Techniques to compensate for mirror Doppler spreading in coherent LiDAR systems using matched filtering
A received signal is sampled at the LiDAR system and the received signal is converted to a frequency domain, where the received signal comprises a first frequency waveform. A matched filter is selected, where the matched filter comprises a second frequency waveform with a set of coefficients to match the first frequency waveform. The set of coefficients are updated according to a set of metrics. The received signal is filtered by the matched filter to generate a filtered received signal. Range and velocity information is extracted from the filtered received signal.
1. A method in a frequency-modulated continuous-wave (FMCW) light detection and ranging (LiDAR) system, comprising:
generating an optical beam from an optical source and transmitting the optical beam to a target;
receiving a return signal from the target based on the optical beam;
sampling the return signal at the LiDAR system and converting the return signal to a frequency domain, wherein the return signal comprises a first frequency waveform;
selecting a matched filter, the match filter comprising a second frequency waveform with a set of coefficients to match the first frequency waveform;
updating the matched filter by updating the set of coefficients of the second frequency waveform according to a set of metrics, wherein the set of metrics include an angular speed of a scanning mirror;
filtering the return signal by the matched filter to generate a filtered return signal; and
extracting range and velocity information from the filtered return signal.
2. The method of claim 1 , wherein selecting a matched filter comprises selecting a rectangular waveform, a sinc waveform, a sinc squared waveform, or a Gaussian waveform to be the second frequency waveform.
3. The method of claim 1 , wherein the set of coefficients are further updated according to at least one of a position of the scanning mirror, a geometry of an optical scanner, or the target.
4. The method of claim 1 , wherein the set of coefficients are updated such that a filter bandwidth of the matched filter is proportional to at least one of an angular speed of a scanning mirror, a scanning mirror size, or a beam diameter.
5. The method of claim 1 , wherein the second frequency waveform is determined based on an estimation of a power spectrum density function of the return signal.
6. The method of claim 1 , wherein the set of coefficients are updated based on a change in a hardware configuration or a system operation including a change of a mirror angular speed or a scan pattern change.
7. The method of claim 1 , further comprising inputting the filtered return signal into a peak selection process to extract the range and velocity information.
8. The method of claim 1 , wherein the second frequency waveform is determined based on a model or a simulation or a measurement of an optical sub-system of the LiDAR system.
9. A frequency-modulated continuous-wave (FMCW) light detection and ranging (LiDAR) system, comprising:
an optical source to generate an optical beam for transmitting towards a target;
a scanning mirror to scan the target;
a photodetector to receive a return signal from the target based on the optical beam;
a memory; and
a processor, operatively coupled with the memory, to:
sample the return signal at the LiDAR system and convert the return signal to a frequency domain, wherein the return signal comprises a first frequency waveform;
select a matched filter, the match filter comprising a second frequency waveform with a set of coefficients to match the first frequency waveform;
update the matched filter by updating the set of coefficients of the second frequency waveform according to a set of metrics, wherein the set of metrics include an angular speed of the scanning mirror;
filter the return signal by the matched filter to generate a filtered return signal; and
extract range and velocity information from the filtered return signal.
10. The LiDAR system of claim 9 , wherein the second frequency waveform comprises a rectangular waveform, a sinc waveform, a sinc squared waveform, or a Gaussian waveform to be the second frequency waveform.
11. The LiDAR system of claim 9 , wherein the set of coefficients are further updated according to at least one of a position of the scanning mirror, a geometry of an optical scanner, or the target.
12. The LiDAR system of claim 9 , wherein the set of coefficients are updated such that a filter bandwidth of the matched filter is proportional to at least one of an angular speed of a scanning mirror, a scanning mirror size, or a beam diameter.
13. The LiDAR system of claim 9 , wherein the second frequency waveform is determined based on an estimation of a power spectrum density function of the return signal.
14. The LiDAR system of claim 9 , wherein the set of coefficients are updated based on a change in a hardware configuration or a system operation including a change of a mirror angular speed or a scan pattern change.
15. The LiDAR system of claim 9 , wherein the processor operatively coupled with the memory is further to input the filtered return signal into a peak selection process to extract the range and velocity information.
16. The LiDAR system of claim 9 , wherein the second frequency waveform is determined based on a model or a simulation or a measurement of an optical sub-system of the LiDAR system.
17. A non-transitory machine-readable medium having instructions stored therein, which when executed by a processor of a light detection and ranging (LiDAR) system, cause the processor to:
generate an optical beam from an optical source and transmit the optical beam to a target;
receive a return signal from the target based on the optical beam;
sample the return signal at the LiDAR system and convert the return signal to a frequency domain, wherein the return signal comprises a first frequency waveform;
select a matched filter, the match filter comprising a second frequency waveform with a set of coefficients to match the first frequency waveform;
update the matched filter by updating the set of coefficients of the second frequency waveform according to a set of metrics, wherein the set of metrics include an angular speed of a scanning mirror;
filter the return signal by the matched filter to generate a filtered return signal; and
extract range and velocity information from the filtered return signal.
18. The non-transitory machine-readable medium of claim 17 , wherein the second frequency waveform comprises a rectangular waveform, a sinc waveform, a sinc squared waveform, or a Gaussian waveform to be the second frequency waveform.
19. The non-transitory machine-readable medium of claim 17 , wherein the set of coefficients are further updated according to a position of the scanning mirror, a geometry of an optical scanner, or the target.
20. The non-transitory machine-readable medium of claim 17 , wherein the set of coefficients are updated such that a filter bandwidth of the matched filter is proportional to at least one of an angular speed of a scanning mirror, a scanning mirror size, or a beam diameter.
21. The non-transitory machine-readable medium of claim 17 , wherein the second frequency waveform is determined based on an estimation of a power spectrum density function of the return signal.
22. The non-transitory machine-readable medium of claim 17 , wherein the set of coefficients are updated based on a change in a hardware configuration or a system operation including a change of a mirror angular speed or a scan pattern change.
23. The non-transitory machine-readable medium of claim 17 , wherein the processor operatively coupled with the memory is further to input the filtered return signal into a peak selection process to extract the range and velocity information.
24. The non-transitory machine-readable medium of claim 17 , wherein the second frequency waveform is determined based on a model or a simulation or a measurement of an optical sub-system of the LiDAR system.