LiDAR Receiving Array Denoising for Position-Dependent Echo Noise
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Solution Overview
Problem
Current denoising methods for LIDAR use a single threshold to remove noise signals, which results in poor denoising effectiveness and affects the ranging accuracy due to varying noise types and echo signal energies across different regions of the receiving array.
Innovation Solution
A denoising method for LIDAR that acquires echo signals, obtains target measurement distance and echo feature information, and sets a target noise point threshold based on pixel position and distance to accurately identify and remove noise signals, using different thresholds for different regions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a single threshold is used to remove noise signals, then the denoising process is simple, but the denoising accuracy deteriorates due to varying noise types and echo signal energies across different regions
Solution Approach 1:
The patent applies local quality by setting different noise point thresholds for different regions of the receiving array. Specifically, a first noise point threshold is set for a first region and a second noise point threshold is set for a second region, where the first and second noise point thresholds are different. This allows the denoising process to adapt to varying noise characteristics and echo signal energies in different spatial regions, thereby improving denoising accuracy without excessive complexity.
Solution Approach 2:
The receiving array is segmented into multiple regions (first region and second region), each with its own dedicated noise point threshold. This segmentation allows independent optimization of denoising parameters for each region based on its specific noise characteristics, resolving the contradiction between simple processing and accurate denoising.
2Measurement precision
If different noise point thresholds are used for different pixel positions and distances, then the denoising accuracy is improved, but the system complexity increases
Solution Approach 1:
The patent implements local quality by configuring different noise point thresholds according to specific pixel positions and measurement distances. The processing unit is configured to set the first noise point threshold for the first region and the second noise point threshold for the second region based on their respective pixel positions and distances. This targeted approach improves LIDAR accuracy by adapting to local noise characteristics while maintaining manageable system complexity through structured threshold configuration.
Data Source
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AI summary
The present application embodiment discloses a denoising method for a LIDAR and a LIDAR. The method first obtaining the echo signal corresponding to a pixel unit in a receiving array of the LIDAR; obtaining a target measurement distance and echo feature information based on the echo signal, wherein the echo feature information is an echo amplitude and/or an echo width; obtaining a target noise point threshold based on a pixel position of the pixel unit and the target measurement distance; determining whether the echo signal is a noise signal according to the echo feature information and the target noise point threshold; if so, deleting the echo signal. Different pixel positions or different target measurement distances correspond to different target noise thresholds. The target noise threshold changes with the change of the pixel position or the target measurement distance to effectively remove the noise signals in multiple echo signals received at the pixel position and improve the accuracy of the LIDAR.