , the signal processing unit 201 determines the history UP peak f _up as the normal history UP peak.

Similarly, the signal processing unit 201 derives the _{angle θ dn} by the directional calculation based on _{the history DOWN peak f dn extracted in the process of step S107.} FIG. 13 shows an angular spectrum derived from the historical DOWN peak f _dn. In FIG. 13, the signal processing unit 201 determines whether or not _{an angle θ dn} whose power is equal to or higher than the threshold value TH _{is included within ± 4 degrees from the predicted angle θ edn derived from the predicted DOWN peak. Then, when the angle θ dn} whose power is equal to or higher than the threshold value TH is within ± 4 degrees from the predicted angle θ _edn , the signal processing unit 201 determines the history DOWN peak f _dn as the normal history DOWN peak.

Incidentally, if the predicted angle theta plurality of angle theta _{Stay up-power} is equal to or more than the threshold value TH within ± 4 degrees relative _eup is present, the signal processing unit 201 corresponds to the nearest angle theta _{Stay up-to} predict the angle theta _eup The history UP peak is determined as the normal history UP peak. _{Similarly, when there are a plurality of angles θ dn} whose power is equal to or greater than the threshold TH within ± 4 degrees with respect to the predicted angle θ _edn , the signal processing unit 201 corresponds to the angle θ _{dn closest to the predicted angle θ edn.} The history DOWN peak to be performed is determined as the normal history DOWN peak.

Returning to FIG. 11, in step S331, the signal processing unit 201 performs “normal history peak determination processing” for determining whether or not both the normal history UP peak and the normal history DOWN peak are present. For example, when both the normal history UP peak and the normal history DOWN peak satisfying the condition of step S329 exist, the signal processing unit 201 determines that the normal history peak exists. On the other hand, when either or both of the normal history UP peak and the normal history DOWN peak that satisfy the conditions of step S327 and step S329 do not exist, the signal processing unit 201 determines that the normal history peak does not exist. do.

Returning to FIG. 10, when the signal processing unit 201 determines that the normal history peak exists in the determination in step S331 (step 313: Yes), the signal processing unit 201 pairs the normal history UP peak with the normal history DOWN peak. A history pair is derived (step S317).

On the other hand, when the signal processing unit 201 determines in the determination in step S331 that the normal history peak does not exist (step 313: No), the process proceeds to the “one-sided history peak extraction process” in step S315.

Here, in the normal history peak determination process (step S311), the signal processing unit 201 determines whether or not both the normal history UP peak and the normal history DOWN peak exist. Therefore, when the signal processing unit 201 determines in step S331 that either the normal history UP peak or the normal history DOWN peak does not exist, the signal processing unit 201 determines that the normal history peak does not exist, but the normal history UP peak or the normal history UP peak or It holds the determination result that only one of the normal history DOWN peaks exists. Therefore, in the one-sided history peak extraction process (step S315), the signal processing unit 201 uses the result of the normal history peak determination process (step S311) to determine that one of the normal history UP peak and the normal history DOWN peak is normal. Extract historical peaks. Then, in step S315, when the signal processing unit 201 has any one of the normal history UP peak and the normal history DOWN peak, it determines that the one-sided history peak exists and sets the "one-sided history pair flag". If it is set to ON and both peaks do not exist, it is determined that the one-sided history peak does not exist and the "one-sided history pair flag" is set to OFF.

Then, when the signal processing unit 201 determines in step S315 that a one-sided history peak exists, for example, one existing normal history UP peak or normal history DOWN peak and the other predicted DOWN peak or predicted UP peak are displayed. A history pair is derived by pairing.

Returning to FIG. 9, the signal processing unit 201 executes the history pairing process (step S301), and then performs the pairing process for the stationary peak extracted in the stationary peak extraction process (step S109) in step S303. .. In step S303, the signal processing unit 201 pairs the stationary object UP peak and the stationary object DOWN peak. The signal processing unit 201 performs pairing of the stationary object UP peak and the stationary object DOWN peak in the same manner as the pairing of the historical UP peak and the historical DOWN peak.

Next, in step S305, the signal processing unit 201 pairs the remaining UP peak and the remaining DOWN peak. The signal processing unit 201 performs pairing of the remaining UP peak and the remaining DOWN peak in the same manner as the pairing of the history UP peak and the history DOWN peak. The pair data of the remaining UP peak and the remaining DOWN peak corresponds to the above new pair.

Next, in step S307, the signal processing unit 201 calculates the vertical distance, the relative speed, the angle, the horizontal distance, and the like based on the pair data derived in each of the above pairing processes. The signal processing unit 201 has a vertical distance, a relative velocity, an angle, and a lateral direction based on the pair data derived in the stationary object pairing process (step S303) or the pair data derived in the new pairing process (step S305). When calculating the distance, it can be calculated in the same manner as when the equations (1) to (3) are used.

Further, when the signal processing unit 201 calculates the vertical distance, the relative speed, the angle, and the horizontal distance based on the pair data derived in the history pairing process (step S301), the signal processing unit 201 calculates as follows.

That is, first, the signal processing unit 201 extracts a history pair in which the one-sided history pair flag is set to ON. Of the two peaks included in the history pair for which the one-sided history pair flag is set to ON, one peak is the normal history UP peak or the normal history DOWN peak, so the other peak is the history DOWN peak or history. It is an UP peak, or a predicted DOWN peak or a predicted UP peak.

Next, the signal processing unit 201 determines whether or not the priority own vehicle lane preceding vehicle status flag of the extracted history pair is set to ON.

Next, the signal processing unit 201 determines whether or not a peak of FFT data (hereinafter, may be referred to as “FFT peak”) exists in the peak of the history pair in which the priority own vehicle lane preceding vehicle status flag is set to ON. If there is an FFT peak, the distance or the like is calculated using the FFT peak. For example, when the history pair is formed from the normal history UP peak and the history DOWN peak, the signal processing unit 201 uses the FFT peak of the normal history UP peak and the FFT peak of the history DOWN peak to set the distance and the relative velocity. Etc. are calculated. Further, since the history DOWN peak has no angle information, the signal processing unit 201 derives the angle of the normal history UP peak as the angle of the history pair. The calculation of the distance and the like using the FFT peak can be performed using the equations (1) to (3). That is, the signal processing unit 201, in the formula (1) and (2), using the frequency of the FFT peak normal history UP peak as _{f Stay up-,} using the frequency of the FFT peak history DOWN peak as _{f dn.} Further, in the equation (3), the signal processing unit 201 uses the angle derived from the normal history UP peak as θ _up , and does not use _{θ dn.}

On the other hand, if the FFT peak does not exist in the peak of the history pair in which the priority vehicle lane preceding vehicle status flag is set to ON, one of the two peaks included in the history pair is the predicted peak. The signal processing unit 201 calculates the distance and the like using the predicted peak. For example, when the history pair is formed from the normal history UP peak and the predicted DOWN peak, the signal processing unit 201 calculates the distance and the relative velocity using the FFT peak of the normal history UP peak and the predicted peak. .. Further, although the signal processing unit 201 can derive the predicted angle from the predicted DOWN peak, the angle of the normal history UP peak may be derived as the angle of the history pair. The calculation of the distance and the like using the predicted peak can be performed using the equations (1) to (3). That is, the signal processing unit 201, in the formula (1) and (2), using the frequency of the FFT peak normal history UP peak as _{f Stay up-,} using the frequency of the FFT peaks predicted DOWN peak as _{f dn.} Further, in the equation (3), the signal processing unit 201 uses the angle derived from the normal history UP peak as θ _up , and does not use _{θ dn.}

In the above, the case where the one-sided history peak exists has been described. For example, when neither the normal history peak nor the one-sided history peak exists, the distance and the relative velocity are used by using the predicted peaks in both the UP section and the DOWN section. And the angle may be calculated.

<Reliability takeover processing>
FIG. 14 is a flowchart for explaining an example of the reliability inheritance process of the first embodiment, and FIG. 15 is a diagram for explaining an operation example of the signal processing unit of the first embodiment. In FIG. 15, a predetermined region AR is set within the scanning range of the beam pattern NA of the central axis BL. The length of the region AR in the vertical distance direction is defined as "α", and the length of the region AR in the lateral distance direction is defined as "± β" about the central axis BL. Then, for example, a target P1 having a rear bumper installed at the rear end of a truck as a stopped vehicle as a reflection point and a side mirror installed near the driver's seat at the front of the truck as a stopped vehicle as a reflection point. The target P2 to be used exists in the area AR.

In FIG. 14, in step S141, the signal processing unit 201 determines whether or not the “condition group A” is satisfied. The "condition group A" includes the following conditions 1 to 5, and the signal processing unit 201 determines that the condition group A is satisfied when all of the conditions 1 to 5 are satisfied. Further, the case where both the condition 3 and the condition 4 of the conditions 1 to 5 are satisfied corresponds to the case where a plurality of pair data different from each other belong to the same object, for example, the target P1 and the object. The mark P2 corresponds to the case where the mark P2 is a target related to a vertically cracked object. That is, in step S141, the signal processing unit 201 determines whether or not a plurality of different targets belong to the same object. Further, here, it is assumed that the target P1 is derived later than the target P2 after the target P2 is derived. That is, in the radar device 1, it is assumed that the target P2 is detected earlier in time than the target P1. A multipath wave is received from the bottom of the vehicle body of a truck provided with a battery or the like, and this multipath wave interferes with a direct wave from the rear end of the truck, delaying the detection of the target P1 at the rear end. There is a time lag in the detection of such targets.

Hereinafter, some conditions for determining whether or not a plurality of targets (for example, target P1 and target P2) belong to the same object will be described.
<Condition 1>
The target P1 is the target closest to the radar device 1.
<Condition 2>
X1 <Vertical distance of target P1 <X2
For example, X1 = 80m and X2 = 105m.
<Condition 3>
Vertical distance of target P1 <vertical distance of target P2 ≤ vertical distance of target P1 + α
<Condition 4>
Absolute value of the lateral distance of the target P1 and absolute value of the lateral distance of the target P2 <β
<Condition 5>
The number of targets existing in the area AR is less than or equal to the threshold value. For example, when the threshold value is "2", the condition 5 is satisfied only for the target P1 and the target P2 in the area AR, and the target other than the target P1 and the target P2 is in the area AR. If it does not exist.

If the condition group A is satisfied in step S141 (step S141: Yes), the process proceeds to step S143. On the other hand, if the condition group A is not satisfied, that is, if any of the conditions 1 to 5 is not satisfied (step S141: No), the reliability transfer process is terminated.

In step S143, the signal processing unit 201 calculates the following four parameters (parameters 1 to 4) for the target P1 that satisfies the condition group A. Hereinafter, other conditions for determining whether or not a plurality of targets (for example, target P1 and target P2) belong to the same object will be described.
<Parameter 1>
Target distance difference w = (vertical distance of target P2)-(vertical distance of target P1)
<Parameter 2>
Target angle difference x = (angle of target P2)-(angle of target P1)
<Parameter 3>
Target relative velocity difference y = (relative velocity of target P2)-(relative velocity of target P1)
<Parameter 4>
Target angle power difference z = (power of target P2 in the angle spectrum)
-(Power of target P1 in the angle spectrum)

Here, each parameter of the target whose reliability is to be inherited is distributed with the parameters having a correlation with each other centering on a specific value. On the other hand, since each parameter of the target whose reliability is not inherited can take any value, its distribution does not have a peak.

Therefore, in step S145, the signal processing unit 201 sets the parameters 1 to 4 (target distance difference w, target angle difference x, target relative velocity difference y, target angle power difference z) calculated in step S143. On the other hand, the vertical crack model and the stationary object model shown in FIG. 16 are applied, and the score is calculated as follows. FIG. 16 is a diagram for explaining an operation example of the signal processing unit of the first embodiment. In FIG. 16, the vertical crack model is defined as a multivariate normal distribution and the rest model is defined as a uniform distribution. The vertical crack model and the stationary model are examples of statistical models.

Further, the likelihood when the target distance difference w is used as a parameter is calculated as shown in FIG. FIG. 17 is a diagram for explaining an operation example of the signal processing unit of the first embodiment. Using the normal distribution as shown in FIG. 17, for example, when the target distance difference w is 1.2 m, the likelihood is calculated as 0.7, and when the target distance difference w is 1.4 m, the likelihood is calculated as 0.2. Will be done. With respect to the target angle difference x, the target relative velocity difference y, and the target angle power difference z, the likelihood can be calculated using the normal distribution in the same manner as the target distance difference w.

Therefore, first, in step S145, the signal processing unit 201 calculates the “vertical crack likelihood f (x)” according to the equations (5) to (7). In equation (5), "m" represents the number of parameters, in equations (5) and (6), "S" represents the covariance matrix, and in equations (5) and (7), "D ² " is Mahalanobis. Represents the distance. Here, m = 4. Further, in the equations (6) and (7), the parameter values of w, x, y, and z are calculated by this processing, and the average value, the variance, and the variance other than w, x, y, and z are calculated. The covariance is calculated in advance from the normal pair acquired before mounting the radar device 1 on the vehicle CR, and is stored in the memory 18.

Then, the signal processing unit 201 calculates the score according to the equation (8), and cumulatively adds it to the score calculated up to the previous processing. In the following, the cumulatively added score may be referred to as "cumulative score". The rest object likelihood in the equation (8) corresponds to the rest object model likelihood shown in FIG. 16 and takes a constant value regardless of the magnitude of the parameter value. Further, the cumulative score indicates the certainty that both the target P1 and the target P2 are pair data corresponding to the vertically cracked object, and the larger the cumulative score, the more both the target P1 and the target P2 are. More likely to belong to a vertically cracked object.
Score = log (vertical crack likelihood f (x) / rest object likelihood) ... (8)

Next, in step S147, the signal processing unit 201 determines whether or not the "condition group B" is satisfied. The "condition group B" includes the following conditions 6 to 10, and the signal processing unit 201 determines that the condition group B is satisfied when all of the conditions 6 to 10 are satisfied. Hereinafter, other conditions for determining whether or not a plurality of targets (for example, target P1 and target P2) belong to the same object will be described.
<Condition 6>
In the previous joining process (step S131), the target P1 and the target P2 were combined.
<Condition 7>
In the previous combination process (step S131), the pair data combined with the target P1 was only the target P2, and the pair data combined with the target P2 was only the target P1.
<Condition 8>
Cumulative score ≥ predetermined threshold <Condition 9>
Existence time of target P1 ≤ Existence time of target P2 <Condition 10>
Additive reliability of target P1 <Additive reliability of target P2

If the condition group B is satisfied in step S147 (step S147: Yes), the process proceeds to step S149. On the other hand, if the condition group B is not satisfied, that is, if any of the conditions 6 to 10 is not satisfied (step S147: No), the reliability takeover process is terminated.

In step S149, the signal processing unit 201 inherits the addition reliability of the target P2 to the target P1. Since the target P1 is pair data derived later than the target P2, the additional reliability of the target P1 is the addition of the target P2 before the addition reliability of the target P2 is handed over to the target P1. Small compared to reliability. Therefore, by inheriting the addition reliability of the target P2 to the target P1, the addition reliability of the target P1 is increased, and the time until the addition reliability of the target P1 reaches the threshold value is shortened.

For example, when the addition reliability of the target P1 is "10" and the addition reliability of the target P2 is "82", the addition reliability of the target P2 is inherited by the target P1 to add the target P1. The reliability is changed from "10" to "82". For example, when the threshold value of the addition reliability is "91", the addition reliability of the target P2 is reflected rather than the addition reliability "10" of the target P1 before the addition reliability of the target P2 is reflected. The later addition reliability "82" of the target P1 is more likely to exceed the threshold "91" earlier. When the reliability of the target P1 related to the rear bumper exceeds the threshold value relatively quickly, the radar device 1 can quickly determine the type of the target P1 used as the reference point of the vehicle control device 2.

As described above, in the first embodiment, the radar device 1 has a signal processing unit 201 and a target information output unit 204. The radar device 1 transmits a transmission signal whose transmission frequency changes at a predetermined cycle, and receives a reception signal that arrives when the transmission signal is reflected by an object. Further, the radar device 1 acquires the peak of the frequency spectrum of the beat signal in the UP section and the DOWN section, and derives the target information based on the pair data of the UP peak and the DOWN peak. The target information output unit 204 outputs only the pair data whose addition reliability is equal to or higher than the threshold value to the outside of the radar device 1 as target information. The signal processing unit 201 determines whether or not the target P1 and the target P2 belong to the same object. The target P1 is pair data derived after the target P2. Then, when the signal processing unit 201 determines that the target P1 and the target P2 belong to the same object, the signal processing unit 201 inherits the reliability of the target P2 to the target P1.

That is, the radar device 1 handles the information acquired as the information regarding the type of the target P2 from the past processing to the current processing as the information regarding the type of the target P1. Then, the radar device 1 outputs the target information including the information regarding the type inherited from the target P2 by the target P1 to the vehicle control device 2. As a result, the vehicle control device 2 can execute appropriate control such as brake control of the vehicle based on the target information acquired from the radar device 1.

In this way, by inheriting the addition reliability of the target P2 to the target P1, the addition reliability of the target P1 is increased and the time until the addition reliability of the target P1 reaches the threshold value is shortened. , It is possible to prevent a delay in detecting a desired reference point of the vehicle control device 2 connected to the radar device 1.

Further, in the first embodiment, the signal processing unit 201 determines whether or not the reliability of the target P2 is inherited by the target P1 by using the statistical model relating to the parameters 1 to 4.

By doing so, it is possible to prevent the reliability from being inherited by pair data that is not suitable as the inheritance destination of the reliability.

[Example 2]
Next, the radar device 1 according to the second embodiment will be described. In the following, the parts different from those of the first embodiment will be mainly described, and the description of the overlapping parts will be omitted.

In Example 2, the statistical model used to calculate the score in the reliability inheritance process of Example 1 described above was changed. Specifically, in the reliability succession process of the second embodiment, the signal processing unit 201 calculates or acquires the following four parameters (see step S143 in FIG. 14).
<Parameter A>
Target vertical distance difference w1 = (vertical distance of target P2)-(vertical distance of target P1)
<Parameter B>
Target horizontal distance difference w2 = (horizontal distance of target P2)-(horizontal distance of target P1)
<Parameter C>
Target angle power difference z = (power of target P2 in the angle spectrum)
-(Power of target P1 in the angle spectrum)
<Parameter D>
Extrapolation processing factors 1-5

Next, the signal processing unit 201 calculates the score by applying a statistical model described later based on the parameters A to D (see step S145 in FIG. 14).

First, parameters A and B (target vertical distance difference w1 and target horizontal distance difference w2 (hereinafter, may be referred to as “vertical / horizontal distance difference w1 and w2”)) will be described. The vertical / horizontal distance differences w1 and w2 are correlated when the target P1 and the target P2 (see FIG. 15) are detected by vertical cracks in the target (for example, a stopped vehicle) whose reliability is to be inherited. There is a relationship.

Therefore, in the second embodiment, a two-dimensional normal distribution model (statistical model) in which both the vertical / horizontal distance differences w1 and w2 are used as parameters is defined in advance, and the signal processing unit 201 scores using the statistical model. Was calculated.

18A and 18B are diagrams for explaining an operation example of the signal processing unit 201 of the second embodiment. Specifically, FIG. 18A is a statistical model of the likelihood for the vertical / horizontal distance difference w1 and w2 when the targets P1 and P2 are detected, for example, by vertical cracks in a stopped vehicle in the own lane. Reference numeral 18B is a statistical model of the likelihood of the vertical / horizontal distance differences w1 and w2 when the targets P1 and P2 are detected, for example, by vertical cracks in the upper object.

In the following, the statistical model for vertical cracks in a stopped vehicle such as FIG. 18A will be referred to as a "vehicle vertical crack model", and the statistical model for vertical cracks in an upper object such as FIG. 18B will be referred to as an "upper object vertical crack model". In some cases. Further, the likelihood of the vehicle vertical crack model may be described as "vehicle vertical crack likelihood", and the likelihood of the upper object vertical crack model may be described as "upper object vertical crack likelihood".

The vehicle vertical crack model roughly corresponds to the "vertical crack model" of the first embodiment, and the upper object vertical crack model roughly corresponds to the "stationary object model" of the first embodiment. Further, the vehicle vertical crack model and the upper object vertical crack model of FIGS. 18A and 18B are examples of the first statistical model.

The signal processing unit 201 applies the vehicle vertical crack model and the upper object vertical crack model to the target vertical distance difference w1 and the target horizontal distance difference w2 calculated in step S143 to obtain the vehicle vertical crack likelihood and the upper object. Calculate the vertical crack likelihood. Then, the signal processing unit 201 calculates the score by appropriately applying each of the calculated likelihoods to the above equation (8). The vehicle vertical crack likelihood corresponds to the "vertical crack likelihood" of the equation (8), and the upper object vertical crack likelihood roughly corresponds to the "stationary object likelihood" of the equation (8).

Here, the vehicle vertical crack model and the upper object vertical crack model shown in FIGS. 18A and 18B will be described. The vehicle vertical crack likelihood is such that the target vertical distance difference w1 is within the predetermined distance difference range A1 and the target horizontal. When the distance difference w2 is within the predetermined distance difference range A2, it is larger than the upper object vertical crack likelihood.

On the other hand, the vehicle vertical crack likelihood is less than or equal to the upper object vertical crack likelihood when at least one of the target vertical distance difference w1 and the target horizontal distance difference w2 is outside the corresponding predetermined distance difference ranges A1 and A2. It has become.

Therefore, as can be seen from the equation (8) for calculating the score, the vehicle vertical crack model and the upper object vertical crack model have a predetermined distance difference range in which the target vertical distance difference w1 and the target horizontal distance difference w2 correspond to each other. The score when it is within A1 and A2 is higher than the score when at least one of the target vertical distance difference w1 and the target horizontal distance difference w2 is outside the predetermined distance difference range A1 and A2. Is set to. The predetermined distance difference ranges A1 and A2 can be said to indicate that the target P1 and the target P2 are likely to be detected by vertical cracks in the stopped vehicle in the own lane.

As described above, in the second embodiment, a statistical model (vehicle vertical crack model and upper object vertical crack model) in which both the target vertical distance difference w1 and the target horizontal distance difference w2 having a correlation are used as parameters is used. By using it, the score can be calculated accurately.

Next, the parameter C (target angle power difference z) will be described. FIG. 19 is a diagram for explaining an operation example of the signal processing unit 201 of the second embodiment. Specifically, FIG. 19 shows a vehicle vertical crack model and an upper object vertical crack model in which the target angle power difference z is a parameter.

The target angle power difference z is an example of the received power difference of the reflected wave between the target P1 and the target P2. Further, the vehicle vertical crack model and the upper object vertical crack model of FIG. 19 are examples of the second statistical model.

As shown in FIG. 19, both the vehicle vertical crack model and the upper object vertical crack model with respect to the target angle power difference z are defined in advance as normal distribution models. The signal processing unit 201 applies the vehicle vertical crack model and the upper object vertical crack model shown in FIG. 19 to the target angle power difference z calculated in step S143 to obtain the vehicle vertical crack likelihood and the upper object vertical crack likelihood. Calculate the degree. Then, the signal processing unit 201 calculates the score based on each of the calculated likelihoods.

As described above, in the second embodiment, the upper object vertical crack model (resting object model) defined as the uniform distribution in the first embodiment is now defined as the normal distribution, so that the score can be more accurately determined. Can be calculated.

Next, parameter D (factors 1 to 5 of extrapolation processing) will be described. Here, the extrapolation process will be described before the description of the parameter D is started.

As described above, the signal processing unit 201 determines the position of the target data of the current processing based on the target data (previous pair) derived by the previous processing in the continuity determination process (see step S115 in FIG. 6). Predict as a prediction pair. Then, when the vertical distance difference, the horizontal distance difference, etc. between the prediction pair and the target data (current pair) derived by the current processing are within a predetermined value, the signal processing unit 201 sets the current pair and the previous pair. Judge that there is temporal continuity between.

However, in the current processing of the signal processing unit 201, for example, the peak of the power of the FFT data is not extracted by the peak extraction processing (see step S105 in FIG. 6), and the object has continuity with the target data derived in the previous processing. The target data may not be derived.

In such a case, the signal processing unit 201 virtually derives the target data that has not been derived in the current process based on the parameters (vertical distance, horizontal distance, etc.) of the target data derived in the previous process. Perform "processing". The extrapolation data derived by the extrapolation process may be treated as the target data derived by the present process.

In this way, the extrapolation process is a process of predicting the virtual position of a target that is no longer detected by the current detection process based on the past position of the target when the detection process for detecting the target is repeatedly performed. Is.

By the way, for example, when targets P1 and P2 (see FIG. 15) are detected for one object (for example, a stopped vehicle or an upper object) and vertical cracks occur, the back side when viewed from the radar device 1 of the own vehicle. The target P2 in the above is likely to be extrapolated because the peak of the power of the corresponding FFT data is not extracted due to the influence of multipath or the like while the detection process is repeated.

Conventionally, if there is a target (target P2 in this case) that has been extrapolated, the score is not updated and the value of the previous processing is retained. On the other hand, in the second embodiment, the score is calculated according to the factor that the extrapolation process is executed. As a result, in the second embodiment, the score can be updated to an appropriate value even when extrapolation processing is performed on the target P2, for example.

FIG. 20 is a diagram provided for explaining an operation example of the signal processing unit 201 of the second embodiment. Specifically, FIG. 20 is a statistical model (table) in which factors 1 to 5 of extrapolation processing are used as parameters.

The statistical model of FIG. 20 aggregates the target data when extrapolation processing is performed on the target P2, for example, and the vehicle vertical crack likelihood and the upper object vertical crack according to the factors 1 to 5 of the extrapolation processing. This is a statistical model in which the likelihood is calculated and the score is calculated based on each likelihood. The statistical model of FIG. 20 is an example of the third statistical model.

In the statistical model of FIG. 20, specific numerical values are set for each likelihood and score, but here, those with a likelihood of 0.24 or more and relatively high are “high” and 0.1 or more. Less than 0.24 is classified as "medium", 0.01 or more and less than 0.1 is classified as "low", and less than 0.01 and extremely low is classified as "extremely low". Regarding the score, the one added to the cumulative score is described as "positive value", the value subtracted is described as "negative value", and the value not added or subtracted is described as "0".

21A to 21D are schematic views illustrating factors 1 to 4 of extrapolation processing. 21A to 21D show FFT data of the UP section and the DOWN section, and each graph corresponds to, for example, the graphs of FIGS. 7 and 8. Further, in FIGS. 21A to 21D, the two figures on the left side show the FFT data at the time of the previous processing, and the two figures on the right side show the FFT data at the time of the current processing and the target P2 is extrapolated. There is.

<Factor 1>
First, factor 1 of the extrapolation process will be described with reference to FIG. 21A. In FIG. 21A and the like, the history UP peak for the target P1 processed in the previous process is set to "fu1a", the history DOWN peak is set to "fd1a", the history UP peak for the target P2 is set to "fu2a", and the history DOWN peak is set to "fu2a". It was set as "fd2a". Further, the history UP peak for the target P1 processed this time was set to "fu1b", and the history DOWN peak was set to "fd1b".

As shown in FIG. 21A, since the historical UP peak and the historical DOWN peak exist in both the UP section and the DOWN section for the targets P1 and P2 of the previous processing, for example, pairing by pairing processing (see step S113 in FIG. 6). The ring and the like are made normal, and the targets P1 and P2 are both detected normally.

Then, in this processing, the history UP peak fu1b and the history DOWN peak fd1b for the target P1 exist. On the other hand, with respect to the target P2, the power of the received signal is reduced due to the influence of multipath or the like, and the history UP peak and the history DOWN peak do not exist in both the UP section and the DOWN section. Therefore, the extrapolation process is performed on the target P2. Shall be made.

Further, in factor 1, the history UP peak fu1b and the history DOWN peak fd1b of the target P1 are the frequencies _feep and the predicted DOWN peak of the predicted UP peak of the target P2 in both the UP section and the DOWN section. It is assumed that it is within the prediction range E including the frequency _{fedn of.}

The frequency f _edn frequency f _eup and prediction DOWN peaks predicted UP peak, as described above, the predicted value of peak derived based on the previous processing, also, for example, those that are predicted by extrapolation It is a frequency corresponding to the virtual position of the mark P2. Further, the prediction range E is, for example, is set from the frequency _{f eup} predicted UP peak (or frequency _{f edn} prediction DOWN peak) in the range of up to -3Bin, but is not limited thereto.

The peaks in the UP section and DOWN section of this processing are in the state shown on the right in FIG. 21A. For example, when one peak is a candidate for the history peaks of both the targets P1 and P2, it is on the front side. Since the processing related to the target P1 is prioritized, the one peak is regarded as the historical peak of the target P1, but the present invention is not limited to this.

Factor 1 is a case where the peaks of the UP section and the DOWN section in this processing are in the above-mentioned state and the extrapolation processing is reached. In such a case, as shown in the statistical model of FIG. 20, the vehicle vertical crack likelihood is "High", the likelihood of vertical cracking of the upper object is "low", and the score is "positive value".

Therefore, when the signal processing unit 201 extrapolates the target P2 due to factor 1, the signal processing unit 201 calculates the score (positive value) by applying the statistical model of FIG. 20, in other words, the targets P1 and P2 Calculate a score (positive value) indicating that there is a high possibility that a vertical crack was detected for a stopped vehicle. Conversely, the signal processing unit 201 calculates a score indicating that it is unlikely that the targets P1 and P2 are detected by vertical cracks in the upper object.

<Factor 2>
Next, factor 2 of the extrapolation process will be described with reference to FIG. 21B. As shown in FIG. 21B, it is assumed that both the targets P1 and P2 are normally detected in the previous process. Then, in this processing, while the history UP peak fu1b and the history DOWN peak fd1b exist, the peak for the target P2 disappears and the history UP peak and the history DOWN peak of the target P2 do not exist.

Further, in factor 2, it is assumed that the history UP peak fu1b and the history DOWN peak fd1b of the target P1 are outside the prediction range E of the target P2 in both the UP section and the DOWN section.

The peaks in the UP section and DOWN section of this processing are in the state shown on the right in Fig. 21B due to the influence of multipath, etc., and the vertically cracked object is higher than the case of a stopped vehicle. In some cases, such a state is likely to occur. Therefore, in the statistical model in the case of factor 2, as shown in FIG. 20, the vehicle vertical crack likelihood is "medium", the upper object vertical crack likelihood is "high", and the score is "negative value".

Therefore, the signal processing unit 201 calculates a score (negative value) by applying the statistical model of FIG. 20 when extrapolation processing is performed on the target P2 due to factor 2. That is, it is unlikely that the signal processing unit 201 has detected the targets P1 and P2 in the vertical crack of the stopped vehicle, or conversely, it is highly likely that the target P1 and P2 have been detected in the vertical crack of the upper object. Calculate the score (negative value) indicating.

<Factor 3>
Next, factor 3 of the extrapolation process will be described with reference to FIG. 21C. As shown in FIG. 21C, it is assumed that both the targets P1 and P2 are normally detected in the previous processing. Then, in this processing, the history UP peak fu1b and the history DOWN peak fd1b exist, while the history UP peak and the history DOWN peak of the target P2 do not exist.

Further, in factor 3, the history UP peak fu1b and the history DOWN peak fd1b of the target P1 are the prediction range E of the target P2 in one of the UP section and the DOWN section (UP section in the example of FIG. 21C). Within, it is assumed that the other section (DOWN section in the example of FIG. 21C) is outside the prediction range E. In factor 3, the history UP peak fu1b may be outside the prediction range E, and the history DOWN peak fd1b may be within the prediction range E.

The peaks in the UP section and DOWN section of this processing are in the state shown on the right in FIG. 21C due to the influence of multipath, etc., but it is in such a state when the vertically cracked object is an upper object. hard. Therefore, in the statistical model in the case of factor 3, as shown in FIG. 20, the vehicle vertical crack likelihood is "medium", the upper object vertical crack likelihood is "extremely low", and the score is "positive value".

Here, the reason why the extrapolation process of factor 3 is difficult when the vertically cracked object is an upper object, and therefore the likelihood of the upper object vertical crack is extremely low, that is, extremely low will be described. FIG. 22 is a diagram schematically showing the state of the reflected wave when the vertically cracked object is an upper object.

As shown in FIG. 22, here, the case where the upper object is the overpass 100 will be described as an example. The lower surface side of the overpass 100 has, for example, a concavo-convex shape in which a plurality of convex portions 101 are continuously formed along the traveling direction of the vehicle CR.

When a transmitted wave is transmitted from the radar device 1 to the overpass 100 having such a shape, the transmitted wave is likely to be reflected, for example, near a corner portion (groove portion) on the proximal end side of a plurality of convex portions 101. .. Therefore, the radar device 1 may receive, for example, two reflected waves RXp1 and RXp2 from one object, the overpass 100, and in such a case, the two target P1 and P2 are detected, resulting in vertical cracking. Occurs.

Here, while the target P1 continues to be detected stably, for example, the target P2 on the back side is affected by the multipath in which the reflected wave RXp2 is reflected on the ground, as shown by the alternate long and short dash line. The peak may not be extracted and extrapolation may be performed.

When extrapolation processing is performed on the target P2, the detected history UP peak fu1b and history DOWN peak fd1b of the target P1 (see the right figure of FIGS. 21A to 21C) are the prediction range E of the target P2. Whether or not it exists inside is easily determined by the structure of the overpass 100.

Specifically, if the distance G between the convex portions 101 of the overpass 100 is equal to or less than the distance corresponding to 3 bin, which is the prediction range E, the history UP peak fu1b and the history DOWN peak are shown in the right figure of FIG. 21A. Both fd1b are within the prediction range E.

On the other hand, if the separation distance G between the convex portions 101 is longer than the distance corresponding to 3 bin, both the history UP peak fu1b and the history DOWN peak fd1b exist outside the prediction range E, as shown in the right figure of FIG. 21B. It becomes. Since the overpass 100 is a relatively large structure, most of the overpass 100 is in a state as shown in the right figure of FIG. 21B.

That is, when the upper object is an overpass 100 having irregularities on the lower surface side, one of the history UP peak fu1b and the history DOWN peak fd1b is within the prediction range E and the other is within the prediction range, as shown in the right figure of FIG. 21C. It is unlikely that it will exist outside E.

Therefore, when the vertically cracked object is an upper object (here, the overpass 100), the timing of receiving the reflected wave differs between the UP section and the DOWN section because it has a continuously formed uneven shape. However, the history UP peak fu1b and the history DOWN peak fd1b are in substantially the same state, and it is difficult to perform extrapolation processing related to the state shown in factor 3, so that the likelihood of vertical cracking of the upper object of factor 3 is extremely low.

On the other hand, when the vertically cracked object is a stopped vehicle, the shape of the vehicle has a flat portion and a curved portion, so that the timing of receiving the reflected wave is the UP section and the DOWN section. Of the history UP peak fu1b and the history DOWN peak fd1b as shown in the right figure of FIG. 21C, one may be in the prediction range E and the other may be outside the prediction range E. That is, the history UP peak fu1b and the history DOWN peak fd1b may be in different states. Therefore, the vehicle vertical crack likelihood of factor 3 is set to "medium" (see FIG. 20).

Since the score is the ratio of the vehicle vertical crack likelihood to the upper object vertical crack likelihood, the score of factor 3 is a relatively large value. Specifically, the score of factor 3 is set to a value larger than the score of factor 1. The score of factor 3 is not limited to the above, and may be, for example, a value equal to or less than the score of factor 1.

From the above, in the signal processing unit 201 of the second embodiment, when the target P2 is extrapolated by factor 3, it is possible that the targets P1 and P2 are detected by vertical cracks in the stopped vehicle. Calculate the score (positive value) indicating that it is high. Conversely, the signal processing unit 201 calculates a score (positive value) indicating that it is unlikely that the targets P1 and P2 are detected by vertical cracks in the upper object.

<Factor 4>
Next, factor 4 of the extrapolation process will be described with reference to FIG. 21D. As shown in FIG. 21D, it is assumed that both the targets P1 and P2 are normally detected in the previous processing. Then, in this processing, the history UP peak fu1b and the history DOWN peak fd1b of the target P1 and the history DOWN peak fd2b of the target P2 exist, but the history UP peak of the target P2 does not exist.

Note that FIG. 21D shows a case where the history UP peak fu1b of the target P1 is within the prediction range E of the target P2, but the present invention is not limited to this, and is outside the prediction range E as shown by the alternate long and short dash line, for example. You may.

In the case where the processing is shown in the right figure of FIG. 21D, the target P2 is extrapolated in the UP section because the history UP peak does not exist in the UP section. In the example shown in FIG. 21D, the history DOWN peak fd2b of the target P2 exists, but the present invention is not limited to this. For example, the history DOWN peak fd2b does not exist and the history UP peak of the target P2 exists. You may.

That is, factor 4 is that the peaks of the targets P1 and P2 are detected in one of the two sections of the UP section and the DOWN section (DOWN section in the example of FIG. 21D), and the other section (example of FIG. 21D). Then, the extrapolation process is performed when the peak of the target P1 is detected in the UP section) and the peak of the target P2 is not detected. In the following, regarding the target P2 processed this time, the process in which the extrapolation process is performed in one of the UP section and the DOWN section may be described as "one-sided extrapolation process".

Then, as shown in FIG. 20, the statistical model in the case of the one-sided extrapolation process of factor 4 has a vehicle vertical crack likelihood of "high", an upper object vertical crack likelihood of "high", and a score of "zero". It is said that. That is, the one-sided extrapolation process can occur to the same extent whether the vertically cracked object is an upper object or a stopped vehicle, so the score is set to zero.

Therefore, in the signal processing unit 201, when one-sided extrapolation of factor 4 is performed on the target P2, whether the targets P1 and P2 are detected by vertical cracks on the upper object or vertical cracks on the stopped vehicle. Calculate a score (zero) indicating that it is not determined whether or not it was detected in.

<Factor 5>
Next, factor 5 of the extrapolation process will be described. Factor 5 is that extrapolation processing is performed for reasons other than the above factors 1 to 4. Factors 5, for example, the azimuth arithmetic processing (see step S111 in FIG. 6) that the target azimuth is not derived when the Mahalanobis distance D _M (x, which is calculated when the pairing process (see step S113) ) Is not paired because it is relatively far away, and there is no current pair that has temporal continuity with the previous pair in the continuity determination process (see step S115), but it is limited to these. It's not a thing.

Then, in the statistical model in the case of factor 5, the vehicle vertical crack likelihood is "low", the upper object vertical crack likelihood is "medium", and the score is "negative value". The score of factor 5 is set to a value larger than the score of factor 2 in absolute value, but is not limited to this, and may be, for example, a value equal to or less than the score of factor 2.

Therefore, in the signal processing unit 201 of the second embodiment, when the target P2 is extrapolated by factor 5, it is unlikely that the targets P1 and P2 are detected by vertical cracks in the stopped vehicle. Calculate the score (negative value) indicating that. Conversely, the signal processing unit 201 calculates a score (negative value) indicating that the targets P1 and P2 are likely to be detected by vertical cracks in the upper object.

When the score is calculated based on the above-mentioned parameters A to D, the signal processing unit 201 of the second embodiment calculates the cumulative score as in the first embodiment, and whether or not the "condition group B" is satisfied. (See step S147 in FIG. 14). Then, when the condition group B is satisfied (step S147: Yes), the signal processing unit 201 inherits the reliability of the target P2 to the target P1 (see step S149).

As a result, the radar device 1 can quickly determine the type of the target P1 used as the reference point of the vehicle control device 2.

Further, in the second embodiment, by using the above-mentioned parameters A to D, even if the upper object is, for example, the overpass 100 (see FIG. 22) having unevenness on the lower surface side, the target is a target. It is possible to presume that it is highly possible that P1 and P2 were detected by vertical cracks in the upper object.

The signal processing unit 201 described above functions as a determination means and a takeover means. Further, the target P1 is an example of the first target, and the target P2 is an example of the second target. The score is an example of a value indicating the possibility that the targets P1 and P2 are targets for which the information regarding the type of the target P2 is to be inherited as the information regarding the type of the target P1.

Further, in Examples 1 and 2, the score is calculated using all of a plurality of statistical models, but the score is not limited to this, and the score is calculated using some statistical models. You may try to do it.

[Other Examples]
[1] Each process in the above description on the processor 17 may be realized by causing the processor 17 to execute a program corresponding to each process. For example, a program corresponding to each process in the above description may be stored in the memory 18, and each program may be read from the memory 18 by the processor 17 and executed. Further, each program does not necessarily have to be stored in the memory 18 in advance. That is, for example, each program is recorded in advance on a portable recording medium such as a magnetic disk, an optical disk, an IC card, or a memory card that can be connected to the radar device 1, and each program is read from the recording medium by the processor 17 and executed. May be done. Further, for example, each program may be stored in a computer or server connected to the radar device 1 wirelessly or by wire via the Internet, LAN, wireless LAN, or the like, and each program may be read out to the processor 17 and executed. ..

[2] In the above embodiment, as an example, the number of transmitting antennas of the radar device 1 is one, and the number of receiving antennas is three. However, the number of transmitting antennas may be plurality, and the number of receiving antennas may be four or more.

1 Radar device 11 Oscillator 12 Transmit antenna 13a, 13b, 13c Receive antenna 14a, 14b, 14c Mixer 16a, 16b, 16c ADC
17 Processor 18 Memory 201 Signal processing unit 202 Transmission control unit 203 Signal generation unit 204 Target information output unit

Claims (8)

A radar device that derives information related to a target based on a received signal obtained by receiving a transmitted wave transmitted to the periphery of the own vehicle and reflected by an object existing in the periphery.
A determination means for determining whether or not a plurality of targets belong to the same object,
When it is determined that the plurality of targets belong to the same object, the first target among the plurality of targets exists at a position closer to the second target, and the above-mentioned target. When the second target is derived in time earlier than the first target, the transfer means for inheriting the information regarding the type of the second target as the information regarding the type of the first target. ,
Equipped with a,
The determination means
Using a plurality of statistical models relating to the parameters of the plurality of targets, it is determined whether or not to inherit the information regarding the type of the second target as the information regarding the type of the first target.
The plurality of statistical models
The vertical distance difference indicating the distance difference between the first target and the second target in the traveling direction of the own vehicle and the width direction of the own vehicle between the first target and the second target The first statistical model whose parameter is the lateral distance difference indicating the distance difference,
A second statistical model in which the received power difference of the reflected wave between the first target and the second target is used as a parameter.
as well as
When the detection process for detecting the target is repeatedly performed, the extrapolation process for predicting the virtual position of the target that is no longer detected by the detection process this time based on the past position of the target is executed. Third statistical model with time factors as parameters
Including radar equipment. The determination means
The first target score indicates the possibility that the first target and the second target are targets for which the information regarding the type of the second target is to be inherited as the information regarding the type of the first target. , Calculated based on the second and third statistical models, respectively, and when the cumulative score obtained by accumulating the calculated scores is equal to or greater than the predetermined threshold value, the information regarding the type of the second target is obtained from the first target. Decide to take over as information about the type,
The radar device according to claim 1. The first statistical model is
When the vertical distance difference and the horizontal distance difference are within the corresponding predetermined distance difference range, at least one of the vertical distance difference and the horizontal distance difference is outside the predetermined distance difference range. Set to be higher than the above score in the case,
The radar device according to claim 2. The third statistical model is
In the detection process this time, the first target is detected and the second target is not detected, and both of the two sections of the rising section in which the frequency of the transmitted wave rises and the falling section in which the frequency of the transmitted wave falls. When the first target is extrapolated due to being within the predicted range including the predicted virtual position of the second target in the section, the score is set to be a positive value. NS,
The radar device according to claim 2 or 3. The third statistical model is
In the detection process this time, the first target is detected and the second target is not detected, and both of the two sections of the rising section in which the frequency of the transmitted wave rises and the falling section in which the frequency of the transmitted wave falls. When the first target is extrapolated due to the fact that it is outside the predicted range including the predicted virtual position of the second target in the section, the score is set to be a negative value. NS,
The radar device according to any one of claims 2 to 4. The third statistical model is
In the detection process this time, the first target is detected and the second target is not detected, and one of the two sections of the rising section in which the frequency of the transmitted wave rises and the falling section in which the frequency of the transmitted wave falls. Extrapolation due to the fact that the first target is within the predicted range including the predicted virtual position of the second target in the section and the first target is outside the predicted range in the other section. In the case of processing, the score is set to be a positive value.
The radar device according to any one of claims 2 to 5. The third statistical model is
Of the two sections of the rising section where the frequency of the transmitted wave rises and the falling section where the frequency of the transmitted wave falls, the first target and the second target are detected in one section, and the first target is detected in the other section. Is detected and the extrapolation process is caused by the fact that the second target is not detected, the score is set to be zero.
The radar device according to any one of claims 2 to 6. This is an information transfer method in a radar device that derives information related to a target based on a received signal obtained by receiving a reflected wave reflected by an object existing in the vicinity of the transmitted wave transmitted to the periphery of the own vehicle. ,
Determine if multiple targets belong to the same object,
When it is determined that the plurality of targets belong to the same object, the first target among the plurality of targets exists at a position closer to the second target, and the first target is the target. the than one target second object when target is a target object derived earlier in time, the information related to the type of the second target, take over as the information related to the type of the first target,
Using a plurality of statistical models relating to the parameters of the plurality of targets, it is determined whether or not to inherit the information regarding the type of the second target as the information regarding the type of the first target.
The plurality of statistical models
The vertical distance difference indicating the distance difference between the first target and the second target in the traveling direction of the own vehicle and the width direction of the own vehicle between the first target and the second target The first statistical model whose parameter is the lateral distance difference indicating the distance difference,
A second statistical model in which the received power difference of the reflected wave between the first target and the second target is used as a parameter.
as well as
When the detection process for detecting the target is repeatedly performed, the extrapolation process for predicting the virtual position of the target that is no longer detected by the detection process this time based on the past position of the target is executed. Third statistical model with time factors as parameters
Information transfer method including.

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