Adaptive LiDAR Scanning for Long-Range Accuracy and Frame Rate
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Solution Overview
Problem
Conventional LiDAR systems face challenges in achieving reliable and accurate range measurements at long distances due to the need for increased laser power and longer dwell times, which limits their frame rate and efficiency, especially in miniature systems used in automotive applications.
Innovation Solution
A LiDAR system employing a dynamically varying temporal scanning pattern based on distance and reflectivity, using an optical switching network and a controller to route light to optical emitters, allowing for adaptive per-pixel dwell times and independent scanning of different regions within the field of view, thereby optimizing laser power usage and frame rate.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If laser power and dwell time are increased to improve measurement accuracy at long ranges, then measurement precision is improved, but frame rate decreases and system power consumption increases
Solution Approach 1:
The patent applies local quality by assigning different dwell times to different spatial regions of the field of view. Regions requiring high measurement precision (such as areas with objects of interest) receive longer dwell times, while regions with lower priority receive shorter dwell times. This spatially varying dwell time strategy allows the system to maintain high frame rates overall while ensuring accurate measurements where needed, resolving the contradiction between measurement precision and frame rate.
Solution Approach 2:
The patent implements dynamics by making the scanning pattern and dwell times adaptive rather than static. The controller dynamically adjusts the temporal pattern based on detected objects, their distances, and priorities. This allows the system to optimize the balance between measurement precision and frame rate in real-time, allocating laser power and dwell time dynamically to achieve high accuracy at long ranges while maintaining overall system productivity.
2Measurement precision
If laser power is increased to maintain measurement accuracy at long ranges, then measurement precision is improved, but use of energy increases
Solution Approach 1:
The patent applies local quality by concentrating laser power and dwell time only on regions where high measurement precision is required, rather than uniformly across the entire field of view. By identifying specific areas with objects of interest and allocating resources locally to those regions, the system achieves long-range measurement accuracy while significantly reducing overall energy consumption compared to a uniform high-power scanning approach.
Solution Approach 2:
The patent applies partial action by using high laser power and long dwell times only partially, specifically only for regions containing objects of interest rather than for the entire field of view. This selective application of excessive action (high power) to only the necessary portions allows the system to achieve required measurement precision while avoiding unnecessary energy consumption in regions where high accuracy is not needed.
3Measurement precision
If dwell time is increased to improve measurement accuracy, then measurement precision is improved, but revisit frequency decreases
Solution Approach 1:
The patent applies local quality by implementing spatially varying revisit frequencies based on the importance and distance of detected objects. High-priority regions with distant objects receive longer dwell times and lower revisit frequencies, while other regions maintain higher revisit frequencies. This local differentiation allows the system to achieve accurate long-range measurements without sacrificing overall revisit frequency across the entire field of view.
Solution Approach 2:
The patent implements dynamics by making revisit frequencies adaptive rather than uniform. The controller dynamically adjusts revisit frequencies based on object priority, distance, and motion characteristics. This allows the system to allocate longer dwell times selectively to critical long-range targets while maintaining high revisit frequencies for other regions, thereby achieving measurement precision improvement without a system-wide reduction in revisit frequency.
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
This approach minimizes laser power requirements, enhances frame rate, and improves detection accuracy and safety by dynamically adjusting scanning rates and dwell times based on object distance and reflectivity, allowing for efficient detection of moving objects and prioritizing high-interest areas within the scene.
Implementation Method 1
An objective lens optically couples each optical emitter of the array of optical emitters to a respective unique portion of the field of view
Implementation Method 2
An optical receiver is coupled to the optical switching network. The optical receiver is configured to receive light reflected from the field of view
Implementation Method 3
In general, more laser power and/or longer dwell times are required to acquire reliable, accurate range measurements using LiDAR systems at long ranges than at short ranges
Data Source
AI summary
A LiDAR system includes an array of optical emitters, an objective lens optically coupling each optical emitter to a respective unique portion of a field of view, an optical switching network coupled between a laser and the array of optical emitters and a controller coupled to the optical switching network and configured to cause the optical switching network to route light from the laser to a sequence of the optical emitters according to a dynamically varying temporal pattern and to vary the temporal pattern based at least in part on distance to an object within the field of view. The LiDAR system scans different portions of the field of view differently, such as with different laser power levels, different revisit rates and/or different scan patterns, for example based on likelihood of detecting objects of interest in the various portions or based on likely relative importance of objects likely to be found in the various portions.