CN117337401A - Techniques for mitigating ghosts in a coherent LIDAR system using in-phase/quadrature-phase (IQ) processing - Google Patents

Abstract

A light detection and ranging (LIDAR) system for transmitting a light beam comprising at least one up-chirp frequency and at least one down-chirp frequency to a target in a field of view of the LIDAR system and receiving an up-and down-chirped return signal reflected from the target. The LIDAR system may perform IQ processing on one or more return signals to generate a baseband signal in the frequency domain of the return signals during at least one of the up-chirps and at least one of the down-chirps. The baseband signal includes a first set of peaks associated with the at least one up-chirp frequency and a second set of peaks associated with the at least one down-chirp frequency. The LIDAR system determines a target location using the first set of peaks and the second set of peaks.

Description

Techniques for mitigating ghosts in a coherent LIDAR system using in-phase/quadrature-phase (IQ) processing

RELATED APPLICATIONS

The present application claims priority and benefit from U.S. provisional patent application Ser. No. 63/165,601, filed on even 24. 3/2021, and U.S. non-provisional patent application Ser. No. 17/702,595, filed on even 23/2022, which are incorporated herein by reference in their entireties.

Technical Field

The present disclosure relates generally to LIDAR (light detection and ranging) systems, and more particularly to ghost mitigation in coherent LIDAR systems.

Background

LIDAR systems, such as Frequency Modulated Continuous Wave (FMCW) LIDAR systems, use tunable infrared lasers to frequency chirped illuminate a target and coherent receivers to detect backscattered or reflected light from the target that is combined with a local replica of the transmitted signal. The local replica is mixed with a round trip time delayed return signal (e.g., a return signal) that is reached and returned to the targets, and signals are generated at the receiver at a frequency proportional to the distance to each target in the field of view of the system. The distance and speed of the detection target can be detected using an up sweep of frequency (upsweep) and a down sweep of frequency (downsweep). However, when one or more of the LIDAR system and the target (or targets) are moving, a problem arises in that peaks corresponding to each target are associated.

Disclosure of Invention

The present disclosure describes examples of systems and methods for ghost mitigation in a coherent LIDAR system.

According to one aspect, the present disclosure is directed to a method. The method comprises the following steps: one or more light beams are emitted toward a target in a field of view of a light detection and ranging (LIDAR) system, the one or more light beams including at least one up-chirp frequency and at least one down-chirp frequency. The method also includes receiving a set of return signals from the target based on the one or more beams. The method also includes determining whether a peak associated with the target is within one or more sets of frequency ranges that include signal attribute values corresponding to a lower likelihood of accurately calculating a position or velocity of the target. The method further comprises the steps of: in-phase quadrature phase (IQ) processing is performed on one or more received signals if a peak associated with the target is within the one or more sets of frequency ranges. The set of return signals includes doppler shifted up-chirp frequencies shifted from the at least one up-chirp frequency caused by relative motion between the target and the LIDAR system and doppler shifted down-chirp frequencies shifted from the at least one down-chirp frequency caused by relative motion between the target and the LIDAR system. The doppler shift up-chirp frequency and the doppler shift down-chirp frequency produce a first set of peaks associated with the at least one up-chirp frequency corresponding to the target location of the target and a second set of peaks associated with the at least one down-chirp frequency corresponding to the target location of the target. The method further includes determining one or more of a target position, a target velocity, and a target reflectivity using the first set of peaks and the second set of peaks.

In one embodiment, the first set of peaks includes a first true peak and a first mapped peak, the second set of peaks includes a second true peak and a second mapped peak, and the IQ process reduces a first magnitude of the first mapped peak and a second magnitude of the second mapped peak.

In one embodiment, determining the target location using the first set of peaks and the second set of peaks includes: selecting a first true peak from the first set of peaks and a second true peak from the second set of peaks; and determining a target location based on the first true peak and the second true peak.

In one embodiment, the one or more sets of frequency ranges are based on the self-velocity of the LIDAR system.

In one embodiment, performing IQ processing includes: generating a first signal and a second signal based on the set of return signals, wherein the first signal is offset from the second signal by 90 degrees; generating a third signal, wherein the third signal comprises a combination of the first signal and imaginary units; and combining the third signal and the second signal to generate a combined signal.

In one embodiment, performing IQ processing further comprises: the combined signal is subjected to a fast fourier transform.

In one embodiment, combining the third signal and the second signal comprises:

Subtracting the third signal from the second signal for up-chirp, and adding the third signal to the second signal for down-chirp; or for up-chirping the third signal is added to the second signal and for down-chirping the third signal is subtracted from the second signal.

In one embodiment, subtracting the third signal from the second signal and for down-chirping, adding the third signal to the second signal reduces a frequency range that is processed to determine one or more of a target position, a target velocity, and a target reflectivity.

In one embodiment, the method further comprises: if the peak associated with the target is not within the one or more sets of frequency ranges, then the use of an in-phase quadrature phase (IQ) circuit is avoided.

According to one aspect, the present disclosure is directed to a light detection and ranging (LIDAR) system. The LIDAR system includes an optical scanner for transmitting one or more light beams comprising at least one up-chirp frequency and at least one down-chirp frequency to a target in a field of view of the LIDAR system and receiving a set of return signals based on the one or more light beams. The LIDAR system also includes an optical processing system coupled to the optical scanner for generating a baseband signal in the time domain from the return signal, the baseband signal including a frequency corresponding to the LIDAR target distance. The LIDAR system also includes a signal processing system coupled to the optical processing system. The signal processing system includes processing means and memory for storing instructions that, when executed by the processing means, cause the LIDAR system to determine whether a peak associated with the target is within one or more sets of frequency ranges, the one or more sets of frequency ranges including signal attribute values corresponding to a lower likelihood of accurately calculating a position or velocity of the target, perform in-phase quadrature phase (IQ) processing on one or more received signals if the peak associated with the target is within the one or more sets of frequency ranges, wherein the set of return signals includes an up-chirp frequency from a doppler shift of the at least one up-chirp frequency offset caused by relative motion between the target and the LIDAR system, and a down-chirp frequency from a doppler shift of the at least one down-chirp frequency offset caused by relative motion between the target and the LIDAR system, the up-chirp frequency and the down-chirp frequency producing a first set of peaks associated with the at least one up-chirp frequency corresponding to a target position of the target, and producing a second set of peak associated with the at least one down-chirp frequency corresponding to the target position, and determining a velocity of the target, the target and the first set of peak and the velocity.

In one embodiment, the first set of peaks includes a first true peak and a first mapped peak, the second set of peaks includes a second true peak and a second mapped peak, and the IQ processing reduces a first magnitude of the first mapped peak and a second magnitude of the second mapped peak.

In one embodiment, to determine the target location using the first and second sets of peaks, the LIDAR system is further to: selecting a first true peak from the first set of peaks and a second true peak from the second set of peaks; and determining the target position according to the first true peak value and the second true peak value.

In one embodiment, the one or more sets of frequency ranges vary according to the self-speed of the LIDAR system.

In one embodiment, to perform IQ processing, the LIDAR system is further to: generating a first signal and a second signal from the set of return signals, wherein the first signal is offset from the second signal by 90 degrees; generating a third signal, wherein the third signal comprises a combination of the first signal and imaginary units; and combining the third signal and the second signal to generate a combined signal.

In one embodiment, to perform IQ processing, the LIDAR system further performs a fast fourier transform on the combined signal.

In one embodiment, to combine the third signal and the second signal, the LIDAR system is further to: subtracting the third signal from the second signal for up-chirp, and adding the third signal to the second signal for down-chirp; or for up-chirping the third signal is added to the second signal and for down-chirping the third signal is subtracted from the second signal.

In one embodiment, subtracting the third signal from the second signal and for down-chirping, adding the third signal to the second signal reduces a frequency range that is processed to determine one or more of a target position, a target velocity, and a target reflectivity.

In one embodiment, the LIDAR system is further configured to: if the peak associated with the target is not within the one or more sets of frequency ranges, then the use of an in-phase quadrature phase (IQ) circuit is avoided.

According to one aspect, the present disclosure is directed to a light detection and ranging (LIDAR) system. The LIDAR system includes a processor and a memory for storing instructions that, when executed by the processor, cause the LIDAR system to: transmitting one or more light beams to a target in a field of view of the LIDAR system, the one or more light beams comprising at least one up-chirp frequency and at least one down-chirp frequency; receiving a set of return signals from the target based on the one or more light beams; determining whether a peak associated with the target is within one or more sets of frequency ranges, the one or more sets of frequency ranges including signal attribute values corresponding to a lower likelihood of accurately calculating a position or velocity of the target; performing in-phase quadrature phase (IQ) processing on one or more received signals if peaks associated with the target are within the one or more sets of frequency ranges, wherein the set of return signals includes an up-chirp frequency at a doppler shift from the at least one up-chirp frequency shift caused by relative motion between the target and the LIDAR system and a down-chirp frequency at a doppler shift from the at least one down-chirp frequency shift caused by relative motion between the target and the LIDAR system, the up-chirp frequency at the doppler shift and the down-chirp frequency producing a first set of peaks associated with the at least one up-chirp frequency corresponding to a target location of the target and producing a second set of peaks associated with the at least one down-chirp frequency corresponding to the target location, and determining one or more of a target location, a target velocity, and a target reflectivity using the first set of peaks and the second set of peaks.

In one embodiment, the first set of peaks includes a first true peak and a first mapped peak, the second set of peaks includes a second true peak and a second mapped peak, and the IQ processing reduces a first magnitude of the first mapped peak and a second magnitude of the second mapped peak.

Drawings

For a more complete understanding of the various examples, reference is made to the following detailed description taken in conjunction with the accompanying drawings, in which like reference numerals correspond to like elements.

Fig. 1 is a block diagram illustrating an example LIDAR system according to the present disclosure;

fig. 2 is a time-frequency diagram illustrating one example of a LIDAR waveform according to the present disclosure;

fig. 3A is a block diagram illustrating an example LIDAR system according to the present disclosure;

FIG. 3B is a block diagram illustrating an electro-optical system according to the present disclosure;

FIG. 4 is a block diagram of an example signal processing system according to the present disclosure;

fig. 5 is a signal amplitude versus frequency graph showing signal peaks for a target according to the present disclosure.

Fig. 6 is a block diagram of an example signal processing system for selecting peaks according to the present disclosure.

Fig. 7A is a magnitude-frequency plot illustrating a frequency range according to the present disclosure.

Fig. 7B is a magnitude-frequency plot showing a frequency range according to the present disclosure.

Fig. 8 is a flowchart illustrating a method for selecting a peak value according to the present disclosure.

Detailed Description

The present disclosure describes various examples of LIDAR systems and methods for automatically mitigating ghosts that may occur due to doppler bias. According to some embodiments, the described LIDAR system may be implemented in any sensing market, such as, but not limited to, transportation, manufacturing, metering, medical, virtual reality, augmented reality, and security systems, among others. According to some embodiments, the described LIDAR system is implemented as part of the front end of a Frequency Modulated Continuous Wave (FMCW) device for assisting the spatial perception of an automated driver assistance system or an autonomous vehicle.

The LIDAR systems described in embodiments herein include a coherent scanning technique to detect a signal returned from a target to generate a coherent heterodyne signal from which range and velocity information of the target can be extracted. The one or more signals may include an up-sweep (up-chirp) and a down-sweep (down-chirp) of frequencies from a single light source or from separate light sources (i.e., one light source with an up-sweep and one light source with a down-sweep). Thus, two different frequency peaks (one for up-chirp and one for down-chirp) may be associated with the target and may be used to determine the target distance and speed. However, peak mapping may also occur when the LIDAR system processes these signals. The peak map may include data (e.g., graphical data) including signal attributes (e.g., SNR values) that indicate weak correspondence between detected peaks and the location and/or velocity of the target. Thus, if these peak images are used by the LIDAR system to detect a target, the LIDAR system will use erroneous data to process the position, velocity, and speed associated with the target. Using peak mapping in this manner may be referred to as "ghosting". Using the techniques described herein, embodiments of the present invention may address the above issues, for example, by introducing phase modulation into the frequency sweep/chirp. This enables the LIDAR system to match the peak and/or peak image to an expected peak shape to distinguish the peak (e.g., true peak) from the peak image. Unlike the image peaks, the true peaks include data (e.g., graphical data) that includes signal properties (e.g., SNR values) that closely correspond to the location and/or rate of the target. Thus, such peaks enable the LIDAR system to reliably identify the location, velocity, and speed of the target. It should be noted that the peak image may also be referred to as an image peak.

Fig. 1 illustrates a LIDAR system 100 according to an example embodiment of the present disclosure. The LIDAR system 100 includes one or more of the various components of the plurality of components, but may include fewer or more components than those shown in fig. 1. As shown, the LIDAR system 100 includes an optical path 101 implemented on a photonic chip. The optical path 101 may include a combination of active and passive optical components. The active optical component may generate, amplify, and/or detect an optical signal, etc. In some examples, the active optical components include light beams of different wavelengths, and include one or more optical amplifiers, one or more optical detectors, and the like.

Free-space optics 115 may include one or more optical waveguides to carry and route and manipulate optical signals to the appropriate input/output ports of the active optical components. Free-space optics 115 may also include one or more optical components such as taps, wavelength Division Multiplexers (WDM), splitters/combiners, polarizing Beam Splitters (PBS), collimators, or couplers, among others. In some examples, free-space optics 115 may include components to transform polarization states using a PBS and direct received polarized light to an optical detector, for example. The free space optics 115 may also include diffractive elements to deflect light beams having different frequencies at different angles along an axis (e.g., a fast axis).

In some examples, the LIDAR system 100 includes an optical scanner 102, the optical scanner 102 including one or more scan mirrors rotatable along an axis (e.g., a slow axis) orthogonal or substantially orthogonal to a fast axis of the diffraction element to direct an optical signal to scan the environment according to a scan pattern. For example, the scan mirror may be rotatable by one or more galvanometers. The optical scanner 102 also collects light incident on any object in the environment into a return beam that is returned to the passive optical path components of the optical path 101. For example, the return beam may be directed to an optical detector by a polarizing beam splitter. In addition to mirrors and galvanometers, the optical scanner 102 may also include components such as quarter wave plates, lenses, or antireflection coating windows.

To control and support the optical path 101 and the optical scanner 102, the LIDAR system 100 includes a LIDAR control system 110. The LIDAR control system 110 may include a processing device for the LIDAR system 100. In some examples, the processing device may be one or more general purpose processing devices such as a microprocessor or central processing unit. More particularly, the processing device may be a Complex Instruction Set Computing (CISC) microprocessor, a Reduced Instruction Set Computer (RISC) microprocessor, a Very Long Instruction Word (VLIW) microprocessor, or a processor implementing other instruction sets, or a processor implementing 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), or a network processor, etc. In some examples, the LIDAR control system 110 may include a memory to store data and instructions to be executed by the processing device. The memory may be, for example, read-only memory (ROM), random-access memory (RAM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), flash memory, magnetic disk memory such as a Hard Disk Drive (HDD), optical disk memory such as compact disk read-only (CD-ROM) and compact disk read-write memory (CD-RW), or any other type of non-transitory memory.

In some examples, the LIDAR control system 110 may include a signal processing unit 112, such as a DSP. The LIDAR control system 110 is configured to output digital control signals for controlling the optical driver 103. In some examples, the digital control signal may be converted to an analog signal by the signal conversion unit 106. For example, the signal conversion unit 106 may include a digital-to-analog converter. The optical driver 103 may then provide a drive signal to the active optical components of the optical path 101 to drive a light source such as a laser and an amplifier. In some examples, a plurality of optical drivers 103 and signal conversion units 106 may be provided to drive a plurality of light sources.

The LIDAR control system 110 is also configured to output digital control signals for the optical scanner 102. The motion control system 105 may control the galvanometer of the optical scanner 102 based on control signals received from the LIDAR control system 110. For example, a digital-to-analog converter may convert coordinate routing information from the LIDAR control system 110 into signals that may be interpreted by a galvanometer in the optical scanner 102. In some examples, the motion control system 105 may also return information regarding the position or operation of components of the optical scanner 102 to the LIDAR control system 110. For example, the analog-to-digital converter may in turn convert information about the position of the galvanometer into a signal that may be interpreted by the LIDAR control system 110.

The LIDAR control system 110 is also configured to analyze the incoming digital signal. In this regard, the LIDAR system 100 includes an optical receiver 104 to measure one or more beams received by the optical path 101. For example, the reference beam receiver may measure the amplitude of the reference beam from the active optical component, and an analog-to-digital converter converts the signal from the reference receiver into a signal that can be interpreted by the LIDAR control system 110. The target receiver measures an optical signal (modulated optical signal) in the form of a beat frequency carrying information about the distance and speed of the target. The reflected light beam may be mixed with a second signal from the local oscillator. The optical receiver 104 may include a high-speed analog-to-digital converter to convert signals from the target receiver into signals that may be interpreted by the LIDAR control system 110. In some examples, the signal from the optical receiver 104 may be signal conditioned by the signal conditioning unit 107 before being received by the LIDAR control system 110. For example, the signal from the optical receiver 104 may be provided to an operational amplifier to amplify the received signal, and the amplified signal may be provided to the LIDAR control system 110.

In some applications, the LIDAR system 100 may additionally include one or more imaging devices 108 configured to capture images of the environment, a global positioning system 109 configured to provide a geographic location of the system, or other sensor inputs. The LIDAR system 100 may also include an image processing system 114. The image processing system 114 may be configured to receive images and geographic locations and transmit the images and locations or information related thereto to the LIDAR control system 110 or other systems connected to the LIDAR system 100.

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

In some examples, the scanning process begins with the optical driver 103 and the LIDAR control system 110. The LIDAR control system 110 instructs the optical driver 103 to independently modulate one or more light beams and these modulated signals propagate through a passive optical path to a collimator. The collimator directs light at an optical scanning system that scans the environment in a preprogrammed pattern defined by the motion control system 105. The optical path 101 may also include a Polarization Waveplate (PWP) to convert the polarization of the light as it exits the optical path 101. In some examples, the polarizing waveplate may be a quarter-wave plate or a half-wave plate. A portion of the polarized light may also be reflected back into the optical path 101. For example, lenses or collimating systems used in the LIDAR system 100 may have naturally reflective properties or reflective coatings for reflecting a portion of the light back into the optical path 101.

The optical signal reflected from the environment is transmitted to the receiver through the optical path 101. Since the polarization of the light has been transformed, it may be reflected by the polarizing beam splitter along with a portion of the polarized light reflected back into the optical path 101. Thus, the reflected light is reflected to a separate optical receiver, rather than returning to the same optical fiber or waveguide as the light source. These signals perturb each other and generate a combined signal. A time-shifted waveform is generated from each beam signal returned from the target. The time phase difference between the two waveforms generates a beat frequency that is measured at an optical receiver (photodetector). The combined signal may then be reflected to the optical receiver 104.

An analog signal from the optical receiver 104 is converted into a digital signal using an ADC. The digital signal is then sent to the LIDAR control system 110. The signal processing unit 112 may then receive the digital signals and interpret them. In some embodiments, the signal processing unit 112 also receives position data from the motion control system 105 and galvanometer (not shown), as well as image data from the image processing system 114. Then, as the optical scanner 102 scans additional points, the signal processing unit 112 may generate a 3D point cloud having information about the range and speed of points in the environment. The signal processing unit 112 may also superimpose the 3D point cloud data with the image data to determine the speed and distance of objects in the surrounding area. The system also processes satellite-based navigation positioning data to provide accurate global position.

Fig. 2 is a time-frequency diagram 200 of a scan signal 201 that can be used by a LIDAR system, such as system 100, to scan a target environment, according to some embodiments. In one example, marked as f _FM The scan waveform 201 of (t) is of chirped bandwidth Δf _C And chirp period T _C Saw tooth waveform (saw tooth "chirp"). The slope of the saw tooth is given as k= (Δf) _C /T _C ). Fig. 2 also depicts a target return signal 202 (e.g., a return signal) in accordance with some embodiments. Marked as f _FM The target return signal 202 of (t- Δt) is a time-delayed version of the scan signal 201, where Δt is the round trip time relative to the target illuminated by the scan signal 201. The round trip time is given as Δt=2r/v, whichWhere R is the target distance and v is the velocity of the beam (speed of light c). Thus, the target distance R may be calculated as r=c (Δt/2). When return signal 202 is optically mixed with the scanning signal, a distance-dependent difference frequency ("beat frequency") Δf is generated _R (t). Beat frequency Δf _R (t) is linearly related to the time delay Δt with the slope of the sawtooth k. That is, Δf _R (t) =kΔt. Since the target distance R is proportional to Δt, the target distance R can be calculated as r= (c/2) (Δf _R (t)/k). That is, the distance R and the beat frequency Δf _R (t) linear correlation. For example, beat frequency Δf may be generated _R (t) as an analog signal in the optical receiver 104 of the system 100. The beat frequency may then be digitized by an analog-to-digital converter (ADC), for example in a signal conditioning unit such as signal conditioning unit 107 in LIDAR system 100. The digitized beat signal may then be digitally processed, for example, in a signal processing unit such as signal processing unit 112 in system 100. It should be noted that if the target has a velocity relative to the LIDAR system 100, the target return signal 202 will typically also include a frequency offset (doppler shift). The doppler shift can be determined separately and used to correct the frequency of the return signal, and is therefore not shown in fig. 2 for simplicity and ease of illustration. It should also be noted that the sampling frequency of the ADC will determine the highest beat frequency that can be handled by the system without aliasing. In general, the highest frequency that can be handled is half the sampling frequency (i.e., the "nyquist limit"). In one example, and without limitation, if the sampling frequency of the ADC is 1 gigahertz, the highest beat frequency (Δf _Rmax ) Is 500 mhz. This limit in turn determines the maximum distance of the system as R _max ＝(c/2)(Δf _Rmax /k) which can be adjusted by varying the chirp-slope k. In one example, while the data samples from the ADC may be continuous, the subsequent digital processing described below may be divided into "time periods" that can be associated with some periodicity of the LIDAR system 100. In one example, and without limitation, the time period may be azimuthally with a predetermined number of chirp periods T or optical scannersCorresponding to a plurality of complete rotations.

Fig. 3A is a block diagram illustrating an exemplary LIDAR system 300 according to the present disclosure. In one example, the system 300 includes an optical scanner 301 to emit a light beam, such as an FMCW (frequency modulated continuous wave) Infrared (IR) light beam 304, and to receive a return signal 313 from a reflection of an object, such as object 312, in a field of view (FOV) of the optical scanner 301, according to the light beam 304. The system 300 further includes an optical processing system 302 to generate a baseband signal 314 in the time domain from the return signal 313, wherein the baseband signal 314 contains a frequency corresponding to the LIDAR target distance. The optical processing system 302 may include the elements of the free-space optics 115, the optical path 101, the optical driver 103, and the optical receiver 104 in the LIDAR system 100. The system 300 further includes a signal processing system 303 to measure the energy of the baseband signal 314 in the frequency domain, compare the energy to an estimate of the LIDAR system noise, and determine the likelihood that a signal peak in the frequency domain is indicative of a detection target. The signal processing system 303 may include the elements of the signal conversion unit 106, the signal conditioning unit 107, the LIDAR control system 110, and the signal processing unit 112 in the LIDAR system 100.

Fig. 3B is a block diagram illustrating an example electro-optic system 350. Electro-optic system 350 includes an optical scanner 301 similar to optical scanner 102 shown and described with respect to fig. 1. The electro-optic system 350 also includes an optical processing system 302, which optical processing system 302 may include the free-space optics 115, the optical path 101, the optical driver 103, and the elements of the optical receiver 104 in the LIDAR system 100, as described above.

The electro-optical processing system 302 includes a light source 305 to generate a light beam 304. The light beam 304 may be directed to an optical coupler 306, the optical coupler 306 configured to couple the light beam 304 to a Polarizing Beam Splitter (PBS) 307 and couple a sample 308 of the light beam 304 to a Photodetector (PD) 309.PBS307 is configured to direct light beam 304 toward optical scanner 301 due to its polarization. The optical scanner 301 is configured to scan a target environment with the light beam 304 by covering a range of azimuth and elevation angles of a field of view (FOV) 310 of a LIDAR window 311 in a housing 320 of the optical system 350. In fig. 3B, only azimuth scanning is shown for ease of illustration.

As shown in fig. 3B, at one azimuth (or range of angles), the beam 304 passes through the LIDAR window 311 and illuminates the target 312. The return signal 313 from the target 312 passes through the LIDAR window 311 and is directed back to the PBS307 by the optical scanner 301.

A return signal 313 having a different polarization than beam 304 is directed by PBS307 to Photodetector (PD) 309 due to reflection from target 312. In PD309, return signal 313 is optically mixed with local samples 308 of beam 304 to generate distance-dependent baseband signal 314 in the time domain. The distance-dependent baseband signal 314 is the frequency difference (i.e., Δf) between the local sample 308 of the optical beam 304 and the return signal 313 with respect to time _R (t)). The distance-dependent baseband signal 314 may be in the frequency domain and may be generated by mixing at least one up-chirp frequency and at least one down-chirp frequency with the return signal 313. The at least one down-chirp frequency may be delayed in time in proportion to the relative motion of at least one of the target and the LIDAR system.

Fig. 4 is a detailed block diagram illustrating an example of the signal processing system 303 processing the baseband signal 314 according to some embodiments. As described above, the signal processing unit 303 may include the elements of the signal conversion unit 106, the signal conditioning unit 107, the LIDAR control system 110, and the signal processing unit 112 in the LIDAR system 100.

The signal processing system 303 includes an analog-to-digital converter (ADC) 401, a time-domain signal processor 402, a block sampler 403, a discrete fourier transform processor 404, a frequency-domain signal processor 405, and a peak search processor 406. The component blocks of the signal processing system 303 may be implemented in hardware, firmware, software, or some combination of hardware, firmware, and software.

In fig. 4, a baseband signal 314, which is a continuous analog signal in the time domain, is sampled by an ADC401 to generate a series of time-domain samples 315. The time domain samples 315 are processed by a time domain processor 402, which time domain processor 402 conditions the time domain samples 315 for further processing. For example, the time domain processor 402 may apply weighting or filtering to remove unwanted signal artifacts or to make the signal easier to process for subsequent processing. The output 316 of the time domain processor 402 is provided to a block sampler 403. The block sampler 403 groups the time domain samples 316 into groups of N samples 317 (where N is an integer greater than 1), which groups of N samples 317 are provided to the DFT processor 404. The DFT processor 404 transforms the set of N time-domain samples 317 into N frequency bins (bins) or sub-bands 318 in the frequency domain, covering the bandwidth of the baseband signal 314. The N sub-bands 318 are provided to a frequency domain processor 405, which frequency domain processor 405 adjusts the sub-bands for further processing. For example, the frequency domain processor 405 may resample and/or average the sub-bands 318 to reduce noise. The frequency domain processor 405 may also calculate signal statistics and system noise statistics. The processed subbands 319 are then provided to a peak search processor 406, which peak search processor 406 searches for signal peaks representing detection targets in the field of view of the LIDAR system 300.

Fig. 5 is an example of a signal amplitude versus frequency plot 500 showing signal peaks for one or more targets, in accordance with some embodiments. A LIDAR system (e.g., FMCW LIDAR system) may generate up-and down-chirped frequency modulations (also referred to herein as up-and down-sweeps) to scan an environment and determine a distance and a velocity of one or more targets within the environment. In one example, a single light source may generate both up-chirps and down-chirps. In another example, a system may include a light source to generate a signal including an up-chirp and another light source to generate a signal including a down-chirp. Using the return signals from the up-chirp and the down-chirp and the corresponding generated beat frequency (i.e., peak frequency), the signal processing system may determine one or more of a distance of the target and a velocity of the target. For example, according to some embodiments, the signal processing unit 112 may be configured to determine the distance of the target by calculating the distance relative to the LIDAR system 500 using a plurality of frequencies corresponding to respective peaks. As discussed above, the signal processing unit 112 may generate the baseband signal in the frequency domain by mixing at least one up-chirp frequency and at least one down-chirp frequency with one or more return signals. The at least one down-chirp frequency may be delayed in time in proportion to the relative motion of at least one of the target and the LIDAR system 500. The baseband signal may include peaks 505A, 505B, 510A, and 510B, and may include additional peaks (not shown in fig. 5).

According to some embodiments, the signal processing unit 112 may be configured to determine the speed of the target using differences between a plurality of frequencies corresponding to the peaks. However, as shown in fig. 5, there may be cases where there is also an image peak (sometimes referred to as "mirror image" or "image ghost" or the like) in the baseband signal. This may result in the LIDAR system detecting a false (or "false") target rather than the desired "true" target or peak (or "true image" or "true peak").

As shown in fig. 5, signal amplitude versus frequency plot 500 includes peak 505A, peak 505B, peak 510A, and peak 510B. Also indicated in the signal amplitude versus frequency plot 500 is a frequency 0 (e.g., 0 hertz, 0 terahertz, etc.). As discussed in more detail below, the peaks 505A, 505B, 510A, and 510B may be present in baseband signals processed and/or analyzed by a signal processing unit of the LIDAR system (e.g., signal processing unit 112 shown in fig. 1). Peak 505B may be a mirror image of peak 505A. For example, peak 505B is a mirror image across frequency 0 and shares the same characteristics (e.g., the same curvature or shape) of peak 505A. Peak 505B may be referred to as a peak map or map peak. Peak 505B may be conjugate symmetric with peak 505A and vice versa. Peak 510B may be a mirror image of peak 510A. For example, peak 510B is a mirror image across frequency 0 and shares the same characteristics (e.g., the same curvature or shape) as peak 510A. Peak 510B may also be referred to as a peak map or map peak. In some scenarios, the position of the peak 505A relative to the target is shifted (e.g., shifted) upward in frequency. Peak 505A may be referred to as a shift-up peak, a doppler shift peak, or F _up . The position of peak 510A relative to the target is shifted downward in frequency (as shown by the vertical solid line in signal amplitude-frequency plot 500). Peak 510A may be referred to as a downshifted peak, a doppler shift peak, or F _dn . The shift in peak value may be due to, for example, movement of one or more of the targets and/or sensors relative to a LIDAR system (e.g., FMCW or similar LIDAR system)And (3) starting. For example, the target may be moving, a device (e.g., a vehicle, a smart phone, etc.) including a LIDAR sensor (e.g., the optical scanner 102 and/or the optical path 101 shown in fig. 1, etc.) may be moving, or both the target and the device may be moving relative to a particular point.

Since peak 505A has shifted upward (e.g., up) to a higher frequency, peak 505B (e.g., peak image) is at a corresponding negative frequency. For example, if peak 505A is shifted to frequency J, peak 505B would be at frequency-J. In addition, since peak 510A has shifted downward (e.g., shifted downward) to a lower frequency, peak 510B (e.g., peak image) is at a corresponding positive frequency. Peak 505B may be referred to as-F _up And peak 510B may be referred to as-F _dn . In some embodiments, peak 505A (and corresponding peak 505B) may correspond to an up-chirp signal (e.g., an up-chirp signal from a particular target), and peak 510A (and corresponding peak 510B) may correspond to a down-chirp signal. In other embodiments, peak 505A (and corresponding peak 505B) may correspond to a down-chirp signal, and peak 510A (and corresponding peak 510B) may correspond to an up-chirp signal (e.g., a down-chirp signal from a particular target).

In some embodiments, a LIDAR system (e.g., the signal processing unit 112 of the LIDAR system 100 shown in fig. 1) may be configured to select the peak 505A. For example, when the target is at a closer range (e.g., within a first threshold range of the LIDAR), the peak with the highest frequency (e.g., peak 505A) may be determined to be the true peak corresponding to the target rather than the peak image, and thus selected by the LIDAR system (e.g., signal processing unit 112 shown in fig. 1). In this way, the signal processing unit 112 is configured to select the peak 505A based on the type of ghost that is occurring (e.g., near-range ghost or far-range ghost). Thus, the LIDAR (e.g., the signal processing unit 112 shown in fig. 1) is able to determine that the peak 505A should be selected to determine a range and/or distance associated with the target. In addition, since the LIDAR system (e.g., the signal processing unit 112 shown in fig. 1) has determined that the peak 505A is a true peak (rather than a peak image), the LIDAR system may also determine that the peak 505B (which has a negative frequency of the peak 505A) is a peak image. In some embodiments, the LIDAR system may be configured to discard the peak 505B (e.g., discard the peak image).

As discussed above, situations may arise where peak images (e.g., peaks 505B and 510B) also exist. For example, due to hardware and computing resources, the beat signal may experience real sampling and the frequency peaks may be assumed to be positive. However, if the target is at a closer range (e.g., within a first threshold range of the LIDAR system), a negative doppler shift may cause the beat peak to become negative. For example, peak 510A may have a negative frequency due to the downshifting. In contrast to embodiments of the present invention, this may result in a conventional system selecting peak 510B over peak 510A when determining the location of the target. For example, when using peak 505A and peak 510A, the target position may be determined as follows: (F) _up -F _dn )/2. Thus, the target (e.g., true target location) is easily determined to be toward the middle of peak 505A and peak 510A (not shown). However, if peaks 505A and 510B are used, the target location (e.g., the location of a ghost or ghost target) may be determined as follows: (F) _up +F _dn )/2。

If there is no Doppler shift, the peak in the baseband signal may be a positive frequency. However, due to the Doppler shift, the peak corresponding to the near target may shift to a negative frequency near 0Hz, while the peak corresponding to the far target may shift to a negative frequency near- ((sampling frequency)/2). Thus, the LIDAR system should determine which peaks correspond to true peaks, and if false peaks are selected, ghosts may occur (e.g., the LIDAR system may detect ghost images). If IQ processing is not performed, peak 505B may have the same height (e.g., amplitude) and shape as peak 505C and peak 510B may have the same height (e.g., amplitude) and shape as peak 510C. If peak 505B remains at the height/amplitude of peak 505C and peak 510B remains at the height/amplitude of peak 510C, this may result in the LIDAR system 100 selecting the wrong peak (e.g., peak 505B and/or 510B) in determining the location, speed, and/or reflectivity of the target.

In one embodiment, a LIDAR system (e.g., the signal processing unit 112 of the LIDAR system 100 shown in fig. 1) may perform in-phase-quadrature-phase (IQ) processing on a return signal (e.g., a received signal). IQ processing of the return signal may allow the LIDAR system to more easily, quickly, efficiently identify true peaks in the baseband signal, etc., as will be discussed in detail below.

In one embodiment, a LIDAR system (e.g., the signal processing unit 112 of the LIDAR system 100 shown in fig. 1) may perform IQ processing on a return signal by generating a quadrature signal and an in-phase signal from the return signal. The quadrature signal may be offset 90 degrees relative to the in-phase signal. The LIDAR system may generate an in-phase signal by shifting the return signal down a corresponding transmitted signal (e.g., a local copy of the transmitted signal). For example, the mixing module may receive the return signal and the corresponding transmit signal and downshift the return signal with the corresponding transmit signal. The LIDAR system may generate the quadrature signal by downshifting the return signal by a 90 degree phase-shifted version of the corresponding transmit signal (e.g., phase-shifting the corresponding transmit signal by 90 degrees). For example, another mixing module may receive the return signal and a 90 degree phase shifted version of the corresponding transmit signal and may downshift the return signal through the 90 degree phase shifted version of the corresponding transmit signal. A 90 degree phase shifted version of the corresponding transmit signal may be generated by a phase shifting module, as described in detail below.

In one embodiment, a LIDAR system (e.g., the signal processing unit 112 of the LIDAR system 100 shown in fig. 1) may add (e.g., combine, mix, etc.) in-phase signals and quadrature signals to generate a combined signal. The combined signal may also be referred to as a mixed signal, a summed signal, etc. The LIDAR system may also perform a Fast Fourier Transform (FFT) on the combined signal. For example, the combined signal may be provided to an FFT module, which may perform a fast fourier transform on the combined signal to generate a spectrum of the baseband signal.

In one embodiment, the combined signal may be a complex signal (e.g., a signal including a complex or imaginary component). Since the combined signal is a complex signal, the fast fourier transform of the combined signal may no longer be symmetric. For example, prior to IQ processing, peak 505B (e.g., a shadow peak) may be an exact mirror image of peak 505A (e.g., the amplitude/height of peak 505B would be the same as peak 505A). However, after IQ processing, the amplitude/height of the peak 505B may be reduced, suppressed, minimized, etc., as compared to the amplitude/height of the peak 505A. In another example, peak 510B (e.g., a shadow peak) may be an exact mirror image of peak 510A (e.g., the amplitude/height of peak 510B would be the same as peak 510A) prior to IQ processing. However, after IQ processing, the amplitude/height of peak 510B may be reduced, suppressed, minimized, etc., as compared to the amplitude/height of peak 510A. The combined signal (e.g., complex signal) may be represented as i+ (j x Q), where I is the in-phase signal, Q is the quadrature signal, and j is the imaginary unit.

In one embodiment, if the transmit signal is an up-chirp signal, the LIDAR system (e.g., the signal processing unit 112 of the LIDAR system 100 shown in fig. 1) may combine (e.g., add) the in-phase signal and the quadrature signal by subtracting the quadrature signal from the in-phase signal. For example, if the corresponding transmit signal (for the return signal) has a sweep-up frequency, the LIDAR system may combine the in-phase signal and the quadrature signal by subtracting the signal j Q from the in-phase signal (or adding the negative value of the signal j Q to the in-phase signal).

In one embodiment, if the transmit signal is a down-chirp signal, a LIDAR system (e.g., the signal processing unit 112 of the LIDAR system 100 shown in fig. 1) may combine the in-phase signal and the quadrature signal by adding the quadrature signal to the in-phase signal. For example, if the corresponding transmit signal (for the return signal) has a downshifting frequency, the LIDAR system may add the in-phase signal and the quadrature signal multiplied by j to generate a complex signal.

In one embodiment, a LIDAR system (e.g., the signal processing unit 112 of the LIDAR system 100 shown in fig. 1) may determine one or more of a target location (e.g., a location of a target), a target speed (e.g., a speed of a target), and a target reflectivity (e.g., a reflectivity of a target) using the peaks 505A, 505B, 510A, and 510B. For example, after IQ processing, the amplitude/height of peaks 505B and 510B (e.g., the mapped peaks) may be reduced or suppressed. The LIDAR system may use the peak value of the maximum amplitude/altitude to determine (e.g., calculate) one or more of the position, velocity, and reflectivity of the target. For example, the LIDAR system may select peak 505A from a set of peaks (e.g., a pair of peaks) that includes peaks 505A and 505B. The LIDAR system may also select a peak 510A from a set of peaks (e.g., a pair of peaks) that includes peaks 510A and 510B. The LIDAR system may determine the position, velocity, and reflectivity of the target from the peaks 505A and 510A.

In one embodiment, a LIDAR system (e.g., the signal processing unit 112 of the LIDAR system 100 shown in fig. 1) may subtract the signal j x Q from the up-chirped in-phase signal and add a quadrature signal to the down-chirped in-phase signal to reduce a frequency range that is processed to determine one or more of a target position, a target velocity, and a target reflectivity. If there is no Doppler shift, the beat frequency F of a given chirp _peak Will be equal to the chirp rate (α), multiplied by the delay/time (τ) to the target and back to the LIDAR system. Beat frequency without Doppler shift can be expressed as F _peak =α×τ. For the upper sweep, α will be positive, thus F _peak Will be at positive frequencies and the corresponding mapping peaks will be at negative frequencies. For the down sweep, α will be negative, thus F _peak Will be at negative frequencies and the corresponding mapping peaks will be at positive frequencies. To reduce the frequency range or number processed by the LIDAR system, the combined signal may be determined (e.g., generated, calculated, constructed, etc.) as: i- (j Q) for up-chirp and i+ (j Q) for down-chirp. This may result in all true peaks being at positive frequencies without doppler shift. For example, this may result in the location of peak 510A being at a positive frequency. This may allow the LIDAR system to process (e.g., analyze, scan, etc.) a smaller range or number of frequencies (e.g., positive frequencies) when identifying true peaks (e.g., peaks 505A and 510A). If Doppler shift exists, the beat frequency of the chirp can be expressed as F _peak = |α||τ+d, where D is the doppler shift. Thus, one or more true peaks may be at a negative frequency due to doppler shift. However, for a particular bestLarge Doppler shift D _max The true peak position may be limited to-D _max To 0 or-F _sample 2 to-F _sample /2-D _max Is within the negative frequency range of (2). To reduce the frequency range or number processed by the LIDAR system, the combined signal may be determined (e.g., generated, calculated, constructed, etc.) as: i+ (j x Q) for up-chirp and I- (j x Q) for down-chirp. This may result in all true peaks being at negative frequencies. In the presence of doppler shift, the true peak may be at some positive frequency. LIDAR systems are capable of handling a smaller range or number of frequencies (e.g., negative frequencies) when identifying true peaks (e.g., peaks 505A and 510A).

In one embodiment, a LIDAR system (e.g., the signal processing unit 112 of the LIDAR system 100 shown in fig. 1) may determine whether a target is within one or more sets of ranges where ghosts may occur. For example, referring to fig. 7, the lidar system may determine whether any peaks associated with the target are within a near ghost range (e.g., a frequency range where near range ghosts may occur) or a far ghost range (e.g., a frequency range where far range ghosts may occur). The LIDAR system may use the true peak position and the mapped peak position to determine or estimate whether ghosting is likely to occur (e.g., whether ghosting is likely to occur). If any one of the target frequency peaks is within one or more of the frequency ranges in which ghosting may occur, the LIDAR system may perform IQ processing as described above. If the target is not within one or more of the sets where ghosting may occur, the LIDAR system may refrain from performing IQ processing (e.g., may not perform IQ processing), but instead perform real processing. For example, LIDAR systems may avoid the use of IQ circuits, modules, components, and the like.

In one embodiment, the LIDAR system may change, adjust, modify, etc. the set of frequency ranges in which ghosts may occur based on the speed of the LIDAR system. For example, the LIDAR system may increase/decrease the boundaries of the set of frequency ranges at which ghosts may occur, depending on the speed/velocity (e.g., self-velocity) of the vehicle in which the LIDAR system is located.

Fig. 6 is a block diagram of an exemplary processing module 600 for selecting (e.g., determining, picking, calculating, etc.) a peak value in accordance with the present disclosure. The processing module 600 may be part of a signal processing system of a LIDAR system. For example, the processing module 600 may be part of the signal processing system 303 of the LIDAR system 300 as shown in fig. 3A and 4. In another example, the processing module 600 may be part of the signal processing apparatus 112 shown in fig. 1. As another example, portions of processing module 600 may be included in time domain processor 402 and DFT processor 404 of signal processing system 303 as shown in fig. 4. The processing modules include a mixing module 601, a mixing module 602, an offset module 611, an analog-to-digital converter (ADC) 621, an ADC622, a mixing module 631, a combining module 641, and an FFT module 651. Each of the mixing module 601, the mixing module 602, the offset module 611, the ADC621, the ADC622, the mixing module 631, the combining module 641, and the FFT module 651 may be hardware, software, firmware, or a combination thereof.

As described above, the processing module 600 may receive a return signal (e.g., the target return signal 202 shown in fig. 2) and may provide the return signal to the mixing module 601 and the mixing module 602. The mixing module 601 may mix, shift, downshift, etc., the return signal by transmitting a signal (corresponding to the return signal) to generate a downshift signal 605. The downshifted signal 605 may be provided to an ADC621, and the ADC621 may generate an in-phase signal (I) from the downshifted signal 605.

The offset module 611 may offset the transmit signal by 90 degrees and may provide the transmit signal offset by 90 degrees to the mixing module 602. The mixing module 602 may mix, shift, downshift, etc., the return signal with the transmit signal shifted by 90 degrees to generate a downshift signal 606. The downshifted signal 606 may be provided to an ADC622, and the ADC622 may generate a quadrature signal (Q) from the downshifted signal 606. The quadrature signals are provided to a mixing module 631. The mixing module 631 also receives complex or imaginary components j. The mixing module 631 may mix the quadrature signal Q and the imaginary component j to generate a signal j x Q.

The in-phase signal I and the signal j x Q are provided to a combining block 641 that combines the in-phase signal I and the signal j x Q to generate a combined signal (i+ (j x Q)). The combined signal i+ (j Q) is provided to an FFT module 651 which performs an FFT on the combined signal i+ (j Q) to generate a baseband signal.

As described above, the FFT of the combined signal i+ (j x Q) may no longer be symmetrical, as the combined signal i+ (j x Q) is a complex signal. After FFT of the combined signal, the magnitude/height of the image peak may be reduced, suppressed, minimized, etc. as compared to the magnitude/height of the true peak. This allows the LIDAR system to more easily, quickly, efficiently (etc.) identify true peaks.

Also as described above, the LIDAR system may determine whether a frequency peak associated with the target is within one or more sets of frequency ranges in which ghosting may occur. If the target is not within one or more of the sets of possible ghost images, the LIDAR system may refrain from performing IQ processing (e.g., may not perform IQ processing). For example, the LIDAR system may power down or avoid the use of the mixing module 602, the offset module 611, the ADC622, and the mixing module 631.

Fig. 7A is a signal amplitude versus frequency plot 700 illustrating a frequency range in accordance with the present invention. Frequency 0 (e.g., 0 hertz, 0 terahertz, etc.) is shown in signal amplitude versus frequency plot 700. Frequency D is also shown in signal amplitude versus frequency plot 700 _MAX,DN 。D _MAX,DN May be a maximum or threshold negative doppler shift that the LIDAR system may be capable of considering when detecting an object (e.g., a doppler shift that occurs when an object is moving away from the LIDAR system). Reference is also made to the signal amplitude versus frequency plot 700 to D _MAX,UP 。D _MAX,UP May be a maximum or threshold positive doppler shift that the LIDAR system may be capable of considering when detecting an object (e.g., a doppler shift that occurs when an object is moving toward the LIDAR system). The nyquist frequency F is also shown in the signal amplitude-frequency plot 700 _NYQUIST . In addition, frequency F is also shown in signal amplitude versus frequency plot 700 _NYQUIST- D _MAX,UP 。

0 and D _MAX,DN The frequency range in between may be a first frequency range in which closer/near range ghosting may occur. F (F) _NYQUIST- D _MAX,UP And F _NYQUIST The frequency range in between may be a second frequency range in which far range ghosts may occur. D (D) _MAX,DN And F _NYQUIST- D _MAX,UP The frequency range between may be notA third frequency range in which ghosting occurs.

To determine whether near/more near range or far range ghosts are likely to occur, the LIDAR may analyze the detected peaks. In some embodiments, if the positive peak of the first chirp/sweep is less than D _MAX,DN And the positive peak value of the second chirp/sweep is less than 2*D _MAX,DN Then near-range ghost mitigation may be applied. In other embodiments, if the positive peak of the first chirp/sweep is greater than F _NYQUIST -D _MAX,UP And the positive peak value of the second chirp/sweep is greater than (F _NYQUIST –(2*D _MAX,UP ) A far-range ghost mitigation may be applied. In a further embodiment, if both positive peaks are in the range (D _MAX,DN ,F _NYQUIST -D _MAX,UP ) In that, ghost mitigation may not need to be applied (e.g., IQ processing need not be applied).

In some embodiments, instead of detecting peaks to determine whether closer range or far range ghost mitigation should be used, LIDAR may use energy detection. For example, peak detection may use more computing resources (e.g., processing resources, processing capacity, processing power) and/or memory. Peak detection may also require more time to perform. Detecting not peaks but the total amount of energy in the frequency range (e.g., energy detection) may enable the LIDAR to more quickly and/or efficiently determine which type of ghost mitigation should be used.

Fig. 7B is a signal amplitude versus frequency plot 750 illustrating a frequency range in accordance with the present invention. The frequency 0 (e.g., 0 hertz, 0 terahertz, etc.) is shown in the signal amplitude versus frequency plot 700. Also shown in signal amplitude versus frequency plot 750 is frequency-F _NYQUIST 、-F _NYQUIST +D _MAX,UP 、-D _MAX,DN And F _NYQUIST 。D _MAX May be a maximum or threshold doppler shift that the LIDAR system is capable of considering when detecting an object (e.g., a doppler shift that occurs when the object is moving away from the LIDAR system).

As described above, the combined signal may be determined (e.g., generated, calculated, constructed, etc.) as: i- (j x Q) for up-chirp and i+ (j x Q) for down-chirp to reduce the frequency range or number of LIDAR system processes. This may result in all true peaks being at positive frequencies without doppler shift. When the true peak is at a positive frequency, the LIDAR system may only scan for peaks at positive frequencies (e.g., may not scan for peaks at negative frequencies). Alternatively, the combined signal may be determined as: i+ (j x Q) for up-chirp and I- (j x Q) for down-chirp. This may result in all true peaks being at negative frequencies. When the true peak is at a negative frequency, the LIDAR system may only scan for peaks at negative frequencies (e.g., may not scan for peaks at positive frequencies).

In the absence of a doppler shift where the true peak is forced to be at a positive frequency, the presence of a doppler shift may cause the peak to move to a negative frequency. If near-range ghosting occurs, the true peak may be at-D _MAX,DN And 0. LIDAR system scannable-D _MAX,DN And 0. If a far range ghost occurs, the true peak may be at F _NYQUIST And (F) _NYQUIST +D _MAX ) In the frequency range between. This will alias (aliased) to-F _NYQUIST To (-F) _NYQUIST +D _MAX,UP ) Within a range of (2). LIDAR systems may be at-F _NYQUIST and-F _NYQUIST+ D _MAX,UP Scanning the true peak in the frequency range in between. True peak cannot be found at frequency- (F) _NYQUIST -DMAX, UP) and-D _MAX,DN Is positioned therebetween. The LIDAR system may not be able to scan- (F) _NYQUIST -D _MAX,UP ) and-D _MAX,DN Frequency ranges therebetween. By analysing certain frequency ranges (e.g. at F _NYQUIST And (F) _NYQUIST +D _MAX,UP ) Between) while avoiding analysis of other frequency ranges (e.g., at (F) _NYQUIST +D _MAX,UP ) and-D _MAX,DN In between), the LIDAR system may identify true peaks faster and/or more efficiently (e.g., using less energy or processing power). In the absence of a doppler shift, where the true peak is forced to a negative frequency, the presence of the doppler shift can still shift the peak to a positive frequency.

Fig. 8 is a flow chart illustrating a method 800 in a LIDAR system (such as the LIDAR system 100 or the LIDAR system 300) for selecting peaks according to the present disclosure. The method 800 may be performed by processing logic that may comprise hardware (e.g., circuitry, dedicated logic, programmable logic, a processor, a processing device, a Central Processing Unit (CPU), a system-on-a-chip (SoC), etc.), software (e.g., instructions run/executed on a processing device), firmware (e.g., microcode), or a combination thereof. In some embodiments, the method 800 may be performed by a signal processing system of a LIDAR system (e.g., the signal processing system 303 of the LIDAR system 300 shown in fig. 3A and 4).

The method 800 begins at operation 805, where processing logic transmits one or more light beams including up-chirped frequency modulation and down-chirped frequency modulation to a target in a field of view of a light detection and ranging (LIDAR) system at operation 805. Alternatively, processing logic may introduce phase modulation into one or more beams. At operation 810, processing logic receives one or more return signals for the up-chirp and the down-chirp reflected from the target.

Processing logic may determine whether the target peak is within one or more ghost ranges (e.g., whether within a distance where far range ghosts or near range ghosts may occur) at block 815. If the target is not within the one or more ghost ranges, processing logic may determine the target location from the baseband signal at operation 825, as discussed above in fig. 5. Processing logic may also selectively set, determine, adjust, change, etc., the ghost range in operation 815 based on the speed of the LIDAR system.

If the target is within one or more ghosts, processing logic may perform IQ processing at block 820, as discussed above in fig. 5. For example, processing logic may generate an in-phase signal and a quadrature signal, combine the quadrature signal with an imaginary unit (e.g., j), perform an FFT on the combined signal, and so on. IQ processing may reduce, suppress, etc. the magnitude/height of the image peak in the baseband signal. At block 825, processing logic may determine a target location based on the peak value (e.g., true peak value) of the maximum amplitude/height in the baseband signal.

The foregoing description sets forth numerous specific details, such as examples of specific systems, components, methods, etc., in order to provide a thorough understanding of several examples in the present disclosure. It will be apparent, however, to one skilled in the art that at least some examples of the present disclosure may be practiced without these specific details. In other instances, well-known components or methods have not been described in detail or are presented in simple block diagram form in order to avoid unnecessarily obscuring the present disclosure. Therefore, the specific details set forth are merely exemplary. Specific examples may vary from these exemplary details and are still contemplated to be within the scope of the present disclosure.

Any reference in this specification to "one example" or "an example" means that a particular feature, structure, or characteristic described in connection with the example is included in at least one example. Thus, the appearances of the phrase "in one example" or "in an example" in various places in the specification are not necessarily all referring to the same example.

Although the operations of the methods are illustrated and described herein in a particular order, the order of the operations of the various methods may be altered so that certain operations may be performed in an inverse order or so that certain operations may be performed at least partially concurrently with other operations. The instructions or sub-operations of the different operations may be performed in an intermittent or alternating manner.

The above description of illustrated embodiments of the invention, including what is described in the abstract, is not intended to be exhaustive or to limit the invention to the precise forms disclosed. Although specific embodiments of, and examples for, the invention are described herein for illustrative purposes, various equivalent modifications are possible within the scope of the invention, as those skilled in the relevant art will recognize. The words "example" or "exemplary" are used herein to mean serving as an example, instance, or illustration. Any aspect or design described herein as "example" or "exemplary" is not necessarily to be construed as preferred or advantageous over other aspects or designs. Rather, use of the word "example" or "exemplary" is intended to present concepts in a concrete fashion. As used in this application, the term "or" is intended to mean an inclusive "or" rather than an exclusive "or". That is, unless otherwise indicated or clear from the context, "X includes a or B" is intended to mean any natural inclusive permutation. That is, if X includes A; x comprises B; or X includes both A and B, then "X includes A or B" is satisfied under any of the foregoing instances. In addition, the articles "a" and "an" as used in this application and the appended claims should generally be construed to mean "one or more than one" unless specified otherwise or clear from context to be directed to a singular form. Furthermore, as used herein, the terms "first," "second," "third," "fourth," and the like, mean labels for distinguishing between different elements and may not necessarily have a sequential meaning according to their numerical designation.

Claims (20)

1. A method, comprising:

transmitting one or more light beams to a target in a field of view of a light detection and ranging (LIDAR) system, the one or more light beams comprising at least one up-chirp frequency and at least one down-chirp frequency;

receiving a set of return signals from the target based on the one or more light beams;

determining whether a peak associated with the target is within one or more sets of frequency ranges, the one or more sets of frequency ranges including signal attribute values corresponding to a lower likelihood of accurately calculating a position or velocity of the target;

performing in-phase quadrature phase (IQ) processing on one or more received signals if the peaks associated with the target are within the one or more sets of frequency ranges, wherein the IQ processing reduces one or more magnitudes of one or more of the peaks associated with the target; and

one or more of a target position, a target velocity, and a target reflectivity are determined using the peak associated with the target.

2. The method of claim 1, wherein,

the peaks associated with the target include a first set of peaks and a second set of peaks;

The first set of peaks includes a first true peak and a first mapped peak;

the second set of peaks includes a second true peak and a second mapped peak; and is also provided with

The IQ processing reduces a first magnitude of the first mapped peak and a second magnitude of the second mapped peak.

3. The method of claim 2, wherein determining a target location using the first set of peaks and the second set of peaks comprises:

selecting the first true peak from the first set of peaks and the second true peak from the second set of peaks; and

a target location is determined based on the first true peak and the second true peak.

4. The method of claim 1, wherein the one or more sets of frequency ranges are based on a self-velocity of the LIDAR system.

5. The method of claim 1, wherein performing IQ processing comprises:

generating a first signal and a second signal based on the set of return signals, wherein the first signal is offset from the second signal by 90 degrees;

generating a third signal, wherein the third signal comprises a combination of the first signal and imaginary units; and

the third signal and the second signal are combined to generate a combined signal.

6. The method of claim 5, wherein performing IQ processing further comprises:

and performing fast fourier transform on the combined signal.

7. The method of claim 5, wherein combining the third signal and the second signal comprises:

subtracting the third signal from the second signal for up-chirp, and adding the third signal to the second signal for down-chirp; or (b)

For up-chirp, the third signal is added to the second signal, and for down-chirp, the third signal is subtracted from the second signal.

8. The method of claim 7, wherein subtracting a third signal from the second signal for up-chirp and adding the third signal to the second signal for down-chirp reduces a frequency range that is processed to determine one or more of a target position, a target velocity, and a target reflectivity.

9. The method of claim 1, further comprising:

if the peak associated with the target is not within the one or more sets of frequency ranges, then use of an in-phase quadrature phase (IQ) circuit is avoided.

10. A light detection and ranging (LIDAR) system, comprising:

an optical scanner for transmitting one or more light beams comprising at least one up-chirp frequency and at least one down-chirp frequency to a target in a field of view of the LIDAR system and receiving a set of return signals based on the one or more light beams;

an optical processing system coupled with the optical scanner for generating a baseband signal in the time domain from the return signal, the baseband signal including a frequency corresponding to a LIDAR target range; and

a signal processing system coupled to the optical processing system, comprising:

a processing device; and

a memory for storing instructions that, when executed by the processing device, cause the LIDAR system to:

determining whether a peak associated with the target is within one or more sets of frequency ranges, the one or more sets of frequency ranges including signal attribute values corresponding to a lower likelihood of accurately calculating a position or velocity of the target;

performing an in-phase quadrature phase (IQ) process on the one or more received signals if the peak associated with the target is within the one or more sets of frequency ranges, wherein the IQ process reduces one or more magnitudes of one or more of the peak associated with the target; and

One or more of a target position, a target velocity, and a target reflectivity are determined using the peak associated with the target.

11. The LIDAR system of claim 10, wherein,

the peaks associated with the target include a first set of peaks and a second set of peaks;

the first set of peaks includes a first true peak and a first mapped peak;

the second set of peaks includes a second true peak and a second mapped peak; and is also provided with

The IQ processing reduces a first magnitude of the first mapped peak and a second magnitude of the second mapped peak.

12. The LIDAR system of claim 11, wherein to determine a target location using the first set of peaks and the second set of peaks, the LIDAR system is further to:

selecting the first true peak from the first set of peaks and the second true peak from the second set of peaks; and

and determining a target position according to the first true peak value and the second true peak value.

13. The LIDAR system of claim 10, wherein the one or more sets of frequency ranges vary according to a self-velocity of the LIDAR system.

14. The LIDAR system of claim 10, wherein to perform IQ processing, the LIDAR system is further to:

Generating a first signal and a second signal based on the set of return signals, wherein the first signal is offset from the second signal by 90 degrees;

generating a third signal, wherein the third signal comprises a combination of the first signal and imaginary units; and

the third signal and the second signal are combined to generate a combined signal.

15. The LIDAR system of claim 14, wherein to perform IQ processing, the LIDAR system is further to:

and performing fast fourier transform on the combined signal.

16. The LIDAR system of claim 14, wherein to combine the third signal and the second signal, the LIDAR system is further to:

subtracting the third signal from the second signal for up-chirp, and adding the third signal to the second signal for down-chirp; or (b)

For up-chirp, the third signal is added to the second signal, and for down-chirp, the third signal is subtracted from the second signal.

17. The LIDAR system of claim 16, wherein subtracting the third signal from the second signal for up-chirp and adding the third signal to the second signal for down-chirp reduces a frequency range that is processed to determine one or more of a target location, a target velocity, and a target reflectivity.

18. The LIDAR system of claim 10, wherein the LIDAR system is further configured to:

if the peak associated with the target is not within the one or more sets of frequency ranges, then use of an in-phase quadrature phase (IQ) circuit is avoided.

19. A light detection and ranging (LIDAR) system, the system comprising:

a processor; and

a memory for storing instructions that, when executed by the processor, cause the LIDAR system to:

transmitting one or more light beams to a target in a field of view of the LIDAR system, the one or more light beams comprising at least one up-chirp frequency and at least one down-chirp frequency;

receiving a set of return signals from the target based on the one or more light beams;

determining whether a peak associated with the target is within one or more sets of frequency ranges, the one or more sets of frequency ranges including signal attribute values corresponding to a lower likelihood of accurately calculating a position or velocity of the target;

performing in-phase quadrature phase (IQ) processing on one or more received signals if the peaks associated with the target are within the one or more sets of frequency ranges, wherein the IQ processing reduces one or more magnitudes of one or more of the peaks associated with the target; and

One or more of a target position, a target velocity, and a target reflectivity are determined using the peak associated with the target.

20. The LIDAR system of claim 19, wherein,

the peaks associated with the target include a first set of peaks and a second set of peaks;

the first set of peaks includes a first true peak and a first mapped peak;

the second set of peaks includes a second true peak and a second mapped peak; and is also provided with

The IQ processing reduces a first magnitude of the first mapped peak and a second magnitude of the second mapped peak.