LiDAR Light-Cover Obstruction Detection Via Stray-Light Echoes
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Solution Overview
Problem
LiDAR systems face accuracy issues due to stray light echoes caused by dirt or obstructions on the light cover, leading to decreased ranging capability, reflectivity, and increased noise in point clouds, which are not effectively addressed by existing methods.
Innovation Solution
A method and apparatus for detecting obstructions using independent detection pulse signals within a ranging time window, determining the presence of obstructions based on feature parameters of stray light echoes, and adjusting thresholds dynamically to improve detection accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the light cover becomes dirty or obstructed, then stray light echo increases causing detection noise, but the obstruction detection accuracy decreases because stray light echo cannot be effectively distinguished from target object echo
Solution Approach 1:
The patent divides the echo detection process into two separate time windows: a first time window for detecting stray light echo (obstruction detection) and a second time window for detecting target object echo (ranging detection). This temporal segmentation allows the system to distinguish between obstruction signals and target signals, resolving the contradiction by preventing stray light echo from interfering with target detection while enabling independent obstruction detection.
2Measurement precision
If a separate detection pulse signal is used for obstruction detection, then obstruction detection accuracy improves, but the system complexity increases
Solution Approach 1:
The patent combines obstruction detection and target detection functions into a single LiDAR system by using two different pulse signals (detection pulse signal for obstruction, probe pulse signal for target) within the same hardware framework. The time window separation strategy allows both functions to operate simultaneously without requiring separate physical detection systems, thus improving obstruction detection accuracy while controlling system complexity through resource sharing.
3Measurement precision
If the probe pulse signal intensity is increased to improve target detection, then ranging capability improves, but stray light echo intensity increases causing more detection noise
Solution Approach 1:
The patent extracts the obstruction detection function from the target detection process by introducing a separate detection pulse signal with lower intensity specifically for obstruction detection. This allows the probe pulse signal to maintain high intensity for accurate target ranging, while the detection pulse signal generates manageable stray light echo levels for obstruction detection, thereby resolving the contradiction between target detection performance and stray light interference.
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
Enhances obstruction detection accuracy by isolating stray light echoes from target object echoes, allowing for precise identification and localization of obstructions without affecting target detection, even in varying environments.
Implementation Method 1
When a light emission apparatus of the LiDAR emits a probe pulse signal, the dirt reflects the probe pulse signal to generate stray light
Implementation Method 2
the light reception apparatus can receive a stray light echo corresponding to the detection pulse signal
Data Source
AI summary
A method for detecting an obstruction includes: a detection pulse signal is emitted for probing the obstruction within a ranging time window; the ranging time window is configured to determine a time of flight between emission of a probe pulse signal for probing a target object and reception of an echo from the target object; a stray light echo corresponding to the detection pulse signal is received; whether the obstruction exists is determined based on a feature parameter of the stray light echo.