JP7645368B2 - Method for compensating for phase impairments in a light detection and ranging (LIDAR) system - Google Patents

Description

This application claims priority under 35 U.S.C. §119(e) to U.S. Provisional Patent Application No. 63/089,886, filed October 9, 2020, and U.S. Patent Application No. 17/335,530, filed June 1, 2021, the entire contents of which are incorporated herein by reference.

This disclosure relates to light detection and ranging (LIDAR) systems.

Conventional frequency modulated continuous wave (FMCW) LIDAR systems contain phase impairments such as laser phase noise, circuit phase noise, flicker noise from the laser driving electronics, temperature/weather drift, chirp rate offset, etc. These impairments cause reduced detection probability, increased false alarms and range/velocity bias, and also increased error in estimated target range/velocity.

This disclosure describes various embodiments of LIDAR systems and methods that, among other things, mitigate phase disturbances that may be experienced by a LIDAR system. Embodiments of the invention include the ability to introduce Doppler-corrected phase disturbance corrections.

In accordance with one aspect, the present disclosure relates to a method for compensating for phase impairments in a Light Detection and Ranging (LIDAR) system.
The method includes the steps of transmitting a first optical beam toward a target, receiving a second optical beam from the target based on the first optical beam to generate a return signal, and generating a digitally sampled target signal using a local oscillator (LO) beam, a first optical detector, and the return signal.
The method also includes compensating ego velocity and target velocity of the digitally sampled target signal based on an estimated ego velocity and an estimated target velocity to generate a compensated digitally sampled target signal.
The method also includes performing a phase impairment correction on the compensated digitally sampled target signal for transmission to a point cloud. In one embodiment, the method also includes determining the ego velocity of the LIDAR system, where the ego velocity is a calculated velocity of the LIDAR system based on nearby objects measured using one or more motion sensors.
In one embodiment, compensating for the ego velocity and target velocity of the digitally sampled target signal includes applying a first frequency shift to the digitally sampled target signal that is a function of the ego velocity of the system, and applying a second frequency shift to the digitally sampled target signal that is a conjugate of the first frequency shift.
In one embodiment, the method also includes generating a digitally sampled reference signal using a reference beam transmitted through a fiber delay device and a second photodetector, and wherein performing phase impairment correction on the digitally sampled target signal includes correcting phase impairments introduced into the digitally sampled target signal by the local oscillator (LO) beam and the return signal.
In one embodiment, the method also includes determining a velocity of adjacent detection points around the target and generating the estimated target velocity based on the velocities of the adjacent detection points. In one embodiment, determining the velocity of the adjacent detection points includes running a standard corrector on all of the adjacent detection points and estimating statistics of the velocities of the adjacent detection points. In one embodiment, the method also includes determining a velocity of a previous detection point of the target in the point cloud and generating the estimated target velocity based on the velocities of the previous detection points. In one embodiment, determining the velocity of a previous point of the target in the point cloud includes determining the velocity of a previous detection point on the same scan line, determining the velocity of a detection point from a previous scan line, or determining the velocity of a detection point from a previous scan frame.

According to another aspect, the present disclosure relates to a LIDAR system including an optical beam source that transmits a first optical beam to a target; a first optical detector that receives a return signal and an LO beam from the target and generates a digitally sampled target signal; a fiber delay device having a known length and coupled to the optical beam source; a second optical detector that is coupled to the fiber delay device and generates a digitally sampled reference signal using a reference beam transmitted through the fiber delay device; at least two frequency shifters for compensating ego velocity and target velocity in the digitally sampled target signal based on an estimated ego velocity and an estimated target velocity; and a deskew filter that provides phase impairment correction to the digitally sampled target signal.
In one embodiment, the ego velocity is the velocity of the LIDAR system relative to a nearby object measured using one or more motion sensors. In one embodiment, the at least two frequency shifters include a first frequency shifter that applies a first frequency shift to the digitally sampled target signal that is a function of the ego velocity of the system, and a second frequency shifter that applies a second frequency shift to the digitally sampled target signal that is a conjugate of the first frequency shift. In one embodiment, the phase impairment correction to the digitally sampled target signal corrects for phase impairments introduced into the digitally sampled target signal by the local oscillator (LO) beam and the return signal. In one embodiment, the LIDAR system is also configured to determine the estimated target velocity based on the velocities of nearby detection points around the target. In one embodiment, the LIDAR system determines the velocities of the nearby detection points by performing a standard correction on all of the nearby detection points and estimates the statistics of the velocities of the nearby detection points. In one embodiment, the LIDAR system is also configured to determine the estimated target velocity based on a velocity of a previous detection point of the target in a point cloud, hi one embodiment, the LIDAR system determines the velocity of the previous detection point by determining the velocity of a immediately preceding detection point on the same scan line, determining the velocity of a detection point on a previous scan line, or determining the velocity of a detection point on a previous scan frame.

In another aspect, the present disclosure relates to a method for compensating for phase disturbances in a LIDAR system.
The method includes transmitting a first light beam from the LIDAR system to a target; receiving a return signal from the target at a first photodetector in the LIDAR system; generating a digitally sampled reference signal using a reference beam transmitted through a fiber delay and a second photodetector; estimating one or more phase impairments of the LIDAR system using the digitally sampled reference signal to generate one or more estimated phase impairments; applying a first frequency shift to the digitally sampled target signal, the first frequency shift being a function of an ego velocity of the LIDAR system and an estimated target velocity; adjusting for phase impairments of the digitally sampled target signal for transmission to a point cloud using a deskew filter; and applying a second frequency shift to the digitally sampled target signal, the second frequency shift being a conjugate of the first frequency shift.
In one embodiment, adjusting for phase impairments in a digitally sampled target signal includes correcting for phase impairments introduced into the digitally sampled target signal by a local oscillator (LO) beam and the return signal. In one embodiment, the method also includes determining a velocity of nearby detection points in a periphery of the target and generating the estimated target velocity based on the velocities of the nearby detection points. In one embodiment, the method also includes determining a velocity of a previous detection point of the target in a point cloud and generating the estimated target velocity based on the velocities of the previous detection points.

In order to clarify various aspects of the present invention, the following drawings are referenced in the detailed description (embodiments). The same reference numerals in the drawings refer to the same elements.

1 illustrates an exemplary LIDAR system according to an embodiment of the present disclosure.

FIG. 1 is a time-frequency diagram illustrating how LIDAR waveforms are detected and processed according to an embodiment of the present disclosure.

1 illustrates a phase disturbance that can be mitigated by an embodiment of the present disclosure.

1 illustrates a dynamic scenario in which a disturbance may be corrected according to an embodiment of the present disclosure.

FIG. 1 is a block diagram of an exemplary LIDAR system having a reference arm in accordance with an embodiment of the present disclosure.

1 illustrates an ego-Doppler compensation phase impairment corrector according to an embodiment of the present disclosure.

FIG. 1 illustrates a proximity velocity based corrector according to an embodiment of the present disclosure.

FIG. 1 illustrates a front-point based corrector according to an embodiment of the present disclosure.

1 illustrates an iterative phase impairment corrector according to an embodiment of the present disclosure.

FIG. 2 illustrates a multi-Doppler compensation corrector according to an embodiment of the present disclosure.

1 is a flow diagram illustrating an example of a method for compensating for phase impairments in a LIDAR system according to an embodiment of the present disclosure.

1 is a flow diagram illustrating another example method for compensating for phase impairments in a LIDAR system according to an embodiment of the present disclosure.

This disclosure describes various examples of LIDAR systems and methods for compensating for phase obstructions in dynamic scenes detected by the LIDAR systems.
According to some embodiments, the LIDAR systems described above can be implemented in any sensing market, such as, but not limited to, transportation, manufacturing, metrology, medical, virtual reality, augmented reality, and security systems.
According to some embodiments, the LIDAR system described above is implemented as part of a front end of an automated driving assistance system or a frequency modulated continuous wave (FMCW) device that aids in the spatial awareness of an automated vehicle. According to some embodiments, the LIDAR system described above is implemented as part of a front end of an automated driving assistance system or a frequency modulated continuous wave (FMCW) device that aids in the spatial awareness of an automated vehicle.

FIG. 1 illustrates a LIDAR system 100 in accordance with an exemplary embodiment of the present disclosure.
LIDAR system 100 may include any one or more of a number of components, but may include fewer or additional components than those shown in FIG. 1.
According to some embodiments, one or more of the components illustrated in Figure 1 may be implemented on a photonics chip. According to some embodiments, LIDAR system 100 includes one or more components that may be implemented on a photonics chip.
Optical circuit 101 includes a combination of active and passive optical components. The active optical components generate, amplify, and/or detect optical signals, etc. In some examples, the active optical components have optical beams of different wavelengths and include one or more optical amplifiers, one or more optical detectors, etc.

The free space optics 115 includes one or more optical waveguides for transmitting optical signals and for routing and manipulating the optical signals to the appropriate input/output ports of the active optical circuitry. The free space optics 115 includes one or more optical components such as taps, wavelength division multiplexers (WDMs), splitters/combiners, polarizing beam splitters (PBSs), collimators, couplers, etc.
In one aspect, the free space optics 115 includes components for converting the polarization state and directing the received polarized light to a photodetector, for example, using a PBS, and may further include a diffractive element that deflects light beams having different frequencies at different angles along an axis (e.g., the fast axis).

The LIDAR system 100 of this embodiment includes an optical scanner 102 having one or more scanning mirrors that are rotatable along an axis that is orthogonal or substantially orthogonal to the fast axis (e.g., a slow axis) of the diffractive element to direct an optical signal that scans the environment according to a scanning pattern.
For example, the scanning mirror may be rotated by one or more galvanometers.Objects in the target environment may scatter the incident light into a return light beam or target return signal.
The optical scanner 102 also collects a return light beam or a target return signal, which may be returned to the optical circuit components of the optical circuit 101. For example, the return light beam may be directed by a polarizing beam splitter to a photodetector.
In addition to mirrors and galvanometers, the optical scanner 102 may include quarter-wave plates, lenses, anti-reflective coated optical windows, and the like.

The LIDAR system 100 is provided with a LIDAR controller 110 to control and support the optical circuit 101 and the optical scanner 102. The LIDAR controller 110 contains the processing equipment required for the LIDAR system 100.
In one aspect, the processing device is one or more general-purpose processing devices, such as a microprocessor, a central processing unit, or more specifically, a complex instruction set computing (CISC) microprocessor, a reduced instruction set computing (RISC) microprocessor, a very long instruction word (VLIW) microprocessor, or a processor implementing other instruction sets or a combination of instruction sets. The processing device may also be one or more special purpose processing devices, such as an application specific integrated circuit (ASIC), a field programmable gate array (FPGA), a digital signal processor (DSP), a network processor, or the like.

In one aspect, the LIDAR control device 110 is provided with a signal processing unit 112, such as a DSP, which outputs a digital control signal for controlling the optical driver 103. The digital control signal is converted to an analog signal via the signal conversion unit 106. For example, the signal conversion unit 106 includes a digital-to-analog converter.
The optical driver 103 provides drive signals to the active optical components of the optical circuit 101 to drive light sources such as lasers and amplifiers. In one aspect, multiple optical drivers 103 and signal conversion units 106 may be provided to drive multiple light sources.

The LIDAR controller 110 is also configured to output digital control signals to the optical scanner 102. The motion controller 105 can control the galvanometers of the optical scanner 102 based on the control signals received from the LIDAR controller 110. In particular, a digital-to-analog converter can be used to convert the coordinate routing information from the LIDAR controller 110 into signals that can be processed by the galvanometers of the optical scanner 102.
In one aspect, the motion controller 105 may also transmit information regarding the position or movement of components of the optical scanner 102 back to the LIDAR controller 110. In particular, an analog-to-digital converter may be used to convert the information regarding the galvanometer position into a signal that the LIDAR controller 110 can process.

The LIDAR controller 110 is further configured to analyze the input digital signal. In this regard, the LIDAR system 100 is provided with an optical receiver 104 for measuring one or more beams received by the optical circuit 101. In particular, the reference beam receiver as the optical receiver 104 measures the amplitude of the reference beam from the active optical components and converts the signal from the reference beam receiver by means of an analog-to-digital converter into a signal that can be processed by the LIDAR controller 110. The target receiver as the optical receiver 104 also measures an optical signal that carries information about the distance and speed of the target in the form of a beat frequency modulated optical signal. In this case, the reflected beam of the optical signal may be mixed with a signal from a local oscillator. The optical receiver 104 may be provided with a high-speed analog-to-digital converter that converts the signal from the target receiver into a signal that can be processed by the LIDAR controller 110.
In one aspect, the signal from the optical receiver 104 may be subject to signal conditioning by the signal conditioning unit 107 before being received by the LIDAR controller 110. For example, the signal from the optical receiver 104 may be provided to an operational amplifier in the signal conditioning unit 107 for amplification of the return signal, and the amplified signal provided by the operational amplifier to the LIDAR controller 110.

In some applications, the LIDAR system 100 may additionally include one or more imagers 108 configured to capture images of the environment, a global positioning system (GPS) 109 configured to provide a geographic location of the system, or other sensor inputs. The LIDAR system 100 may also include an image processor 114 configured to receive images and geographic locations from the imagers 108 and the GPS 109, and transmit the images and location or related information to the LIDAR controller 110 or other systems connected thereto.

In operation according to some embodiments, the LIDAR system 100 is configured to simultaneously measure distance and velocity in two dimensions using a non-degenerate optical source. This capability enables real-time, long-range measurements of distance, velocity, azimuth, and elevation of the surrounding environment.

In some examples, the scanning process is initiated by the optical driver 103 and the LIDAR controller 110. The LIDAR controller 110 instructs the optical driver 103 to modulate one or more light beams, respectively, and these modulated signals are transmitted through the passive optical circuitry of the optical circuitry 101 to the collimator of the free space optics 115. The collimator directs the modulated signals to the optical scanner 102, which scans the environment in a pre-programmed pattern defined by the motion controller 105. The optical circuitry 101 may be provided with a polarizing waveplate (PWP) that transforms the polarization state of the light as it exits the optical circuitry 101.
In one aspect, the polarizing wave plate may be a quarter wave plate or a half wave plate. A portion of the polarized light beam may be reflected back into the optical circuit 101. For example, a lens or collimating system used in the LIDAR system 100 may have natural reflective properties or a reflective coating that causes a portion of the light beam to be reflected back into the optical circuit 101.

The optical signal reflected from the environment is sent through the optical circuit 101 to the receiver (optical receiver 104). At this time, the polarization state of the light has been changed, so it is reflected by the polarizing beam splitter along with a portion of the polarized light that was reflected back to the optical circuit 101. As a result, the reflected optical signals do not return to the same optical fiber or waveguide as the light source, but are reflected to different optical receivers. These signals interfere with each other and generate a combined signal. Each beam signal returning from the target generates a time-shifted waveform, and the time phase difference between these two waveforms generates a beat frequency that is measured by the optical receiver (photodetector). The combined signal can then be reflected to the optical receiver 104.

The analog signal received by the optical receiver 104 is converted to a digital signal by an ADC (analog to digital converter). The digital signal is then sent to the LIDAR controller 110, whose signal processing unit 112 receives and processes the digital signals. In one aspect, the signal processing unit 112 receives position data from the motion controller 105 and a galvanometer (not shown) and image data from the image processor 114. This allows the signal processing unit 112 to generate a 3D point cloud with information about the distance and velocity of points in the environment as the optical scanner 102 scans additional points. The signal processing unit 112 may also overlay the 3D point cloud with image data to determine the velocity and distance of surrounding objects.
The system may further process satellite-based navigation position data to provide precise global position information.

FIG. 2 is a time-frequency diagram 200 of an FMCW scanning signal 201 that, in one embodiment, a LIDAR system, such as LIDAR system 100, can use to scan a target environment.
In this example, the FMCW scanning signal 201, denoted as fFM(t), is a sawtooth waveform (sawtooth "chirp") with a chirp bandwidth Δfc and a chirp period Tc. The slope of the sawtooth is k=(Δfc/Tc).
Also shown in FIG. 2 is a target return signal 202 in one embodiment.
The target return signal 202, denoted fFM(t-Δt), is a time delayed version of the FMCW scanning signal 201, where Δt is the round trip time to and from the target illuminated by the FMCW scanning signal 201. This round trip time is given by Δt=2R/v, where R is the range of the target and v is the speed of light, c, which is the speed of the light beam.
Therefore, the range R of the target can be calculated as R=c(Δt/2).
When the target return signal 202 is optically mixed with the FMCW scanning signal, a range-dependent difference frequency ("beat frequency") ΔfR(t) is generated. The beat frequency ΔfR(t) is linearly related to the time delay Δt by the sawtooth slope k, i.e., ΔfR(t) = kΔt. Since the range R of the target is proportional to Δt, the range R of the target can be calculated as R = (c/2)(ΔfR(t)/k). That is, the range R is linearly related to the beat frequency ΔfR(t).
The beat frequency ΔfR(t) is generated as an analog signal, for example, in the optical receiver 104 of the LIDAR system 100. This beat frequency is digitized, for example, by an analog-to-digital converter (ADC) in the signal conditioning unit 107 of the LIDAR system 100. The beat frequency signal thus digitized is digitally processed in a signal processing unit (e.g., signal processing unit 112) in the LIDAR system 100.
However, it should be noted that if the target has a relative velocity with respect to the LIDAR system 100, the target return signal 202 will generally contain a frequency offset (Doppler shift).
For simplicity and ease of illustration, the Doppler shift is not shown in FIG. 2 because it is detected separately and used to correct the frequency of the return signal. It should also be noted that the sampling frequency of the ADC is determined by the highest beat frequency that the system can handle without aliasing. Typically, the highest frequency that can be handled is half the sampling frequency (i.e., the "Nyquist limit"). For example, and not by way of limitation, if the sampling frequency of the ADC is 1 GHz, then the highest beat frequency (ΔfRmax) that can be handled without aliasing is 500 MHz. This limit is determined by the maximum target range of the system, Rmax=(c/2)(ΔfRmax/k), which can be adjusted by changing the sawtooth slope k.
In one example, data samples from the ADC may be continuous, but subsequent digital processing, described below, may be divided into "time segments" that may be related to a predetermined periodicity of the LIDAR system 100. For example, but not limited to, a time segment may correspond to a number of chirp periods Tc, or a number of azimuthal rotations by the optical scanner described above.

In some scenarios, there are several sources of phase disturbance experienced by a LIDAR system, such as the LIDAR system described in FIG.
These sources include, for example, laser phase noise, circuit phase noise, flicker noise imparted to the laser by the drive electronics, drift due to temperature and weather, chirp rate offset, and so on.

FIG. 3A illustrates a phase disturbance that can be mitigated by an embodiment of the present invention.
A peak 301 corrected for phase impairments is shown corresponding to an uncorrected peak 303. As shown in Figure 3A, the phase impairments on the received signal depend on the distance of the target. In some scenarios, a more distant target may have a higher bandwidth of phase impairments compared to a closer target. For example, the farthest uncorrected peak 305 shown in Figure 3A can be seen to have a significantly higher bandwidth of phase impairments compared to the closer uncorrected peak 307.
In some scenarios, the phase impairment may depend only on distance and not on Doppler shift, while the peak frequency may depend on both distance and Doppler shift. In some embodiments, the dependence of the phase impairment on distance may be exploited in some of the correction algorithms described herein. In some embodiments, the deskew filter may apply a negative group delay that is linearly proportional to frequency.

FIG. 3B illustrates a dynamic scenario that can be mitigated by an embodiment of the present invention.
As shown in FIG. 3B, the peak frequency 311 can be calculated as Frequency = α × (times) Δt ± (plus or minus) Doppler shift 309, where α is the slope of the chirp (also called the chirp rate).
In some embodiments, the deskew filter applies a negative group delay based on α × (times) range ± (plus or minus) Doppler shift instead of α × (times) range, which may result in degraded performance and reduced probability of detection and range/velocity errors for dynamic targets.

The embodiments described herein address these issues, for example, by utilizing a described ego-Doppler compensated phase impairment corrector, which can compensate for ego velocity before applying a deskew filter.
Ego speeds as described herein include, but are not limited to, vehicle speed, sensor speed, mirror speed, etc. Also includes any previous ego speed determinations made by or provided to the systems described herein, and any combination thereof.
As used herein, ego velocity can be estimated using either a point cloud or can be measured using one or more motion sensors, such as an inertial measurement unit (IMU).

In some embodiments, a proximity velocity based phase impairment corrector may be used, as described in more detail below with reference to FIG. 6. The signal may be passed through a deskew filter, and an estimate of the true target velocity may be derived using the velocity of a subset of all nearby detection points using a standard deskew filter, and the correction procedure may be re-run based on the proximity velocity estimate.

In some embodiments, a phase impairment corrector based on previous detection points can be used. A phase impairment corrector based on previous detection points can use velocities from previous estimated detection points to estimate the most likely velocity of the current detection point and apply that frequency shift before deskewing. In some embodiments, the immediately previous detection point can be used. In embodiments, a detection point from a previous scan line can be used. In some embodiments, a detection point from a previous frame can be used.

In some embodiments, an iterative phase impairment corrector and/or a multi-Doppler compensation phase impairment corrector can be used. In some embodiments, Doppler compensation can be applied to either the target ADC samples or the deskew filter coefficients in any of the described approaches.

FIG. 4 is a block diagram of an exemplary LIDAR system having a reference arm 427 in accordance with an embodiment of the present disclosure.
As shown in FIG. 4, according to some embodiments, one or more reference arms 427 can be added to the LIDAR system to generate a digitally sampled reference signal 426 that can be used to estimate phase impairments of the transmitted signal. For example, in one embodiment, one or more reference arms 427 can be included as part of the optical circuit 101, the signal conversion unit 106, and/or the signal conditioning unit 107 of FIG. 1. In this exemplary embodiment, the system includes a beam source 401, such as an FMCW laser source. A target arm 405 includes a number of optical components (e.g., lenses or filters) through which the scanning signal 403 can pass on its way to the target 407. A return signal 409 is reflected from the target 407 and directed toward a photodetector 411.
In this embodiment, a local oscillator (LO) signal 413 that is part of the scanning signal 403 is directed to a photodetector 411 before being sent to the target 407. From the photodetector 411, a digitally sampled target signal 416 is then passed through a target ADC 415 to a DSP 417.

As shown in this embodiment, the reference arm 427 receives a signal portion 419 of the scanning signal 403 which is provided either directly to a photodetector 421 or after passing through a delay device 423 of known length.
According to some embodiments, signal portion 419 is received by photodetector 421 as scanning signal 403 is contemporaneously transmitted through the optical components of target arm 405. According to some embodiments, signal portion 419 is received by photodetector 421 after scanning signal 403 passes through the optical components of target arm 405. According to some embodiments, delay device 423 can be a fiber-delay device, or the like. In one embodiment, delay device 423 can include a fiber-coil having a known length that can create a virtual target (e.g., fiber-target) at a known distance.

In some scenarios, the distance of the virtual target can be determined in advance. The optical signal at the output of the reference delay has the same characteristics as the target return signal 202 depicted in FIG. 2. According to some embodiments, in a manner similar to that described in FIG. 2, the virtual target can generate a return signal 409 that is a time-delayed version of the scanning signal 403. When the return signal 409 is optically mixed with the scanning signal 403, a difference frequency (hereinafter referred to as the "reference beat frequency") is generated that depends on the reference distance. According to some embodiments, the reference beat frequency is then digitized and adjusted, for example using the procedure described herein in FIG. 1. This reference signal has the same phase impairment characteristics as the return signal from the target. A phase impairment estimator and a phase impairment corrector based at least in part on the reference signal generated by the reference arm 427 can compensate for phase impairments in the signal transmitted toward the target (i.e., the "target" signal) and the signal received therefrom (i.e., the "received" signal).

From the photodetector 421 , the digitally sampled reference signal 426 then passes through a reference ADC 425 and then to the DSP 417 .
As shown in FIG. 4, an embodiment of the present invention can generate point cloud data 429 based on transmitting and receiving various signals including a return signal 409 from a target, a local oscillator (LO) signal 413, and a reference arm 427.

FIG. 5 illustrates an ego-Doppler compensation phase impairment corrector in accordance with an embodiment of the present invention.
5, the phase impairment corrector 509 comprises an ego-Doppler compensation phase impairment corrector configured to compensate for the estimated or measured ego-Doppler by introducing an applied frequency shift into the received signal by frequency shifter 507 before executing the deskew filter 508, and restoring the frequency shift by frequency shifter 511 after the phase impairment correction. In some embodiments, the ego-Doppler compensation phase impairment corrector may be applied to static targets in a given scene.

As shown in FIG. 5, the phase impairment estimator 503, phase impairment corrector 509, along with one or more reference ADCs 501 and target ADCs 505, may correspond to DSP 417 of FIG. 4 in some embodiments.
In one embodiment, one or more of the phase impairment estimator 503 and/or phase impairment corrector 509 are included as part of the signal processing unit 112 of Figure 1. In some embodiments, the architecture also includes a time domain filter 513, a time domain (TD) to frequency domain (FD) converter 515, a frequency domain filter 517, and a peak detection component 519. The digital signal processing architecture can generate and process data such as point cloud data 521.
Although the use of point clouds is described herein, it should be understood that embodiments are not limited to such and may include, but are not limited to, point clouds.

FIG. 6 illustrates a proximity velocity based corrector used by a phase impairment corrector according to an embodiment of the present invention.
As shown in Figure 6, the phase impairment corrector 609 is configured with a proximity velocity based corrector that runs the phase impairment corrector 623 on a subset of all points and estimates the velocity based on the proximity detection points using a proximity estimator 633. In some embodiments, the estimate is the mean/median or any other statistical value of the velocity of the proximity detection points. In an alternative embodiment, the proximity velocity based corrector can re-run the phase impairment corrector to compensate for the estimated Doppler shift and re-estimate the peaks.

Once the approach velocity is estimated, an estimated Doppler shift is calculated by Doppler shift estimator 635 and the associated frequency shift is introduced in frequency shifter 607 before the deskew filter 608 and phase impairment corrector 609 .
As described above, deskew filter 608 applies a variable delay that is frequency based, so that adjustments to the frequency introduced by frequency shifter 607 affect the delay applied by deskew filter 608. In some embodiments, the second frequency shift applied by frequency shifter 611 is the conjugate of the first frequency shift introduced by frequency shifter 607.

As shown in FIG. 6, the digital signal processing architecture includes one or more reference ADCs 601 and target ADCs 605 , as well as a phase impairment estimator 603 , a phase impairment corrector 609 .
In some embodiments, the proximity velocity estimator arm also includes a time domain filter 625, a TD to FD converter 627, a frequency domain filter 629, and a peak detection component 631. Similarly, the target arm architecture may also include a time domain filter 613, a TD to FD converter 615, a frequency domain filter 617, and a peak detection component 619. The digital signal processing architecture may generate and process data such as point cloud data 621.

FIG. 7 is a diagram illustrating a pre-detection point-based corrector according to an embodiment of the present invention.
As shown in FIG. 7, the phase impairment corrector 709 includes a previous detection point based corrector configured to estimate the velocity of a detection point based on a previously estimated detection point. In some embodiments, the immediately previous detection point may be used. In some embodiments, a detection point from a previous scan line may be used, or a detection point from a previous frame may be used. The previous detection point based corrector may be used to estimate the velocity to compensate for the Doppler shift before the phase impairment corrector.

As shown in FIG. 7, the digital signal processing architecture includes one or more reference ADCs 701 and target ADCs 705 , as well as a phase impairment estimator 703 , a phase impairment corrector 709 .
In some embodiments, the target arm architecture may also include a time domain filter 713, a TD to FD converter 715, a frequency domain filter 717, and a peak detector 719. The digital signal processing architecture may generate and process data such as point cloud data 721. In this exemplary embodiment, after the peak detector 719, a velocity estimator 723 estimates the velocity of the previous detection point as described above. Based on this velocity estimate, an associated frequency shift may be introduced in a frequency shifter 707 before the deskew filter 708 and the phase impairment corrector 709.
As described above, deskew filter 708 applies a variable delay based on frequency, so that adjustments to the frequency introduced by frequency shifter 707 affect the delay applied by deskew filter 708. In some embodiments, the second frequency shift applied by frequency shifter 711 is the conjugate of the first frequency shift introduced by frequency shifter 707.

FIG. 8 illustrates an iterative phase impairment corrector according to an embodiment of the present invention.
As shown in Figure 8, the phase impairment corrector 807 is configured using an iterative phase impairment corrector, which can loop multiple times until convergence. As shown in Figure 8, the digital signal processing architecture includes a phase impairment estimator 801, a filter tap calculation 803, and a phase impairment corrector 807.
In some embodiments, the target arm architecture may also include a time domain filter 811 , a TD to FD converter 813 , a frequency domain filter 815 , and a peak detector 817 .

In this exemplary embodiment, a first frequency shift is introduced in frequency shifter 805 before deskew filter 808 and phase impairment corrector 807. A second frequency shift may be introduced in frequency shifter 809, which may be the conjugate of the first frequency shift from frequency shifter 805.
In this exemplary embodiment, after peak detector 817, the process is repeated with different frequency shifts introduced in frequency shifter 805 and frequency shifter 809 until convergence. In each iteration, the velocity estimate from the previous iteration is used to apply the frequency shift.
Thus, in each iteration, the selected peak and the corresponding distance and velocity estimates may be different. If the selected peak is the same for two or more successive iterations, convergence is achieved.

FIG. 9 illustrates a multi-ego Doppler compensation phase impairment corrector according to an embodiment of the present invention.
As shown in FIG. 9, each of the phase impairment correctors 909 and 927 is a multi-ego Doppler compensation type phase impairment corrector that performs phase impairment correction on a plurality of different (N) Doppler compensated received signals and selects the best one.

As shown in FIG. 9, the digital signal processing architecture includes a phase impairment estimator 903, multiple phase impairment correctors 909, 927, along with one or more reference ADCs 901 and target ADCs 905. In this particular embodiment, a received signal 904 is diverted into multiple different paths, each path including a different frequency shift. For example, a first frequency shift can be introduced by a frequency shifter 907 before the first deskew filter 908 and the first phase impairment corrector 909. After the first phase impairment corrector 909, the frequency shift introduced by the frequency shifter 907 can be inverted by a frequency shifter 911.
In some embodiments, this first target arm may also include a time domain filter 913, a TD to FD converter 915, a frequency domain filter 917, and a peak detection component 919. Similarly, the Nth target arm may include an Nth frequency shift introduced in a frequency shifter 923 before the Nth deskew filter 925 and the Nth phase impairment corrector 927. After the Nth phase impairment corrector 927, the frequency shift introduced in the frequency shifter 923 may be inverted in a frequency shifter 929. In some embodiments, the Nth target arm may also include a time domain filter 931, a TD to FD converter 933, a frequency domain filter 935, and a peak detection component 937.
Finally, once peaks have been detected for each of several delays, the best peak can be selected at 921. Selecting the best peak may, in some embodiments, include picking the strongest peak, highest SNR, or other metric used for signal detection.

FIG. 10 is a flow diagram illustrating an example of a method for compensating for phase impairments in a LIDAR system according to an embodiment of the present disclosure.
The method begins in operation 1001 by transmitting a first light beam to a target. The first light beam may include, for example, an FMWC beam. In an embodiment, the light beam may be transmitted from a beam source 401.

In operation 1003, a return signal 409 is received from the target at a first detector. The first detector that receives the return signal 409 may be the optical detector 411 described above with reference to FIG. 4.

In operation 1005, the local oscillator (LO) signal 413, the photodetector 411, and the return signal 409 are used to generate a digitally sampled target signal 416.

In operation 1007, the ego velocity and target velocity of the digitally sampled target signal 416 are compensated based on the estimated ego velocity and the estimated target velocity. This compensation can be performed in some embodiments using frequency shifters 507, 511, 607, 611, 707, 711, 805, 809, 907, 911, 923, 929. In one embodiment, a first frequency shift can be applied to the digitally sampled target signal, where the first frequency shift is a function of the ego velocity of the LIDAR system and the estimated target velocity. A second frequency shift can be applied to the digitally sampled target signal that is the conjugate of the first frequency shift.
In some embodiments, the estimated target velocity is based on the velocity of the proximity detection points, which can be determined by running a standard corrector on all of the proximity detection points and estimating a statistical value (e.g., average or median) of the velocities of the proximity detection points.
In other embodiments, the estimated target velocity is based on the velocity of a previous detection point.

In operation 1009, phase impairment correction is performed on the digitally sampled target signal using the phase impairment correctors 509, 609, 709, 807, 909, and 927.
In some embodiments, the method also includes generating a digitally sampled reference signal using a reference beam transmitted through a fiber delay device having a known length. The phase impairment correction can correct for phase impairments introduced into the digitally sampled target signal by the LO beam and the return signal. In such embodiments, the reference beam can be split from the first optical beam using a beam splitter. In some embodiments, adjusting for phase impairments in the return signal includes introducing a delay into the return signal based on the frequency of the return signal. Such a delay can be proportional to the frequency of the return signal. That is, reflections from more distant targets can experience more delay and reflections from closer targets can experience less delay. This delay can be introduced using, for example, deskew filters 508, 608, 708, 808, 908, 925.

FIG. 11 is a flow diagram illustrating another example method for compensating for phase impairments in a LIDAR system according to an embodiment of the present disclosure.
The method begins in operation 1101 by receiving a return signal 409 reflected from a target 407 at a LIDAR system. The return signal 409 is a reflection of a scanning signal (first optical beam) 403 transmitted from the LIDAR system. The scanning signal (first optical beam) 403 can be transmitted using a beam source 401 in some embodiments.

In operation 1103, the method determines the ego velocity of the LIDAR system. In some embodiments, the ego velocity is the velocity of the LIDAR system relative to a nearby object. The ego velocity may also include the velocity of a mirror associated with the LIDAR system.
In some embodiments, the ego velocity of the LIDAR system can be determined using, for example, the signal processing unit 112 or the motion controller 105 described with reference to FIG. 1 .

In operation 1105, the method determines an estimated target velocity. In some embodiments, determining the estimated target velocity includes determining a velocity of a proximity detection point proximate to the target and generating the estimated target velocity based on the velocities of the proximity detection points.
In some embodiments, estimating the velocity of the proximity detection points includes running a standard corrector on all the proximity detection points and estimating a statistic (e.g., average or median) of the velocities of the proximity detection points. In an alternative embodiment, determining the estimated target velocity includes determining the velocity of a previous detection point of the target in the point cloud and generating the estimated target velocity based on the velocity of the previous detection point. In some embodiments, the previous detection point includes the velocity of an immediately preceding detection point in the same scan line or a detection point from a previous scan line or a previous scan frame. In some embodiments, the estimated target velocity can be determined using, for example, the signal processing unit 112 or the image processing unit 114 described with reference to FIG. 1.

In operation 1107, an estimated phase impairment is calculated using the phase impairment estimator 503, 603, 703, 801, 903. In operation 1109, a first frequency shift is applied to the return signal. In some embodiments, the first frequency shift is a function of the ego velocity of the LIDAR system. In some embodiments, the first frequency shift is a function of the estimated target velocity determined in operation 1105.

Once the first frequency shift has been applied, in operation 1111 the return signal is adjusted to account for the phase impairment based on the estimated phase impairment.
In some embodiments, adjusting for phase impairments in the return signal includes introducing a delay into the return signal based on a frequency of the return signal.
Such a delay may be proportional to the frequency of the return signal (i.e., reflections from more distant targets may experience more delay and reflections from closer targets may experience less delay). This delay may be introduced using, for example, deskew filters 508, 608, 708, 808, 908, 925.

In operation 1113, a second frequency shift is applied to the delayed beam from the deskew filter.
In some embodiments, the second frequency shift is the conjugate of the first frequency shift. The frequency shifts performed in operations 1109 and 1113 can be performed using frequency shifters 507, 511, 607, 611, 707, 711, 805, 809, 907, 911, 923, and 929, for example.

In the above description, specific examples of specific systems, components, methods, etc. are shown to facilitate understanding of the embodiments of the present invention. However, those skilled in the art can practice the present invention without the description of these specific examples. Also, details of well-known components and methods may be omitted or shown in the form of simple block diagrams in order to facilitate understanding of the present invention. Therefore, the contents disclosed are merely examples, and even if one example differs from other examples, it is considered to be within the scope of the present invention.

When the phrase "one embodiment" or "embodiment" is used in this specification, it means that the particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment. Thus, the appearance of the phrase "in one embodiment" or "in an embodiment" in several places in this specification does not necessarily refer to the same embodiment.

The term "coupled," along with its derivatives, is used to indicate that two or more elements interact with each other. These coupled elements may or may not be in direct physical or electrical contact with each other.

Although the method operations described herein are shown in a particular order, the order of operations in each method may be changed, certain operations may be performed in reverse order, or at least some operations may be performed simultaneously with other operations. Instructions for different operations or auxiliary operations may be performed intermittently or alternately.

The above-described description of the embodiments of the invention (including the contents described in the Abstract) is not intended to be detailed or exhaustive, nor is it intended to limit the invention to the specific forms disclosed. Specific embodiments and examples of the invention are described herein for illustrative purposes, but various equivalent modifications may be made within the scope of those skilled in the art. As used herein, the word "example" or "exemplary" is used to mean serving as an example, illustration, or explanation. An aspect or design described herein as "example" or "exemplary" should not necessarily be construed as preferred or advantageous over other aspects or designs. Rather, use of the term "example" or "exemplary" is intended to illustrate concepts in a concrete manner.
The term "or" as used herein is intended to be interpreted as an inclusive "or" rather than an exclusive "or." That is, unless otherwise specified or clear from the context, the phrase "X includes A or B" refers to any of the natural inclusive permutations. That is, if X includes A, if X includes B, or if X includes both A and B, then in any of the above cases, the condition "X includes A or B" is satisfied.
Furthermore, the articles "a" and "an" as used in this specification and the appended claims are to be construed to mean "one or more" unless otherwise specified and unless the singular form is clear from the context.
Furthermore, when terms such as "first,""second,""third," and "fourth" are used in this specification, these terms are used as identifiers to distinguish different elements and do not necessarily indicate an order according to the numerical designation.

Claims (17)

1. A method for correcting phase impairments in a Light Detection and Ranging (LIDAR) system (hereinafter referred to as a LIDAR system) , comprising:
transmitting a first light beam towards a target;
receiving a second light beam from the target based on the first light beam to generate a return signal;
transmitting a local oscillator (LO) beam and the return signal to a first photodetector and using the first photodetector to generate a digitally sampled target signal;
transmitting a portion of the first optical beam signal and a fiber delay of the portion of the first optical beam signal to a second optical detector and using the second optical detector to generate a digitally sampled reference signal;
determining an estimated ego velocity of the LIDAR system and an estimated target velocity of the target;
introducing a frequency shift to the digitally sampled target signal through a first frequency filter based on an estimated ego velocity of the LIDAR system and an estimated target velocity of the target;
correcting a phase impairment of the target signal incorporating the frequency shift based on the reference signal;
undoing the frequency shift of the phase impairment corrected target signal with a second frequency filter to generate a point cloud;
The method includes: The method according to claim 1,
The method of claim 1, wherein the estimated ego velocity is an ego velocity of the LIDAR system calculated based on nearby objects measured using one or more motion sensors. 2. The method of claim 1 ,
the frequency shift by the first frequency shifter is a function of ego velocity of the LIDAR system;
A method according to claim 1, wherein the frequency shift by the second frequency shifter is a conjugate of the frequency shift by the first frequency shifter . The method according to claim 1,
determining the velocity of adjacent detection points around the periphery of the target;
generating the estimated target velocity based on velocities of the adjacent detection points . 5. The method of claim 4,
The step of determining the velocity of adjacent detection points comprises:
running a standard corrector on all of the adjacent detection points;
and estimating statistics of the velocities of said adjacent detection points . The method according to claim 1,
determining a velocity of a previous detection point of the target within the point cloud;
generating the estimated target velocity based on velocities of the previous detection points . 7. The method of claim 6,
The step of determining a velocity of a previous detection point of the target within the point cloud comprises:
The method includes determining the velocity of a immediately preceding detection point on the same scan line, determining the velocity of a detection point from a previous scan line, or determining the velocity of a detection point from a previous scan frame . 1. A light detection and ranging (LIDAR) system (hereinafter referred to as a LIDAR system), comprising:
a light beam source for transmitting a first light beam to a target;
a first photodetector that receives a return signal from the target and a local oscillator (LO) beam and generates a digitally sampled target signal;
a fiber delay device having a known length and coupled to the optical beam source;
a second photodetector coupled to the fiber delay for generating a digitally sampled reference signal using a portion of the first optical beam signal and a portion of the first optical beam signal delayed through the fiber delay;
a first frequency shifter that introduces a frequency shift to the digitally sampled target signal based on an estimated ego velocity of the LIDAR system and an estimated target velocity of the target;
a deskew filter for correcting a phase impairment of the target signal incorporating the frequency shift based on the reference signal;
a second frequency shifter for undoing the frequency shift on the phase impairment corrected target signal to generate a point cloud;
A LIDAR system comprising : 9. The LIDAR system of claim 8,
The estimated ego velocity is the ego velocity of the LIDAR system relative to a nearby object as measured using one or more motion sensors . 9. The LIDAR system of claim 8,
the frequency shift by the first frequency shifter is a function of ego velocity of the LIDAR system;
a frequency shift by the second frequency shifter is a conjugate of a frequency shift by the first frequency shifter . 9. The LIDAR system of claim 8 ,
The LIDAR system is further configured to determine the estimated target velocity based on velocities of adjacent detection points in a perimeter of the target . 12. The LIDAR system of claim 11 ,
determining velocities of the adjacent detection points by performing a standard correction on all of the adjacent detection points and estimating statistics of the velocities of the adjacent detection points. 9. The LIDAR system of claim 8 ,
The LIDAR system is further configured to determine the estimated target velocity based on a velocity of a previous detection point of the target in a point cloud . 14. The LIDAR system of claim 13,
determining the velocity of the previously detected point by determining the velocity of a immediately preceding detected point on the same scan line, determining the velocity of the detected point on a previous scan line, or determining the velocity of the detected point on a previous scan frame . 1. A method for correcting phase impairments in a Light Detection and Ranging (LIDAR) system (hereinafter referred to as a LIDAR system), comprising:
transmitting a first beam of light from the LIDAR system to a target;
receiving a local oscillator (LO) beam and a return signal from the target at a first photodetector in the LIDAR system and generating a digitally sampled target signal using the first photodetector;
receiving a portion of the first optical beam signal and a portion of the first optical beam signal delayed through a fiber delay device at a second optical detector, and generating a digitally sampled reference signal using the second optical detector;
estimating one or more phase impairments of the LIDAR system using the digitally sampled reference signal to generate one or more estimated phase impairments;
applying a first frequency shift to the target signal, the first frequency shift being a function of an ego velocity of the LIDAR system and an estimated target velocity of the target;
adjusting a phase impairment of the target signal having the first frequency shift applied based on the estimated phase impairment;
applying a second frequency shift, which is a conjugate of the first frequency shift, to the phase impairment adjusted target signal to generate a point cloud using a deskew filter;
The method includes : The method according to claim 15, further comprising the steps of:
determining the velocity of adjacent detection points around the periphery of the target;
generating the estimated target velocity based on velocities of the adjacent detection points . The method according to claim 15, further comprising the steps of:
determining a velocity of a previous detection point of the target within the point cloud;
generating the estimated target velocity based on velocities of the previous detection points .

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