LiDAR Channel Emission Control for High-Reflectivity Crosstalk
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Solution Overview
Problem
High-resolution and high-frame-rate LiDAR systems experience significant crosstalk between channels due to the small physical isolation degree of adjacent channels, particularly exacerbated by high-reflectivity objects, which reduces detection accuracy.
Innovation Solution
A LiDAR control method that adjusts the emission strategy of target adjustment channels based on the spatial position of high-reflectivity objects determined from previous scanning cycles, utilizing driving information to predict and correct positions, and implementing a high-reflectivity emission strategy to minimize crosstalk.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If transmission coding and filtering strategy are used to reduce crosstalk between channels, then channel isolation is improved, but detection accuracy deteriorates due to interference between concurrent channels and high-reflectivity objects
Solution Approach 1:
The system performs preliminary identification of high-reflectivity objects using point cloud data from the previous scanning cycle before the current scanning cycle begins. Based on this preliminary identification, the emission strategy is adjusted in advance for channels that will scan through the predicted position of high-reflectivity objects, preventing crosstalk interference before it occurs
Solution Approach 2:
The emission strategy is made dynamic and adaptive rather than static. The system continuously monitors point cloud data to identify high-reflectivity objects, predicts their positions based on vehicle driving information, and dynamically adjusts the emission strategy for different channels based on their scanning trajectories relative to predicted object positions
2Object-affected harmful factors
If the physical isolation degree between adjacent channels is increased to reduce crosstalk, then channel interference is reduced, but device complexity and size increase
Solution Approach 1:
Instead of changing the physical structure of the LiDAR device, the system changes operational parameters - specifically the emission strategy parameters (emission timing, pulse width, power) for different channels based on their scanning angles and predicted high-reflectivity object positions. This software-based parameter adjustment replaces the need for increased physical isolation
3Measurement precision
If the emission strategy is adjusted in real-time to mitigate crosstalk from high-reflectivity objects, then detection precision is improved, but processing time and system complexity increase
Solution Approach 1:
The system uses point cloud data from the previous scanning cycle to preliminarily identify high-reflectivity objects before the current scanning cycle begins. This preliminary identification allows the emission strategy to be adjusted in advance, so that when the LiDAR scans through the predicted position of high-reflectivity objects, the appropriate mitigation strategy is already in place, reducing processing time during the actual scanning
Solution Approach 2:
The system implements dynamic adjustment of emission strategies based on real-time identification of high-reflectivity objects and their predicted positions. The control device continuously monitors point cloud data, updates object positions based on vehicle driving information, and dynamically adjusts emission parameters for different channels to optimize detection precision while managing processing time
Data Source
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AI summary
The application provides a LiDAR control method and device, a terminal device and a storage medium, and the method comprises the following steps: in the case that it is determined according to point cloud data of a previous frame that a high-reflectivity object exists in a detection area, determining the spatial position of the high-reflectivity object according to the point cloud data of the previous frame; determining a target adjustment channel according to the spatial position of the high-reflectivity object; adjusting the emission strategy of the target adjustment channel to a high-reflectivity emission strategy; and controlling the LiDAR to perform scanning in a current scanning cycle according to the adjusted emission strategy, and controlling the switching of the channel corresponding to the high-reflectivity object in the current scanning cycle to the high-reflectivity emission strategy in advance, so that the interference of the reflected echo generated by the high-reflectivity object can be better reduced, and the detection precision of the LiDAR is improved.