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LiDAR Echo Gaussian Decomposition Algorithm for FPGA Implementation
by
Jia, Guoshuai
, Zhou, Xiang
, Zhou, Guoqing
, Chen, Jinlong
, Zhu, Qiang
in
Accuracy
/ Algorithms
/ Decomposition
/ Design and construction
/ Digital integrated circuits
/ echo processing algorithm
/ FPGA
/ Gaussian decomposition
/ Lasers
/ LiDAR
/ Matrix decomposition
/ Methods
/ Noise
/ Testing
2022
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LiDAR Echo Gaussian Decomposition Algorithm for FPGA Implementation
by
Jia, Guoshuai
, Zhou, Xiang
, Zhou, Guoqing
, Chen, Jinlong
, Zhu, Qiang
in
Accuracy
/ Algorithms
/ Decomposition
/ Design and construction
/ Digital integrated circuits
/ echo processing algorithm
/ FPGA
/ Gaussian decomposition
/ Lasers
/ LiDAR
/ Matrix decomposition
/ Methods
/ Noise
/ Testing
2022
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Do you wish to request the book?
LiDAR Echo Gaussian Decomposition Algorithm for FPGA Implementation
by
Jia, Guoshuai
, Zhou, Xiang
, Zhou, Guoqing
, Chen, Jinlong
, Zhu, Qiang
in
Accuracy
/ Algorithms
/ Decomposition
/ Design and construction
/ Digital integrated circuits
/ echo processing algorithm
/ FPGA
/ Gaussian decomposition
/ Lasers
/ LiDAR
/ Matrix decomposition
/ Methods
/ Noise
/ Testing
2022
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LiDAR Echo Gaussian Decomposition Algorithm for FPGA Implementation
Journal Article
LiDAR Echo Gaussian Decomposition Algorithm for FPGA Implementation
2022
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Overview
As the existing processing algorithms for LiDAR echo decomposition are time-consuming, this paper proposes an FPGA-based improved Gaussian full-waveform decomposition method. The proposed FPGA architecture consists of three modules: (i) a pre-processing module, which is used to pipeline data reading and Gaussian filtering, (ii) the inflection point coordinate solution module, applied to the second-order differential operation and to calculate inflection point coordinates, and (iii) the Gaussian component parameter solution and echo component positioning module, which is utilized to calculate the Gaussian component and echo time parameters. Finally, two LiDAR datasets, covering the Congo and Antarctic regions, are used to verify the accuracy and speed of the proposed method. The experimental results show that (i) the accuracy of the FPGA-based processing is equivalent to that of PC-based processing, and (ii) the processing speed of the FPGA-based processing is 292 times faster than that of PC-based processing.
Publisher
MDPI AG,MDPI
Subject
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