LIDAR window blockage detection

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

an optical scanner to transmit an optical beam through a LIDAR window and receive a return signal from reflections of the optical beam;

an optical processing system to generate a range-dependent baseband signal corresponding to the return signal; wherein the optical processing system comprises:

an optical source to generate a frequency modulated continuous wave (FMCW) optical beam;

an optical coupler to receive the FMCW optical beam from the optical source;

a polarization beam splitter (PBS) coupled with the optical coupler, to direct the FMCW optical beam to the optical scanner and to receive the return signal from the optical scanner; and

a photodetector (PD) to receive the return signal from the PBS, and a sample of the FMCW optical beam from the optical coupler, the PD to generate the range-dependent baseband signal from spatial mixing of the return signal with the sample of the FMCW optical beam; and

a signal processing system comprising:

a processor;

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

determine whether the return signal is caused by an obstruction on or proximate to the LIDAR window,

determine operational effects of the obstruction on the LIDAR system, and

mitigate the operational effects of the obstruction, and

a frequency compensation processor coupled to a peak search engine to correct for Doppler scanning artifacts; and

a post-processor coupled to the frequency compensation processor to generate a FOV reflectivity map and a LIDAR window health report.

2. The LIDAR system of claim 1 , wherein to determine whether the return signal is caused by an obstruction on the LIDAR window, the processor further causes the LIDAR system to detect frequencies in the range-dependent baseband signal that are less than a threshold frequency.

3. The LIDAR system of claim 2 , wherein to determine the operational effects of the obstruction, the processor further causes the LIDAR system to generate the reflectivity map to identify an obstructed field of view (FOV) and energy reflected by the obstruction.

4. The LIDAR system of claim 3 , wherein the signal processing system is further to analyze the reflectivity map of the FOV to determine whether the obstructed FOV is a safety critical FOV, and to determine whether a maximum detection range is less than a minimum safety critical detection range.

5. The LIDAR system of claim 4 , wherein the LIDAR system comprises a vehicle-mounted system, wherein the signal processing system is to mitigate the operational effects of the obstruction by one or more commands to slow the vehicle, to park the vehicle, and to clean the LIDAR window.

6. The LIDAR system of claim 2 , wherein the signal processing system comprises:

a sampler coupled with the optical processing system to generate time domain samples of the range-dependent baseband signal;

a discrete Fourier transform (DFT) processor coupled to the sampler to transform the time domain samples into the frequency domain; and

wherein the peak search processor is coupled to the DFT processor to search for energy peaks at frequencies that are less than the threshold frequency.

7. A method in a light detection and ranging (LIDAR) system, comprising:

generating a range-dependent baseband signal corresponding to a return signal, wherein generating comprises:

receiving a sample of a frequency modulated continuous wave (FMCW) optical beam;

receiving the return signal; and

spatial mixing the return signal with the sample of the FMCW optical beam;

detecting an obstruction on or proximate to a LIDAR window from a LIDAR return signal;

determining an operational effect of the window obstruction on the LIDAR system, wherein determining the operational effect of the window obstruction comprises:

generating a reflectivity map of a field of view (FOV) of the LIDAR system; and

analyzing the reflectivity map by identifying an obstructed FOV of the LIDAR system and determining a reflected energy from the obstructed FOV;

mitigating the operational effect of the window obstruction on the LIDAR system;

correcting for Doppler scanning artifacts; and

generating a FOV reflectivity map and a LIDAR window health report.

8. The method of claim 7 , wherein detecting the obstruction comprises:

generating a range-dependent baseband signal from the LIDAR return signal; and

detecting frequencies in the range-dependent baseband signal that are less than a threshold frequency corresponding to ranges at or proximate to the LIDAR window.

9. The method of claim 8 , wherein detecting frequencies in the range-dependent baseband signal that are less than the threshold frequency comprises:

sampling the range-dependent baseband signal in the time domain;

transforming the time domain samples into the frequency domain; and

searching for frequency domain energy peaks at frequencies that are less than the threshold frequency.

10. The method of claim 7 , further comprising:

determining whether the obstructed FOV is a safety critical FOV; and

determining whether the maximum detection range is less than a minimum safety critical detection range.

11. The method of claim 7 , wherein the LIDAR system comprises a vehicle-mounted LIDAR system, wherein mitigating the operational effect of the window obstruction comprises at least one of slowing the vehicle, parking the vehicle, and cleaning the LIDAR window.

12. A non-transitory computer-readable medium containing instructions that, when executed by a processor in a LIDAR system, cause the LIDAR system to:

generate a range-dependent baseband signal corresponding to a return signal by causing the LIDAR system to:

receive a sample of a frequency modulated continuous wave (FMCW) optical beam;

receive the return signal; and

spatial mix the return signal with the sample of the FMCW optical beam;

detect an obstruction on or proximate to a LIDAR window from a LIDAR return signal;

determine an operational effect of the LIDAR window obstruction on the LIDAR system, wherein to determine the operational effect of the LIDAR window obstruction, the LIDAR system to:

generate a reflectivity map of a field of view (FOV) of the LIDAR system; and

analyze the reflectivity map to determine an obstructed FOV of the LIDAR system and to determine a reflected energy from the obstructed FOV;

mitigate the operational effect of the LIDAR window obstruction on the LIDAR system;

correct for Doppler scanning artifacts; and

generate a FOV reflectivity map and a LIDAR window health report.

13. The computer-readable memory of claim 12 , wherein to detect the LIDAR window obstruction, the LIDAR system is further to:

generate a range-dependent baseband signal from the LIDAR return signal; and

detect frequencies in the range-dependent baseband signal that are less than a threshold frequency corresponding to ranges at or proximate to the LIDAR window.

14. The computer-readable memory of claim 13 , wherein to detect frequencies in the range-dependent baseband signal that are less than the threshold frequency, the LIDAR system is further to:

sample the range-dependent baseband signal in the time domain;

transform time domain samples into the frequency domain; and

search for frequency domain peaks at frequencies that are less than the threshold frequency.

15. The computer-readable memory of claim 12 , wherein the LIDAR system is further to:

determine whether the obstructed FOV is a safety critical FOV; and

determine whether the maximum detection range is less than a minimum safety critical detection range.

16. The computer-readable memory of claim 12 , wherein the LIDAR system comprises a vehicle-mounted system, wherein to mitigate the operational effect of the LIDAR window obstruction, the LIDAR system is instructed to slow the vehicle, park the vehicle, or clean the LIDAR window.