Geiger-Mode LiDAR Clock-Skew Search for Accurate Depth Histograms
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Solution Overview
Problem
Lidar systems face limitations in distance measurement accuracy due to binning constraints imposed by clock inaccuracy, leading to errors in determining the location of objects.
Innovation Solution
Introduce a clock drift modeled by an analytical function to assign results to bins, perform fitting and interpolation operations on the histogram, and adjust the peak based on the introduced clock drift to enhance accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If binning is used to group photodetector results based on clock time, then processing efficiency is improved, but measurement precision deteriorates due to clock inaccuracy and bin width limitations
Solution Approach 1:
The patent changes the time parameter by introducing a variable time offset (clock drift) that varies across different bins. Instead of using a fixed clock time for all bins, each bin is assigned a time value that includes a drift component proportional to the bin index. This parameter change allows the system to maintain binning for efficiency while compensating for clock inaccuracies, thereby preserving measurement precision.
Solution Approach 2:
The patent implements a feedback mechanism where the histogram peak detection process informs the adjustment of time offsets for subsequent measurements. By continuously detecting the peak position and using it to refine the clock drift model, the system compensates for accumulated timing errors. This feedback loop ensures that distance measurement accuracy is maintained despite the use of binning for efficient data processing.
2Device complexity
If a fixed clock is used for assigning results to bins, then device complexity is reduced, but measurement precision deteriorates due to clock skew and timing errors
Solution Approach 1:
Instead of using a fixed clock time, the patent introduces a dynamic time offset parameter that varies with each bin. The time value for each bin is calculated as T[i] = T0 + i × Δt, where T0 is the base time, i is the bin index, and Δt is the time step. This parameter change allows the system to maintain a relatively simple clock structure while achieving accurate time-of-flight measurements by compensating for clock skew through the variable offset.
Solution Approach 2:
The patent performs preliminary action by pre-calculating and storing the time offsets for all bins before the actual measurement process. The clock drift model is established in advance, and the time values T[i] are computed beforehand. This preliminary preparation allows the system to use a simple fixed clock during measurement while still achieving high precision through the pre-computed time offsets that account for expected clock behavior.
3Reliability
If bin width is increased to reduce noise, then measurement reliability is improved, but measurement precision deteriorates due to larger time quantization errors
Solution Approach 1:
The patent changes the time parameter by introducing a variable offset that increases with bin index. Even with fixed bin widths, the effective time resolution is improved because the variable offset compensates for clock drift. This allows the system to use wider bins for noise reduction while maintaining distance resolution through the compensating time offset model.
Solution Approach 2:
The feedback mechanism refines the peak detection by using the histogram shape and distribution to correct for bin width effects. By analyzing the peak position relative to bin centers and using curve fitting or interpolation on the histogram data, the system can achieve sub-bin resolution. This feedback-based refinement allows wider bins to be used without sacrificing measurement precision.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Improves distance measurement accuracy by reducing errors from binning limitations, allowing for more precise estimation of object locations.
Implementation Method 1
obtaining, by a processor, results produced by photodetectors of the lidar system in response to light pulses arriving at the photodetectors
Data Source
AI summary
Disclosed herein are systems, methods, and computer program products to improve the accuracy of range measurements of 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 operations to fit the histogram to the analytical function a derived function of the analytical function; and identifying, by the processor, a peak of the histogram based on results of the fitting operations.