LiDAR Waveform Interpolation for Higher Point Cloud Resolution
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Solution Overview
Problem
Existing LiDAR systems face challenges in achieving higher resolution without increasing hardware load or power consumption, as adding emitter and receiver pairs leads to cross-talk and accuracy issues, while neural network processing lacks reliable echo pulse signals.
Innovation Solution
Perform interpolation on actual channels of LiDAR based on waveform information and weights of associated channels to generate interpolation channels, enhancing resolution without altering hardware structure.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If pairs of emitter and receiver are added to improve resolution, then measurement precision is improved, but device complexity and power consumption increase
Solution Approach 1:
The patent creates virtual emitter-receiver pairs by copying and processing signals from existing physical channels through interpolation algorithms. Instead of adding physical hardware, the system generates synthetic channel data that mimics what additional sensors would detect, achieving higher resolution without increasing device complexity
Solution Approach 2:
The patent replaces the mechanical approach of adding physical emitter-receiver pairs with a signal processing approach using interpolation algorithms. The system substitutes hardware expansion with computational methods, using waveform information and weights to generate virtual channels that provide enhanced resolution
2Measurement precision
If pairs of emitter and receiver are added to improve resolution, then measurement precision is improved, but cross-talk between channels increases
Solution Approach 1:
By creating virtual channels through signal interpolation rather than adding physical sensors, the system avoids the cross-talk that occurs between adjacent physical emitter-receiver pairs. The copied signal data is generated computationally without the physical interference that plagues dense sensor arrays
3Measurement precision
If neural network processing is applied to point cloud information to improve resolution, then measurement precision is improved, but reliability decreases due to lack of echo pulse signals
Solution Approach 1:
The patent performs interpolation on the raw waveform information before point cloud generation, creating enhanced channel data in advance. This preliminary processing of the echo pulse signals ensures that the interpolated data maintains the physical constraints and signal characteristics needed for reliable measurement, unlike post-processing neural network approaches
Data Source
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AI summary
A method and an apparatus for improving the resolution of a LiDAR, and a LiDAR, the LiDAR including a plurality of actual channels, wherein one actual channel corresponds to one emitter unit at a emitting end and one detector unit at a detecting end, the method including: determining at least one interpolation channel to be generated; separately determining, for each interpolation channel to be generated, one or more associated channels among the plurality of actual channels that are related to the interpolation channel to be generated; determining weights of the one or more associated channels with respect to the interpolation channel to be generated; and generating a waveform of the interpolation channel based on waveform information of the one or more associated channels and the weights thereof, and determining point cloud data of the LiDAR based on the obtained waveform information of each actual channel and each interpolation channel. The solution of this disclosure can effectively improve the resolution of the existing LiDAR without increasing the hardware load thereon.