LiDAR Echo Gaussian Decomposition Algorithm for FPGA Implementation

Guoqing Zhou; Xiang Zhou; Jinlong Chen; Guoshuai Jia; Qiang Zhu

doi:10.3390/s22124628

LiDAR Echo Gaussian Decomposition Algorithm for FPGA Implementation

Sensors (Basel). 2022 Jun 19;22(12):4628. doi: 10.3390/s22124628.

Authors

Guoqing Zhou^{1

2

3

4}, Xiang Zhou^{1

2

4}, Jinlong Chen⁴, Guoshuai Jia⁴, Qiang Zhu^{3

5}

Affiliations

¹ School of Microelectronics, Tianjin University, Tianjin 300072, China.
² The Center of Remote Sensing, Tianjin University, Tianjin 300072, China.
³ Guangxi Key Laboratory of Spatial Information and Geomatics, Guilin University of Technology, Guilin 541004, China.
⁴ College of Mechanical and Control Engineering, Guilin University of Technology, Guilin 541004, China.
⁵ College of Earth Science, Guilin University of Technology, Guilin 541004, China.

Abstract

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.

Keywords: FPGA; Gaussian decomposition; LiDAR; echo processing algorithm.

Abstract

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