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US-20260126552-A1 - SYSTEMS AND METHODS FOR CLOCK-SKEW SEARCH TO IMPROVE DEPTH ACCURACY IN GEIGER MODE LIDAR

US20260126552A1US 20260126552 A1US20260126552 A1US 20260126552A1US-20260126552-A1

Abstract

A method for operating a lidar system including obtaining, by a processor, a plurality of detection results from a photodetector, applying an intentional temporal modulation to a timing reference of the lidar system according to a predefined pattern, generating a data distribution by combining the detection results based on the timing reference affected by the temporal modulation, and determining a signal peak from the data distribution using characteristics of the predefined pattern, wherein the signal peak is resolved at a resolution finer than a unit timing resolution of the timing reference.

Inventors

  • Yahia Tachwali
  • Michael SCHOENBERG

Assignees

  • LG INNOTEK CO., LTD.

Dates

Publication Date
20260507
Application Date
20251230

Claims (20)

  1. 1 . A method for operating a lidar system, comprising: obtaining, by a processor, a plurality of detection results from a photodetector; applying an intentional temporal modulation to a timing reference of the lidar system according to a predefined pattern; generating a data distribution by combining the detection results based on the timing reference affected by the temporal modulation; and determining a signal peak from the data distribution using characteristics of the predefined pattern, wherein the signal peak is resolved at a resolution finer than a unit timing resolution of the timing reference.
  2. 2 . The method of claim 1 , further comprising adjusting the signal peak based on an average time delay introduced into the timing reference by the temporal modulation.
  3. 3 . The method of claim 1 , wherein the predefined pattern comprises a ramp function, a sawtooth function, or a sine wave function.
  4. 4 . The method of claim 1 , wherein the temporal modulation is configured to cause the detection results from the photodetector to be spread across multiple bins.
  5. 5 . The method of claim 1 , wherein generating the data distribution comprises utilizing both a first timing reference affected by the temporal modulation and a second timing reference without the temporal modulation to reduce a required number of returns.
  6. 6 . The method of claim 1 , wherein determining the signal peak comprises applying an optimization algorithm that utilizes higher-order derivatives of the predefined pattern to the data distribution.
  7. 7 . The method of claim 1 , further comprising generating a trajectory or a control command for an autonomous vehicle based on a distance calculated from the determined signal peak.
  8. 8 . A lidar system, comprising: a processor; and a non-transitory computer-readable storage medium storing programming instructions configured to cause the processor to perform operations comprising: obtaining a plurality of detection results from a photodetector; applying an intentional temporal modulation to a timing reference of the lidar system according to a predefined pattern; generating a data distribution by combining the detection results based on the timing reference affected by the temporal modulation; and determining a signal peak from the data distribution using characteristics of the predefined pattern, wherein the signal peak is resolved at a resolution finer than a unit timing resolution of the timing reference.
  9. 9 . The lidar system of claim 8 , the operations further comprising adjusting the peak based on an average time delay introduced into the timing reference by the temporal modulation.
  10. 10 . The lidar system of claim 8 , wherein the predefined pattern comprises a ramp function, a sawtooth function, or a sine wave function.
  11. 11 . The lidar system of claim 8 , wherein the predefined pattern comprises at least one of a first parameter defined by a time that light is emitted from the lidar system and a second parameter defined by an avalanche time of a photodetector.
  12. 12 . The lidar system of claim 8 , wherein the temporal modulation is implemented by adding delay logic to a photon emission measurement or by an electrical component positioned at a photon reception point to produce a periodic timing variation.
  13. 13 . The lidar system of claim 8 , the operations further comprising dynamically adjusting an amplitude or a width of the temporal modulation based on a geometric complexity of a scene being measured.
  14. 14 . The lidar system of claim 8 , the operations further comprising utilizing two independent clocks to achieve the data distribution with half of a required number of returns.
  15. 15 . A non-transitory computer-readable medium storing instructions that, when executed by at least one computing device, cause the at least one computing device to perform operations comprising: obtaining a plurality of detection results produced by photodetectors of a lidar system in response to light pulses; applying an intentional temporal modulation to a timing reference according to a predefined pattern; generating a data distribution by combining the detection results based on the timing reference affected by the temporal modulation; and determining a signal peak from the data distribution using characteristics of the predefined pattern to resolve the signal peak at a resolution finer than a unit timing resolution of the timing reference.
  16. 16 . The medium of claim 15 , wherein the temporal modulation is configured to cause the detection results from the photodetectors to be spread across multiple bins.
  17. 17 . The medium of claim 15 , wherein the detection results are assigned to bins based on distances corresponding to associated times at which the light pulses arrived at the photodetectors.
  18. 18 . The medium of claim 15 , the operations further comprising controlling operations of an autonomous vehicle based on the peak.
  19. 19 . The medium of claim 15 , wherein determining the signal peak comprises applying a recovery model incorporating an inverse function or a derivative of the predefined pattern into a peak recovery logic.
  20. 20 . The medium of claim 15 , the operations further comprising utilizing a subset of returns to compensate for scene-dependent effects or noise in the data distribution.

Description

CROSS-REFERENCE TO RELATED APPLICATIONS This application is a Continuation of application Ser. No. 17/823,541, filed on Aug. 31, 2022, the entire contents of which is hereby expressly incorporated by reference into the present application. BACKGROUND Light detecting and ranging (lidar) systems are used in various applications. One application for lidar systems is autonomous vehicles (AVs). AVs may use lidar systems to measure the distance from the AV to surrounding objects. To accomplish this task, the lidar system illuminates an object with light and measures the reflected light with a sensor. The reflected light is used to determine features of the object that reflected it and to determine the distance the object is from the AV. Lidar systems also may be used in other applications, such as in aircraft, ships and/or mapping systems. SUMMARY The present disclosure concerns implementing systems and methods for operating a lidar system. The methods comprise: obtaining, by a processor, results produced by photodetectors of the lidar system in response to light pulses arriving at the photodetectors over time; introducing a clock drift into a clock of the lidar system, the clock drift being modeled by an analytical function; assigning, by the processor, the results to bins based on associated times at which the light pulses arrived at the photodetectors as specified by the clock; building, by the processor, a histogram using the results which have been assigned to the bins; performing, by the processor, fitting, curve fitting and/or interpolation operations to fit the histogram to the analytical function or a derived function of the analytical function (such as an inverse or derivative of the analytical function if such exists); and identifying, by the processor, a peak of the histogram based on results of the fitting, curve fitting and/or interpolation operations. The implementing systems can comprise: a processor; and a non-transitory computer-readable storage medium comprising programming instructions that are configured to cause the processor to implement a method for operating a lidar system. The above-described methods can also be implemented by a computer program product comprising memory and programming instructions that are configured to cause a processor to perform operations. BRIEF DESCRIPTION OF THE DRAWINGS The accompanying drawings are incorporated herein and form a part of the specification. FIG. 1 provides an illustration of a lidar system. FIG. 2 provides an illustration showing results from photodetectors of the lidar system shown in FIG. 1. FIG. 3 provides an illustration showing bins to which results from photodetectors of the lidar system shown in FIG. 1 are assigned or otherwise assigned. FIG. 4 shows an illustrative histogram. FIG. 5 shows another illustrative histogram results for adding drift to a clock used for binning results of photodetectors. FIG. 6 provides an illustration showing a function ƒ being fit to the histogram of FIG. 5 for recovering a peak. FIG. 7 provides a flow diagram of a method for operating the lidar system of FIG. 1. FIG. 8 provides an illustration of a system. FIG. 9 provides a more detailed illustration of an autonomous vehicle. FIG. 10 provides an illustration of a computer system. FIG. 11 provides a block diagram of an illustrative vehicle trajectory planning process. In the drawings, like reference numbers generally indicate identical or similar elements. Additionally, generally, the leftmost digit(s) of a reference number identifies the drawing in which the reference number first appears. DETAILED DESCRIPTION In a Geiger mode lidar system, the sensor comprises an avalanche detector (or photodiode) configured to produce an electrical pulse of a given amplitude in response to an absorption of a photon of the same or similar wavelength as the light signal which was emitted. A histogram is then assembled over many trials, and the location of an object's surface is estimated from the peak of the histogram. The term “trial” as used here refers to each measurement attempt. A measurement attempt comprises sending a pulse and recording the detection time. The trial is associated with the measurement, but not necessarily the pulse. There can be multiple trials from a single pulse by grouping the detections from multiple detectors. Each detector output is a measurement. However, the accuracy of the histogram is fundamentally limited by the width of a bin. Binning is required due to technological limitations on the clock accuracy. The binning is performed to group individual results into classes or categories. Even though the bins may be quite small in human terms (for example, under a nanosecond), the bins still limit accuracy of the result. Light travels fifteen centimeters in five hundred picoseconds. In 500 picoseconds, the roundtrip distance would be 15 centimeters. So, the distance measured in one way is 7.5 centimeters. Since the time resolution is set at 500 pic