JP5078669B2 - Target detection apparatus, target detection method, and target detection program - Google Patents

Description

  The present invention relates to a target detection apparatus that detects a target from a signal received using, for example, a radar sensor.

There is a target detection device that repeatedly searches for an integration path of a target signal between signal processing frames, integrates the target signal according to the integration path extracted by the search, and detects a target from the digital video signal obtained by integration.
JP 7-35838 A JP-A-5-281327 J. et al. Arnold and S.M. Shaw: “Efficient Target Tracking Using Dynamic Programming,” IEEE Trans. On Aerospace and Electronic Systems Vol. 29, no. 1 Jan. 1993.

Even if the search for the signal integration path is repeated between frames, the target signal may not be detected because the SN ratio is low. Therefore, it is conceivable to scan a plurality of times with a radar sensor, search for an integration path between signals obtained in each scan, and detect a target. However, when searching for an integration path from signals obtained in each scan, the amount of target movement between scans is large, so the number of resolution cells to be searched for the integration path increases. Therefore, the computer load and integration loss are large.
An object of the present invention is to detect a target at an early stage under a condition where the S / N ratio is low by improving the efficiency of a process for searching for an integration path between signals obtained in each scan.

The target detection device according to the present invention is, for example, a target detection device that detects a target from a signal received by a radar sensor,
A digital video signal generated from a signal obtained by each scan process of a plurality of scan processes performed by the radar sensor, and obtained from a plurality of resolution cells and stored in a storage device A video storage unit,
A block dividing unit that divides the digital video signal stored in the video storage unit by a processing device to generate a plurality of blocks each composed of a plurality of resolution cells;
For each block generated by dividing by the block dividing unit, an evaluation value calculation is performed by the processing device to calculate an evaluation value indicating the possibility that the target is included in each block based on the amplitude value of the resolution cell included in each block. And
For each digital video signal generated from the signal obtained by the above scan processing, each block of a plurality of blocks generated by dividing the digital video signal is a signal obtained by the scan processing performed immediately before. By determining by the processing device which of the plurality of previous blocks generated by dividing the previous digital video signal generated from the processing block, the corresponding block between the digital video signals is determined by the processing device. A corresponding block determination unit for determining;
An integration processing unit that is an evaluation value calculated by the evaluation value calculation unit and calculates an integration value by integrating the evaluation value of the corresponding block determined by the corresponding block determination unit by a processing device;
And a target detection unit that detects a target by detecting an integration value exceeding a predetermined threshold from the integration value calculated by the integration processing unit.

  The target detection apparatus according to the present invention detects a target by searching for an integration path of a signal obtained by each scan process of a plurality of scan processes performed by a radar sensor. In particular, the target detection apparatus according to the present invention divides a digital video signal generated from a signal obtained in each scan into blocks having a predetermined number of resolution cells, searches for integration paths between the blocks, A target is detected based on an evaluation value indicating a possibility that the block includes the target. Therefore, according to the target detection device of the present invention, when searching for an integration path between signals obtained in each scan, the target can be detected even when the SN ratio is low, and the resolution cell unit. The processing can be made more efficient than when searching with.

Embodiment 1 FIG.
In this embodiment, a target detection process of the target detection apparatus 1 that detects a target from a signal obtained by a radar sensor performing a plurality of scan processes will be described.

First, the function of the target detection device 1 will be described with reference to FIG. FIG. 1 is a functional block diagram showing functions of the target detection apparatus 1 according to this embodiment.
The target detection device 1 includes a signal processing unit 10, an integral value generation unit 20, and a target detection unit 30.

The signal processing unit 10 receives a signal obtained by the scanning process performed by the radar sensor, performs A / D conversion processing, and generates a digital video signal. The signal processing unit 10 generates one digital video signal from a signal obtained by one scan process by the radar sensor. Here, since the radar sensor performs scanning processing a plurality of times (M times), the signal processing unit 10 generates M digital video signals.
FIG. 2 is a diagram illustrating a process in which a digital video signal is generated from a signal obtained by one scan process by a radar sensor.
As shown in FIG. 2A, the radar sensor obtains a signal by irradiating a beam multiple times (N times in FIG. 2) in one scan process (kth scan process in FIG. 2). The signal processing unit 10 receives a signal obtained by N times of beam irradiation, and generates a digital video signal shown in FIG. The digital video signal is composed of a plurality of resolution cells in the range direction, the azimuth direction, and the elevation angle direction (only the range direction and the azimuth direction are shown in FIG. 2 for simplicity).

The integral value generation unit 20 searches for an integral path and generates an integral digital video signal.
The integral value generation unit 20 includes a video storage unit 201, a block division unit 202, an amplitude evaluation unit 203 (evaluation value calculation unit), an amplitude evaluation information storage unit 204 (probability density function setting unit), a block representative cell information holding unit 205, Integration path search unit 206 (corresponding block determination unit), correspondence probability storage unit 207 (transition probability setting unit), search width setting unit 208, integration path evaluation unit 209 (evaluation value update unit), integral value calculation unit 210, integration value A storage unit 211 and a state quantity update unit 212 are provided.

  The video storage unit 201 stores the digital video signal generated by the signal processing unit 10 in a storage device. That is, the video storage unit 201 stores M digital video signals as shown in FIG. 2B when the radar sensor has performed M scans. Note that the video storage unit 201 only needs to store the video signal being processed, and does not have to hold M digital video signals when the radar sensor has performed M scans.

The block dividing unit 202 divides each digital video signal stored in the video storage unit 201 by a processing device, and generates a plurality of blocks composed of a plurality of resolution cells.
FIG. 3 is a diagram illustrating a process of dividing a digital video signal into blocks.
The block dividing unit 202 converts each digital video signal (in FIG. 3A, a digital video signal generated from the signal obtained by the k-th scanning process) into a plurality of blocks as shown in FIG. To divide. Here, each block includes a plurality of resolution cells (two resolution cells in the range direction and the azimuth direction in FIG. 3).

The amplitude evaluation unit 203 receives the digital video signal divided into blocks by the block division unit 202, and based on the amplitude evaluation information stored in the amplitude evaluation information storage unit 204, indicates the likelihood that each block may include a target. The degree ratio (evaluation value) is calculated by the processing device.
The amplitude evaluation information storage unit 204 calculates a probability that the signal amplitude value of each resolution cell of the digital video signal is a target and a probability that the signal amplitude value of each resolution cell of the digital video signal is not a target (probability of false alarm). The determined amplitude evaluation information is stored in the storage device. The probability that the signal amplitude value of each resolution cell of the digital video signal is the target and the probability that the signal amplitude value of each resolution cell of the digital video signal is not the target are defined by, for example, a probability density function.
FIG. 4 is a diagram illustrating an example of a process for obtaining a likelihood ratio indicating the possibility that each block is a target.
First, as shown in FIG. 4A, the amplitude evaluation unit 203 receives the digital video signal divided into blocks by the block division unit 202 and inputs digital data based on the amplitude evaluation information stored in the amplitude evaluation information storage unit 204. For each resolution cell of the video signal, a likelihood ratio indicating the possibility that the resolution cell is the target is calculated (FIG. 4 (1)).
Next, the amplitude evaluation unit 203 sets, for example, the likelihood ratio of the resolution cell having the largest likelihood ratio among the resolution cells included in each block as the likelihood ratio of the block. Further, the amplitude evaluation unit 203 selects, for example, the resolution cell having the largest likelihood ratio among the resolution cells included in each block as the block representative cell of the block (FIG. 4 (2)). The amplitude evaluation unit 203 stores the likelihood ratio of the block in the block representative cell information holding unit 205 and stores the coordinate information of the block representative cell in the block representative cell information holding unit 205.

Based on the transition probability (correspondence probability) stored in the correspondence probability storage unit 207 (to be described later), the integration path search unit 206 uses the processing device to find the integration path between the digital video signals generated from the signals obtained in each scan process. Ask.
FIG. 5 is a diagram illustrating a process in which the integration path search unit 206 performs an integration path search.
For each digital video signal, the integration path search unit 206 is configured to block each block of the digital video signal (in FIG. 5, a digital video signal generated from the signal obtained by the k-th scanning process) (hereinafter, the target digital video signal). Corresponds to the previous block of the previous block of the previous digital video signal generated from the signal obtained by the previous scan process (k-1 scan process in FIG. 5) performed one time before Determine. Thereby, the integration path search unit 206 determines a corresponding block between the digital video signals, that is, an integration path.
First, the integration path search unit 206 selects each block of the target digital video signal as a target block in order. In FIG. 5, it is assumed that the shaded block at the center of the target digital video signal is selected as the target block.
Next, the integration path search unit 206 evaluates the possibility that each block (previous block) of the previous digital video signal with respect to the target digital video signal is a previous block (previous block that is the transition source) corresponding to the selected target block. To do. Here, the integration path search unit 206 evaluates the possibility of being the previous block (previous block of the transition source) corresponding to the selected block of interest based on the transition probability stored in the correspondence probability storage unit 207. In other words, the integration path search unit 206 evaluates the previous block having a high transition probability as the previous block of the transition source, and selects it as the transition source.
The integration path search unit 206 does not evaluate all blocks of the previous digital video signal, but only the previous block included in the search area set by the search width setting unit 208 described later corresponds to the selected block of interest. The possibility of being a previous block (previous block before transition) is evaluated.

The correspondence probability storage unit 207 is a probability that each block of the target digital video signal corresponds to each previous block of the previous digital video signal, that is, transition from each previous block of the previous digital video signal to the target block of the target digital video signal. Memorize probabilities. Here, only the transition probability from the previous block included in the search area of the previous digital video signal to the target block of the target digital video signal is stored. That is, the probability of transition to the target block of the target digital video signal is defined for each previous block included in the search area for the previous digital video signal (for each block included in the search area for the previous digital video signal in FIG. 5). . Here, the transition probability is determined based on the position information and speed information of the block representative cell fed back by a state quantity update unit 212 described later.
Further, the correspondence probability storage unit 207 stores information for calculating a track score value (new evaluation value) described later in the storage device based on the transition probability. The information for calculating the track score value is, for example, a predetermined calculation formula, which will be described in detail later.

  The search width setting unit 208 sets a predetermined previous block as a search area among the previous blocks of the previous digital video signal for the target digital video signal, and stores it in the storage device. In FIG. 5, one surrounding block (within the thick frame of the previous digital video signal) centering on the previous block at the same position as the target block of the target digital video signal is set as the search area.

  The integration path evaluation unit 209 is based on the likelihood ratio of the target block of the target digital video signal stored in the block representative cell information holding unit 205 and the transition probability of the previous block of the transition source determined by the integration path search unit 206. The track score value is calculated according to the information for calculating the track score value stored in the correspondence probability storage unit 207.

  Then, the integration value calculation unit 210 integrates the track score value calculated by the integration path evaluation unit 209 with the track score value of the previous block selected as the previous block of the transition source, and calculates the integration value of the target block. .

  The integration path search unit 206, the integration path evaluation unit 209, and the integration value calculation unit 210 select all the blocks of the target digital video signal as the target blocks and perform the above processing, thereby supporting all the blocks of the target digital video signal. The previous block is determined. As a result, the correspondence between the target digital video signal and the previous digital video signal is determined, and an integration path between the target digital video signal and the previous digital video signal is obtained. Then, an integral value for each block is calculated.

The integral value storage unit 211 stores the integral value of each block calculated by the integral value calculation unit 210 in a storage device. Further, the integrated value storage unit 211 stores the coordinates of the block representative cell adopted as the integration path in the storage device. The integrated value storage unit 211 stores the coordinates of the block representative cells that have been adopted as the integration path in all the scans until that time (until the scan processing for obtaining the signal for generating the target digital video signal) in the storage device. deep.
Further, the integral value storage unit 211 feeds back the integral value to the integral value calculation unit 210.

  The state quantity update unit 212 uses the coordinates of the representative cell of the transition source block obtained by the integration path search unit 206 and the representative cell of the block of interest to focus attention at the stage of the current scan process (kth scan process in FIG. 5). The position information and speed information of the block representative cell of the block are updated. Then, the state quantity update unit 212 feeds back the updated information to the correspondence probability storage unit 207. The correspondence probability storage unit 207 updates the transition probability based on the updated position information of the block representative cell and the speed information.

  By selecting a digital video signal generated from signals obtained by all scanning processes as a target digital video signal in time series and executing the processing of the integral value generation unit 20 described above, all scanning processes are performed. The integration path between the digital video signals generated from the signal obtained in step (1) is obtained. Then, an integral value of each block is calculated among all digital video signals generated from signals obtained by all scanning processes.

The target detection unit 30 detects a block representative cell of a block having an integration value exceeding a predetermined threshold from the integration value generated by the integration value generation unit 20 as a target.
That is, after the integration value generation unit 20 integrates the digital video signals for all scan processing, the target detection unit 30 determines whether there is a block having an integration value exceeding the threshold value, and selects a block representative cell of the block exceeding the threshold value. Consider it a goal.

Next, the function of the target detection apparatus 1 described above will be described using mathematical expressions.

  The state vector and the motion model of each resolution cell of the digital video signal in the k-th scan processing can be defined as shown in equations (1) and (2), respectively. Expressions (4) and (5) are search areas set by the search width setting unit 208 and are preset parameters.

  Further, the probability that the signal amplitude value of each resolution cell of the digital video signal stored in the amplitude evaluation information storage unit 204 is a target is defined as in Expression (6), and the signal amplitude value of each resolution cell of the digital video signal is defined as A probability that is not the target (probability of false alarm) is defined as in Expression (7). Then, the likelihood ratio of each block calculated by the amplitude evaluation unit 203 can be expressed as in Expression (8). That is, the likelihood ratio of each resolution cell is a value obtained by dividing the probability density function that is the target of the signal amplitude value of the resolution cell shown in Equation (6) by the probability density function that is a false alarm shown in Equation (7). It is a value obtained by taking the natural logarithm. Then, the maximum likelihood ratio among the likelihood ratios of the resolution cells included in the block is set as the likelihood ratio of the block.

In addition, the correspondence probability storage unit 207 defines, for example, the probability that the block of interest is the transition source for each previous block as in Expression (9).
Here, Pmax in Expression (9) is a transition probability defined for the previous block recognized as a transition source, and is the maximum transition probability in the search region. On the other hand, (1-Pmax) / Bsearch is a transition probability of a block in a search area that is not recognized as a transition source.
That is, the integration path search unit 206 selects the previous block in which Pmax is defined as the previous block of the transition source. That is, the integration path search unit 206 selects the previous block in which Pmax that is the maximum transition probability is defined as the integration path.

Also, the correspondence probability storage unit 207 stores the evaluation formula (10) as information for calculating the track score value.
The track score value s (Θk, Θk−1) on the left side of the equation (10) indicates an increase in the track score value by considering the digital video signal generated based on the signal obtained by the k-th scan processing. .
Interpreting the right side of equation (10), the track score value s (Θk, Θk−1) on the left side of equation (10) is the natural transition probability defined for each previous block in the search region of the previous digital video signal. This is the maximum value of the sum of the logarithm and the likelihood ratio of the target block of the target digital video signal. Here, since the maximum value is selected, the sum of the natural logarithm of the transition probability Pmax and the likelihood ratio of the target block of the target digital video signal is calculated as the track score value s (Θk, Θk−1).
That is, the integration path evaluation unit 209 calculates an increase in the track score value by considering the digital video signal generated based on the signal obtained in the k-th scan processing according to the equation (10).

The integral value calculation unit 210 calculates an integral value s (Θk, Θk−1,..., Θ1) according to the equation (11).
Here, the integral value s (Θk, Θk−1,..., Θ1) on the left side of Expression (11) is generated based on the signal obtained from the first scan process to the kth scan process. A total (accumulated value) of track score values calculated from the video signal is shown.
Further, s (Θk, Θk−1) in the first term on the right side is a track score value shown on the left side of Equation (10). That is, the value is calculated by the integration path evaluation unit 209.
Further, s (Θk−1, Θk−2,..., Θ1) in the second term on the right side is a track score value calculated for each block of the digital video signal generated by the k−1th scan processing. The total (accumulated value) of track score values calculated from the digital video signal generated based on the signals obtained from the first scan process to the (k-1) th scan process is shown.
That is, the integral value s (Θk, Θk−1,..., Θ1) when the digital video signal generated from the signal obtained by the k-th scan processing is set as the target digital video signal is obtained during one scan processing ( The track score value between the (k-1) th scanning process and the kth scanning process) is calculated, and the integrated value (from the first scanning process to the (k-1) th scanning process) It is calculated by adding to the cumulative value of the track score value.

The state quantity update unit 212 updates the position information and speed information of the block representative cell of each block based on the equations (12) and (13). Then, the correspondence probability storage unit 207 defines the transition probability represented by Expression (9) based on the updated position information and speed information.
Here, Expression (12) is an initial value of the state variable vector of the resolution cell (i, j).

Next, based on FIG. 6 and FIG. 7, the flow of the target detection process which is operation | movement of the target detection apparatus 1 is demonstrated. FIG. 6 is a conceptual diagram showing the flow of target detection processing. FIG. 7 is a flowchart showing the flow of target detection processing.
First, an outline will be described with reference to FIG. First, the target detection apparatus 1 generates a digital video signal from signals obtained by each scan process, divides each digital video signal into blocks, and calculates an integration path by extracting representative cells or the like. Next, based on the calculated integration path, the evaluation value of each digital video signal is integrated to generate an integration value. Then, the target is detected from the integrated value.

Next, it demonstrates in detail based on FIG.
(ST1): The signal processing unit 10 receives a signal obtained by the radar sensor through the scanning process and generates a digital video signal. The video storage unit 201 acquires and stores the digital video signal generated by the signal processing unit 10.
(ST2a): The block dividing unit 202 divides the digital video signal stored by the signal processing unit 10 in (ST1) into blocks.
(ST2b): The amplitude evaluation unit 203 calculates a likelihood ratio indicating the possibility of being a target for each resolution cell of the digital video signal, and calculates a likelihood ratio of each block (see Expression (8)). . In addition, the amplitude evaluation unit 203 selects a block representative cell of each block divided in (ST2a).
(ST2c): The block representative cell information holding unit 205 stores the likelihood ratio of each block calculated in (ST2b).
(ST2d): The integration path search unit 206 determines, from the previous block included in the search area, the previous block of the transition source based on the transition probability stored in the corresponding probability storage unit 207 for the target block selected from the blocks of the digital video signal. Is selected (see equation (9)).
(ST2e): The integration path evaluation unit 209 calculates a track score value based on the likelihood ratio stored in (ST2c) and the transition probability stored for the previous block of the transition source selected in (ST2d). (See equation (10)).
(ST2f): The integral value calculation unit 210 adds the track score value calculated in (ST2e) to the integral value (accumulated value of the track score value) obtained from the digital video signal of the past scan processing (formula (11) )reference). Then, the integral value storage unit 211 stores the calculated integral value as the integral value of the block of interest.
(ST2g): The state quantity update unit 212 updates the position information and speed information of the block representative cell of the block of interest (see equations (12) and (13)), and the transition probability stored in the correspondence probability storage unit 207 Update.
(ST2h): The integration path search unit 206 determines whether or not all blocks have been selected as the target block. When all the blocks are selected as the target block (Yes in ST2h), the process proceeds to (ST2i). On the other hand, when all the blocks are not selected as the target block (No in ST2h), the process returns to (ST2d), the next block is selected as the target block, and the processes from (ST2d) to (ST2g) are performed.
(ST2i): The integral value generation unit 20 determines whether or not processing has been performed on signals obtained by all scan processing. If it is determined that processing has been performed on signals obtained in all scanning processes (Yes in ST2i), the process proceeds to (ST3). On the other hand, if it is determined that the signals obtained in all the scan processes are not processed (No in ST2i), the process returns to (ST1), and the signals obtained in the next scan process are changed from (ST1) to (ST2h). Process.
(ST3): The target detection unit 30 detects a block having an integration value exceeding the threshold from the integration value generated in (ST2i), and regards the block representative cell of that block as a target.

According to the target detection device 1 according to this embodiment, an integral value is calculated between scan processes, and a target signal is detected based on the calculated integral value. Therefore, even under a condition where the signal processing frame has a low SN ratio. The target signal can be detected.
In addition, according to the target detection apparatus 1 according to this embodiment, it is possible to improve the processing efficiency by searching for the integration path of the target signal in units of blocks composed of a plurality of resolution cells. Can be detected.
Moreover, according to the target detection apparatus 1 according to this embodiment, the target can be accurately detected by obtaining the integral value based on the likelihood ratio.

  In this embodiment, the target detection apparatus 1 is applied to a ranging radar. However, in this embodiment, the processing method of the target detection apparatus 1 can be applied to a radar for speed measurement using a pulse Doppler frequency. The present invention can also be applied to the case where an infrared sensor, an optical sensor, an image radar, or the like is used. The same applies to the following embodiments.

  2 to 6 are shown in two dimensions. However, the number of dimensions handled by the target detection apparatus 1 may be three dimensions, and may be four dimensions when a pulse Doppler frequency difference is obtained. When other attribute information is obtained, n-dimensional may be used. The coordinate system handled by the signal detection apparatus according to the present invention may be polar coordinates or orthogonal coordinates. The same applies to the following embodiments.

  In summary, the target detection apparatus 1 according to this embodiment has a function of detecting a target signal at an early stage under a condition where the S / N ratio is low, and has means for reducing a computer load for signal detection. It is characterized by that.

Embodiment 2. FIG.
In this embodiment, a method for calculating a track score value different from that in the first embodiment will be described.
In the first embodiment, the integration path evaluation unit 209 calculates the track score value based on the equation (10) stored in the correspondence probability storage unit 207. However, in this embodiment, the integration path evaluation unit 209 changes the method of calculating the track score value depending on the number of times the scan process for obtaining the target digital video signal is performed. In other words, the integration path evaluation unit 209 changes the method of calculating the track score value according to the elapsed time from the start time of the first scan process.

First, the function of the target detection apparatus 1 according to this embodiment will be described with reference to FIG. FIG. 8 is a functional block diagram showing functions of the target detection device 1 according to this embodiment.
The target detection apparatus 1 according to this embodiment includes a scan number determination unit 213 in addition to the target detection apparatus 1 according to the first embodiment shown in FIG.
The scan number determination unit 213 determines, by the processing device, the number of scans indicating how many times the scan process that has obtained the signal for generating the target digital video signal is the scan process.
The correspondence probability storage unit 207 stores information indicating a method for calculating a track score value according to the number of scans. Then, the correspondence probability storage unit 207 changes the information indicating the track score value calculation method based on the number of scans determined by the scan number determination unit 213 and inputs the information to the integration path evaluation unit 209. Then, the integration path evaluation unit 209 calculates the track score value according to the information indicating the calculation method of the track score value input from the correspondence probability storage unit 207.
For example, the correspondence probability storage unit 207 stores information indicating how to calculate the following track score value.

Equations (14) and (15) indicate the method of calculating the track score value, respectively.
Expression (14) is a calculation method in which the likelihood ratio of the block of interest is a track score value. In other words, Expression (14) is a method of calculating the track score value based only on the amplitude value of the resolution cell included in the block of interest. In addition, the calculation method shown in the following formula (14) is called an initial calculation method.
Equation (15) is a method for calculating the track score value shown in the first embodiment. The sum of the natural logarithm of the transition probability Pmax of the previous block as the transition source and the likelihood ratio of the target block of the target digital video signal is expressed as follows. This is a calculation method for obtaining a track score value. In other words, Expression (15) is a method of calculating a track score value by adding a weight representing the movement of the target as a probability to the amplitude value of the resolution cell included in the target block. Note that the calculation method shown in the following formula (15) is referred to as a second calculation method.

Next, based on FIG. 9, the flow of the target detection process which is operation | movement of the target detection apparatus 1 which concerns on this embodiment is demonstrated. FIG. 9 is a flowchart showing the flow of target detection processing according to this embodiment.
The processing from (ST1) to (ST2e) is the same as the processing described in the first embodiment.
(ST2j): The scan count determination unit 213 determines the scan count k indicating the number of scan processes in which the scan process for obtaining the signal for generating the digital video signal acquired in (ST1) is the scan process. Then, the correspondence probability storage unit 207 determines whether the number of scans k is M or less. Here, M is a parameter that can be arbitrarily set. When the number of scans is M or less (Yes in ST2j), the process proceeds to (ST2k). On the other hand, when the number of scans is not less than M (No in ST2j), the process proceeds to (ST2l).
(ST2k): The correspondence probability storage unit 207 selects an initial calculation method and inputs it to the integration path evaluation unit 209. On the other hand, (ST2l): the correspondence probability storage unit 207 selects the second calculation method and inputs it to the integration path evaluation unit 209.
(ST2e): The integration path evaluation unit 209 calculates a track score value according to the calculation method input by the correspondence probability storage unit 207.
The processing from (STf) to (ST3) is the same as the processing described in the first embodiment.

  According to the target detection apparatus 1 according to the present embodiment, the track score value is calculated without considering the transition probability in the initial scan stage (the number of scans M or less). The possibility of calculating an incorrect track score value can be reduced, and the target can be accurately detected.

  In summary, the target detection apparatus 1 according to this embodiment is characterized in that, in the calculation process for signal detection, the method for calculating the track score value of the target cell is changed according to the elapsed time.

Embodiment 3 FIG.
In this embodiment, a method for acquiring target position information and speed information detected by the target detection unit 30 will be described. In particular, in this embodiment, even if the target detection unit 30 detects a plurality of targets, the position information and speed information of each target can be acquired.

First, the function of the target detection apparatus 1 according to this embodiment will be described with reference to FIG. FIG. 10 is a functional block diagram showing functions of the target detection device 1 according to this embodiment.
The target detection device 1 according to this embodiment includes a target information calculation unit 40 and a display unit 50 in addition to the target detection device 1 according to the first embodiment shown in FIG.

  The target information calculation unit 40 acquires the detected position information and speed information of the target. The target information calculation unit 40 includes a target history storage unit 401, simultaneous equation processing unit 402, equation variable definition unit 403, and equation model definition unit 404.

  The target history storage unit 401 stores a history of position information of each target detected by the target detection unit 30 in a storage device. The history of the target position information is the position information of the block representative cell of the block obtained by the integration path search unit 206 as the target integration path from the digital video signal generated from the signal obtained by each scan processing. Hereinafter, the history of target position information is referred to as target cell history.

  The simultaneous equation processing unit 402 acquires the target cell history stored in the target history storage unit 401, and for each target (by target number) according to the definitions of an equation variable definition unit 403 described later and an equation model definition unit 404 described later. The simultaneous equations are solved, and the obtained solution is output to the display unit 50 as a positioning result. Here, the simultaneous equation processing unit 402 can obtain the position information and speed information of each target by solving the simultaneous equations.

  The equation variable definition unit 403 defines a state variable vector and inputs it to the simultaneous equation processing unit 402. In the case of three-dimensional positioning, the equation variable definition unit 403 defines a state variable vector as shown in Expression (16) below, for example.

  The equation model definition unit 404 defines an observation model for the target and inputs it to the simultaneous equation processing unit 402. In the case of three-dimensional positioning, the equation model definition unit 404 defines an observation model as shown in Equation (17) below, for example.

Next, based on FIG. 11, the flow of the target detection process and the target information calculation process which are the operations of the target detection apparatus 1 according to this embodiment will be described. FIG. 11 is a flowchart showing the flow of target detection processing and target information calculation processing according to this embodiment.
The processing from (ST1) to (ST3) is the same as the processing described in the first embodiment.
(ST4a): The target history storage unit 401 stores the history information of the position of the block representative cell extracted as the target integration path of the target number i detected by the target detection unit 30 (range history for each target number i. Formula (17) The left side of) is called a target cell history.
(ST4b): In the case of three-dimensional positioning, the equation variable definition unit 403 defines a state variable vector of the target number i at the end of all M times (M ≧ 6) scans. The equation model definition unit 404 defines an observation model from the range history for each target.
(ST4c): The simultaneous equation processing unit 402 sets the target cell history read from the target history storage unit 401 as a constant term and the components of the state variable vector defined by the equation variable definition unit 403 as unknowns, and the equation model definition unit 404 Solve simultaneous equations for each target number according to the definition of. The simultaneous equation processing unit 402 calculates position information and speed information.
(ST4d): The target information calculation unit 40 determines whether or not the simultaneous equations are solved for all the targets and the position information and the speed information are calculated. If it is determined that the simultaneous equations have been solved for all the targets (Yes in ST4d), the process is terminated. On the other hand, when it is determined that the simultaneous equations have not been solved for all the targets (No in ST4d), the process returns to (ST4c), and the simultaneous equations are solved for the next target.
Then, a solution (position information and velocity information for each target) obtained after the processing for all the targets is completed is output to the display unit 50 as a positioning result.

  According to the target detection device 1 according to this embodiment, when a sensor that can obtain a target distance but cannot obtain angle information is used, it is possible to obtain target three-dimensional position information and velocity information. In particular, according to the target detection apparatus 1 according to this embodiment, when a plurality of targets are detected, the three-dimensional position information and speed information of each target can be obtained.

  In summary, the target detection apparatus 1 according to this embodiment is characterized in that time difference positioning is performed on multiple targets using the obtained target cell history.

Embodiment 4 FIG.
In this embodiment, a method for tracking the target detected by the target detection unit 30 will be described.

First, the function of the target detection apparatus 1 according to this embodiment will be described with reference to FIG. FIG. 12 is a functional block diagram showing functions of the target detection device 1 according to this embodiment.
The target detection apparatus 1 according to this embodiment includes a tracking processing unit 60 in addition to the target detection apparatus 1 according to the third embodiment shown in FIG.

  The tracking processing unit 60 tracks the target based on the positioning result calculated by the target information calculating unit 40. The tracking processing unit 60 includes a positioning result storage unit 601, a correlation processing unit 602, a correlation determination criterion defining unit 603, a smoothing processing unit 604, a smoothing process variable defining unit 605, and a smoothing process model defining unit 606.

  The positioning result storage unit 601 stores the target positioning result calculated by the target information calculation unit 40 in a storage device.

  The correlation processing unit 602 acquires the target positioning result stored in the positioning result storage unit 601 and determines the correlation between the targets according to the definition of the correlation determination criterion definition unit 603 described later.

  The correlation determination criterion definition unit 603 defines a correlation criterion between a plurality of targets and inputs the correlation criterion to the correlation processing unit 602. The correlation determination criterion definition unit 603 defines the correlation criterion based on, for example, the similarity of the likelihood ratio Lb (Θk) of the block representative cell shown in the second term on the right side of the equation (18) shown below. The correlation determination criterion definition unit 603 may define the correlation criterion using a generally used criterion other than the similarity of the likelihood ratio Lb (Θk) of the block representative cell.

  The smoothing processing unit 604 receives the positioning information of the target for which the correlation determination processing has been performed by the correlation processing unit 602, and calculates a smooth value in accordance with the definition of the smoothing processing variable definition unit 605 described later and the smoothing model definition unit 606 described later. To do. Further, the smoothing processing unit 604 feeds back the obtained smoothed value to the correlation processing unit 602.

  The smoothing process variable defining unit 605 defines a state variable vector and inputs it to the smoothing processing unit 604. In the case of three-dimensional positioning, the smoothing process variable definition unit 605 defines a state variable vector as shown in Expression (19) below, for example.

  The smoothing process model definition unit 606 defines an observation model for the target and inputs the observation model to the smoothing processing unit 604. In the case of three-dimensional positioning, the smoothing process model defining unit 606 defines an observation model, for example, as shown in Expression (20) below.

Next, based on FIG. 13, the flow of the target detection process, the target information calculation process, and the target tracking process, which are the operations of the target detection apparatus 1 according to this embodiment, will be described. FIG. 13 is a flowchart showing the flow of target detection processing, target information calculation processing, and target tracking processing according to this embodiment.
The processing from (ST1) to (ST4d) is the same as the processing described in the third embodiment.
(ST6a): The positioning result storage unit 601 stores the target positioning result calculated by the target information calculation unit 40 (formula (19) in the case of three-dimensional positioning).
(ST6b): The correlation determination criterion defining unit 603 defines the correlation criterion and inputs it to the correlation processing unit 602. The correlation criterion is defined in advance and may not be defined here.
(ST6c): The correlation processing unit 602 determines the correlation between the targets in accordance with the correlation criterion defined in (ST6b). Here, the correlation process part 602 determines the correlation between the targets with the same target number, when the some target is detected.
(ST6d): The smoothing process variable definition unit 605 defines a state variable vector shown in Expression (19) in the case of three-dimensional positioning. Further, the smoothing process model defining unit 606 defines the observation model shown in Expression (20). Note that the state variable vector and the observation model may be those defined in (ST4b).
(ST6e): The smoothing processing unit 604 receives the target information on which the correlation determination processing has been performed by the correlation processing unit 602, and calculates a smooth value according to the definitions of the smoothing processing variable defining unit 605 and the smoothing processing model defining unit 606. . Further, the smoothing processing unit 604 feeds back the obtained smoothed value to the correlation processing unit 602.
(ST6f): The tracking processing unit 60 determines whether correlation processing and smoothing processing have been performed for all targets. If it is determined that correlation processing and smoothing processing have been performed for all targets (Yes in ST6f), the processing ends. On the other hand, if it is determined that correlation processing and smoothing processing have not been performed for all targets (No in ST6f), the process returns to (ST6c), and correlation processing and smoothing processing is performed for the next target.
Then, after the processing for all targets is completed, the smooth value of all targets is output to the display unit 50.

  According to the fourth embodiment, when there is no expectation of improvement in the S / N ratio, such as when performing a track will scan, the multi-target time difference positioning result of the third embodiment is used while continuing the target detection process according to the first embodiment. In this way, tracking processing becomes possible.

  In summary, the target detection apparatus 1 according to this embodiment performs multi-target tracking using the detection result obtained by the target detection unit 30 and the positioning result obtained by the target information calculation unit 40. It is characterized by that.

Embodiment 5 FIG.
In this embodiment, a process for optimizing the size of a block generated by the block dividing unit 202 will be described. Here, the block size is the number of resolution cells included in the block.

First, the function of the target detection apparatus 1 according to this embodiment will be described with reference to FIG. FIG. 14 is a functional block diagram showing functions of the target detection device 1 according to this embodiment.
The target detection device 1 according to this embodiment includes a scan number determination unit 213 and a block size setting unit 214 in addition to the target detection device 1 according to the first embodiment shown in FIG.

  As described in the second embodiment, the scan number determination unit 213 determines the number of scans indicating the number of times the scan process for obtaining the signal for generating the target digital video signal is the scan process.

  The block size setting unit 214 sets the optimum size of the block generated by the block dividing unit 202 by the processing device according to the number of scans determined by the scan number determining unit 213, and sends the set size to the block dividing unit 202. input. The block size setting unit 214 includes a range size setting unit 215, an azimuth size setting unit 216, and an elevation angle size setting unit 217.

  The range size setting unit 215 sets the number of resolution cells in the range direction included in the block according to the number of scans determined by the scan number determination unit 213. For example, the range size setting unit 215 sets an initial range size set in advance when the number of scans k is equal to or less than a predetermined threshold M, and calculates by the following formula (21) when the number of scans k is greater than M. Set the size to be used. Here, M is a parameter that can be arbitrarily set.

The azimuth size setting unit 216 sets the number of resolution cells in the azimuth direction included in the block. The azimuth size setting unit 216 sets an initial azimuth size set in advance regardless of the number of scans.
For example, as shown in FIG. 15, the azimuth size setting unit 216 sets a sector with a plurality of resolution cells in the azimuth direction as a unit, and sets the sector as a unit.
Similar to the range size setting unit 215, the azimuth size setting unit 216 dynamically changes and sets the size in consideration of the target movement amount in the azimuth direction when the predetermined number of scans is exceeded. It doesn't matter.

The elevation size setting unit 217 sets the number of resolution cells in the elevation direction included in the block. The elevation angle size setting unit 217 sets a preset initial elevation angle size regardless of the number of scans.
For example, as shown in FIG. 15, the elevation angle size setting unit 217 sets a sector with a plurality of resolution cells in the elevation angle direction as a unit, and sets the sector as a unit, as in the azimuth size setting unit 216.
As with the range size setting unit 215, the elevation angle size setting unit 217 is configured to dynamically change the size in consideration of the amount of movement in the target elevation angle direction when the predetermined number of scans is exceeded. It doesn't matter.

  The reason why the size in the range direction is dynamically changed in accordance with the target movement amount is that the target movement amount in the range direction is generally large. Therefore, when the target movement amount in the azimuth direction or the elevation angle direction is large, as described above, the azimuth size setting unit 216 or the elevation angle size setting unit 217 considers the movement amount in the target azimuth direction or elevation angle direction. Then you can change the size dynamically.

Next, based on FIG. 16, the flow of the target detection process which is operation | movement of the target detection apparatus 1 which concerns on this embodiment is demonstrated. FIG. 16 is a flowchart showing the flow of target detection processing according to this embodiment.
In the flowchart shown in FIG. 16, the size in the range direction is dynamically changed according to the target movement amount, and the sizes in the azimuth direction and the elevation direction are set to preset sizes. .
(ST1) is the same as the process described in the first embodiment.
(ST2m): The azimuth size setting unit 216 sets the initial azimuth size set in advance as the block size in the azimuth direction. Further, the elevation angle size setting unit 217 sets the initial elevation angle size set in advance to the block size in the elevation angle direction.
(ST2n): The scan number determination unit 213 determines the number of scans k indicating the number of times the scan process that has obtained the signal for generating the digital video signal acquired in (ST1) is the scan process. Then, the correspondence probability storage unit 207 determines whether the number of scans k is M or less. If the number of scans is M or less (Yes in ST2n), the process proceeds to (ST2o). On the other hand, when the number of scans is not less than M (No in ST2n), the process proceeds to (ST2p).
(ST2o): The range size setting unit 215 sets the initial range size set in advance as the size of the block in the range direction. On the other hand, (ST2p): range size setting section 215 sets the size calculated by equation (21) as the size of the block in the range direction.
(ST2a): The block dividing unit 202 divides the digital video signal stored by the signal processing unit 10 in (ST1) into blocks having a size set in (ST2m) and (ST2o) or (ST2p).
The processing from (ST2b) to (ST3) is the same as the processing described in the first embodiment.

  According to the target detection apparatus 1 according to this embodiment, the number of resolution cells in a block is optimized. Thereby, the integral path search region can be optimized according to the target movement amount, and the efficiency of the integral path search in the integral value generation unit 20 is improved.

  In summary, the target detection apparatus 1 according to this embodiment is characterized by having optimization means for the range direction block size, the azimuth direction block size, and the elevation angle direction block size that reduce the computer load for signal detection.

Embodiment 6 FIG.
In this embodiment, a block likelihood ratio calculation method and a block representative cell selection method by the amplitude evaluation unit 203 of the target detection apparatus 1 will be described.
Here, a method for calculating the likelihood ratio of three blocks and a method for selecting two block representative cells will be described.

First, a method for calculating the likelihood ratio of a block will be described.
The method for calculating the likelihood ratio of the first block is the same as the method described in the first embodiment. That is, the maximum likelihood ratio among the likelihood ratios of the resolution cells included in the block is used as the likelihood ratio of the block.
That is, according to this method, the method of calculating the likelihood ratio Lb (Θk) can be expressed as in Expression (22).

The likelihood ratio calculation method for the second block is a method in which the likelihood ratio calculated for the resolution cell having the maximum amplitude value among the resolution cells included in the block is used as the likelihood ratio of the block.
That is, according to this method, the method of calculating the likelihood ratio Lb (Θk) can be expressed as in Expression (23).

The method for calculating the likelihood ratio of the third block is a method in which the likelihood ratio calculated from the average value of the amplitude values of the resolution cells included in the block is used as the likelihood ratio of the block.
That is, the amplitude evaluation unit 203 first calculates the average value of the amplitude values of the resolution cells included in the block as shown in Expression (24). Next, the amplitude evaluation unit 203 calculates a likelihood ratio based on the average value of the calculated amplitude values. Then, the amplitude evaluation unit 203 uses the likelihood ratio calculated from the average value of the amplitude values as the likelihood ratio of the block.

Next, a method for selecting a block representative cell will be described.
The method for selecting the first block representative cell is the same as the method described in the first embodiment. That is, the resolution cell having the maximum likelihood ratio among the resolution cells included in the block is used as a block representative cell.
That is, the amplitude evaluation unit 203 first calculates the likelihood ratio of all resolution cells included in the block. Next, the amplitude evaluation unit 203 selects a resolution cell having the maximum likelihood ratio among the resolution cells included in the block and sets it as a block representative cell.

  The second block representative cell selection method is a method in which the resolution cell having the maximum amplitude value among the resolution cells included in the block is used as the block representative cell.

  Note that any block likelihood ratio calculation method and block representative cell selection method may be combined, and any block likelihood ratio calculation method and block representative cell selection method may be used. However, the amplitude evaluation unit 203 stores the calculated block likelihood ratio and the block representative cell in the block representative cell information holding unit 205.

  According to the target detection apparatus 1 according to this embodiment, a target can be accurately detected by adopting a block likelihood ratio calculation method and a block representative cell selection method according to the situation.

In summary, the target detection apparatus 1 according to this embodiment uses a resolution cell having the maximum likelihood ratio among resolution cells constituting a cell block as a representative point of the block, or uses a cell block as a representative block. A resolution cell having the maximum amplitude among the constituent resolution cells is used as a representative point of the cell block.
Further, the target detection apparatus 1 according to this embodiment uses the likelihood ratio of the resolution cell having the maximum amplitude among the resolution cells constituting the cell block as the representative likelihood ratio of the block, or the cell block The likelihood ratio of the average amplitude of the resolution cell to be configured is set as the representative likelihood ratio of the block.

Next, the hardware configuration of the target detection apparatus 1 in the above embodiment will be described.
FIG. 17 is a diagram illustrating an example of a hardware configuration of the target detection device 1.
As shown in FIG. 17, the target detection apparatus 1 includes a CPU 911 (also referred to as a central processing unit, a central processing unit, a processing unit, an arithmetic unit, a microprocessor, a microcomputer, and a processor) that executes a program. The CPU 911 is connected to the ROM 913, the RAM 914, the LCD 901 (Liquid Crystal Display), the keyboard 902, the communication board 915, and the magnetic disk device 920 via the bus 912, and controls these hardware devices. Instead of the magnetic disk device 920, a storage device such as an optical disk device or a memory card read / write device may be used.

  The ROM 913 and the magnetic disk device 920 are examples of a nonvolatile memory. The RAM 914 is an example of a volatile memory. The ROM 913 and the RAM 914 are examples of storage devices. The communication board 915 and the keyboard 902 are examples of input devices. The communication board 915 is an example of an output device. Furthermore, the communication board 915 is an example of a communication device. Furthermore, the LCD 901 is an example of a display device.

  An operating system 921 (OS), a window system 922, a program group 923, and a file group 924 are stored in the magnetic disk device 920 or the ROM 913. The programs in the program group 923 are executed by the CPU 911, the operating system 921, and the window system 922.

The program group 923 includes “signal processing unit 10”, “integral value generation unit 20”, “target detection unit 30”, “target information calculation unit 40”, “display unit 50”, “tracking processing unit” in the above description. A program for executing the function described as “60” or the like and other programs are stored. The program is read and executed by the CPU 911.
The file group 924 includes “digital video signal”, “position information”, “likelihood ratio”, “transition probability”, “calculation method”, “probability density function”, “track score value”, etc. in the above description. The described information, data, signal values, variable values, and parameters are stored as items of “file” and “database”. The “file” and “database” are stored in a recording medium such as a disk or a memory. Information, data, signal values, variable values, and parameters stored in a storage medium such as a disk or memory are read out to the main memory or cache memory by the CPU 911 via a read / write circuit, and extracted, searched, referenced, compared, and calculated. Used for the operation of the CPU 911 such as calculation / processing / output / printing / display. Information, data, signal values, variable values, and parameters are temporarily stored in the main memory, cache memory, and buffer memory during the operation of the CPU 911 for extraction, search, reference, comparison, calculation, calculation, processing, output, printing, and display. Is remembered.
In addition, the arrows in the flowcharts in the above description mainly indicate input / output of data and signals, and the data and signal values are recorded in a memory of the RAM 914 and other recording media such as an optical disk. Data and signals are transmitted online via a bus 912, signal lines, cables, or other transmission media.

  In addition, what is described as “to part” in the above description may be “to circuit”, “to device”, “to device”, “to means”, and “to function”. It may be “step”, “˜procedure”, “˜processing”. In addition, what is described as “˜device” may be “˜circuit”, “˜device”, “˜device”, “˜means”, “˜function”, and “˜step”, “ ~ Procedure "," ~ process ". Furthermore, what is described as “to process” may be “to step”. That is, what is described as “˜unit” may be realized by firmware stored in the ROM 913. Alternatively, it may be implemented only by software, or only by hardware such as elements, devices, substrates, and wirings, by a combination of software and hardware, or by a combination of firmware. Firmware and software are stored in a recording medium such as ROM 913 as a program. The program is read by the CPU 911 and executed by the CPU 911. That is, the program causes a computer or the like to function as the “˜unit” described above. Alternatively, the computer or the like is caused to execute the procedures and methods of “to part” described above.

FIG. 3 is a functional block diagram illustrating functions of the target detection device 1 according to the first embodiment. The figure which shows the process in which a digital video signal is produced | generated from the signal obtained by one scan process by a radar sensor. The figure which shows the process in which a digital video signal is divided | segmented into a block. The figure which shows an example of the process of calculating | requiring the likelihood ratio which shows the possibility that each block is a target. The figure which shows the process in which the integration path search part 206 performs an integration path search. The conceptual diagram which shows the flow of a target detection process. The flowchart which shows the flow of a target detection process. FIG. 4 is a functional block diagram illustrating functions of a target detection device 1 according to a second embodiment. 10 is a flowchart showing a flow of target detection processing according to the second embodiment. FIG. 9 is a functional block diagram illustrating functions of a target detection device 1 according to a third embodiment. 10 is a flowchart showing a flow of target detection processing and target information calculation processing according to the third embodiment. FIG. 6 is a functional block diagram showing functions of a target detection device 1 according to a fourth embodiment. 10 is a flowchart showing a flow of target detection processing, target information calculation processing, and target tracking processing according to the fourth embodiment. FIG. 6 is a functional block diagram showing functions of a target detection device 1 according to a fifth embodiment. The conceptual diagram of the block size of an azimuth direction and an elevation angle direction. 10 is a flowchart showing a flow of target detection processing according to the fifth embodiment. FIG. 2 is a diagram illustrating an example of a hardware configuration of the target detection device 1.

Explanation of symbols

  DESCRIPTION OF SYMBOLS 1 Target detection apparatus, 10 Signal processing part, 20 Integral value production | generation part, 201 Video storage part, 202 Block division part, 203 Amplitude evaluation part, 204 Amplitude evaluation information storage part, 205 Block representative cell information holding part, 206 Integration path search Unit, 207 correspondence probability storage unit, 208 search width setting unit, 209 integral path evaluation unit, 210 integral value calculation unit, 211 integral value storage unit, 212 state quantity update unit, 213 scan number determination unit, 214 block size setting unit, 215 range size setting unit, 216 azimuth size setting unit, 217 elevation angle setting unit, 30 target detection unit, 40 target information calculation unit, 401 target history storage unit, 402 simultaneous equation processing unit, 403 equation variable definition unit, 404 equation model Definition section, 50 display section, 60 tracking processing section, 601 positioning result storage section, 6 02 correlation processing unit, 603 correlation determination criterion defining unit, 604 smoothing processing unit, 605 smoothing process variable defining unit, 606 smoothing process model defining unit.

Claims (13)

A target detection device that detects a target from a signal received by a radar sensor,
A digital video signal generated from a signal obtained by each scan process of a plurality of scan processes performed by the radar sensor, and obtained from a plurality of resolution cells and stored in a storage device A video storage unit,
A block dividing unit that divides the digital video signal stored in the video storage unit by a processing device to generate a plurality of blocks each composed of a plurality of resolution cells;
For each block generated by dividing by the block dividing unit, an evaluation value calculation is performed by the processing device to calculate an evaluation value indicating the possibility that the target is included in each block based on the amplitude value of the resolution cell included in each block. And
For each digital video signal generated from the signal obtained by the above scan processing, each block of the plurality of blocks generated by dividing the image signal is obtained from the signal obtained by the scan processing performed immediately before. The processing device determines the corresponding block between the digital video signals by determining which of the plurality of previous blocks generated by dividing the generated previous digital video signal corresponds to the processing device. A corresponding block determination unit,
An integration processing unit that is an evaluation value calculated by the evaluation value calculation unit and calculates an integration value by integrating the evaluation value of the corresponding block determined by the corresponding block determination unit by a processing device;
A target detection device comprising: a target detection unit for detecting a target by detecting an integration value exceeding a predetermined threshold value from the integration value calculated by the integration processing unit. The target detection device further includes:
An amplitude evaluation information storage unit that stores in a storage device amplitude evaluation information that defines a probability that the amplitude value of each resolution cell of the digital video signal is a target and a probability that the amplitude value is not a target;
The evaluation value calculation unit may include a target in each block based on a probability that is a target indicated by the amplitude evaluation information stored in the amplitude evaluation information storage unit for each resolution cell included in the block and a probability that is not a target. The target detection apparatus according to claim 1, wherein a likelihood ratio indicating is calculated, and the evaluation value is calculated from the likelihood ratio. The target detection device further includes:
Each block includes a corresponding probability storage unit that stores a corresponding probability corresponding to each previous block of the plurality of previous blocks in a storage device;
The target detection apparatus according to claim 2, wherein the corresponding block determination unit determines which previous block corresponds to each block based on the correspondence probability stored in the correspondence probability storage unit. . The target detection device further includes:
For each block, the sum of the corresponding probability stored by the corresponding probability storage unit with respect to the previous block determined to be supported by the corresponding block determination unit and the evaluation value calculated for each block is described above. An evaluation value update unit for calculating as a new evaluation value of the block is provided,
The target detection apparatus according to claim 3, wherein the integration processing unit integrates a new evaluation value calculated by the evaluation value update unit to calculate an integration value of each block. The target detection device further includes:
A scan number determination unit for determining, by a processing device, the number of scans indicating how many times the scan process of the plurality of scan processes is the scan process for obtaining the signal for generating the digital video signal;
The evaluation value update unit
When the number of scans determined by the scan number determination unit is a predetermined number or less, the evaluation value calculated by the evaluation value calculation unit is set as a new evaluation value,
When the number of scans is greater than a predetermined number, for each block, the correspondence probability stored by the correspondence probability storage unit with respect to the previous block determined by the corresponding block determination unit to correspond, and for each block The target detection apparatus according to claim 4, wherein a sum of the calculated evaluation values is calculated as a new evaluation value for each block. The target detection device further includes:
A target information calculation unit for calculating target position information and speed information by a processing device based on position information of a block of each digital video signal that is a source of calculation of an integral value exceeding a threshold detected by the target detection unit; The target detection apparatus according to claim 1, wherein The target detection device further includes:
The target detection device according to claim 6, further comprising a tracking processing unit that performs tracking of the target by the processing device based on the position information and speed information of the target resolution cell calculated by the target information calculation unit. The target detection device further includes:
The number of resolution cells included in the block to be divided by the block dividing unit is determined in accordance with the predetermined direction of the block during each scanning process until the scanning process for obtaining the signal for generating the digital video signal. The target detection apparatus according to claim 1, further comprising a cell block size setting unit that is set by a processing device according to a movement amount. The evaluation value calculation unit selects a resolution cell having the highest likelihood ratio among the resolution cells included in each block as a representative cell, and calculates the likelihood ratio of the selected representative cell as the likelihood ratio of the block. The target detection apparatus according to claim 1, wherein the target detection apparatus includes: 9. The target according to claim 1, wherein the evaluation value calculation unit calculates an average value of likelihood ratios of resolution cells included in each block as a likelihood ratio of the block. Detection device. The target detection device further includes:
A search width setting unit configured to set a predetermined previous block as a search region among the plurality of previous blocks and store the search block in a storage device;
The corresponding block determination unit determines which of the plurality of previous blocks corresponds to which of the previous blocks set by the search width setting unit as a search area among the plurality of previous blocks. The target detection apparatus according to claim 1. A target detection method for detecting a target from a signal received by a radar sensor,
A storage device acquires a digital video signal composed of a plurality of resolution cells, which is a digital video signal generated from a signal obtained by each scan process of a plurality of scan processes performed by the radar sensor. A video storage step for storing;
A block dividing step in which the processing device divides the digital video signal stored in the video storing step to generate a plurality of blocks composed of a plurality of resolution cells;
An evaluation value for calculating an evaluation value indicating the possibility that each block includes a target, based on the amplitude value of the resolution cell included in each block, for each block generated by the processing unit in the block dividing step. A calculation step;
With respect to each digital video signal generated from the signal obtained by each of the scan processes described above, each block of a plurality of blocks generated by dividing the digital video signal is a scan process performed one time before. By determining which of the plurality of previous blocks generated by dividing the previous digital video signal generated from the obtained signal corresponds to the corresponding block between the digital video signals, Corresponding block determination step;
An integration processing step in which the processing device calculates the integral value by integrating the evaluation value of the corresponding block determined in the corresponding block determination step, which is the evaluation value calculated in the evaluation value calculation step;
A target detection method comprising: a processing device comprising: a target detection step of detecting a target by detecting an integration value exceeding a predetermined threshold from the integration value calculated in the integration processing step. A target detection program for detecting a target from a signal received by a radar sensor,
A digital video signal generated from a signal obtained by each scan process of a plurality of scan processes performed by the radar sensor, and obtained from a plurality of resolution cells and stored in a storage device Video storage processing to
A block division process for dividing the digital video signal stored in the video storage process by a processing device to generate a plurality of blocks each composed of a plurality of resolution cells;
For each block generated by the above-described block division processing, evaluation value calculation is performed by the processing device to calculate an evaluation value indicating the possibility that the target is included in each block based on the amplitude value of the resolution cell included in each block. Processing,
For each digital video signal generated from the signal obtained by the above scan processing, each block of a plurality of blocks generated by dividing the digital video signal is a signal obtained by the scan processing performed immediately before. By determining by the processing device which of the plurality of previous blocks generated by dividing the previous digital video signal generated from the processing block, the corresponding block between the digital video signals is determined by the processing device. A corresponding block determination process for determining;
An integration processing for calculating an integrated value by integrating the evaluation value of the corresponding block determined in the corresponding block determination processing by the processing device with the evaluation value calculated in the evaluation value calculation processing;
A target detection program for causing a computer to execute target detection processing for detecting a target by detecting, with a processing device, an integration value exceeding a predetermined threshold from the integration value calculated in the integration processing.

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