Multichannel Weak Signal Extraction Based on Multispectral LiDAR

• Published in: IEEE transactions on geoscience and remote sensing 2024, Vol.62, p.1-11
• Main Authors: Hou, Xiaxia, Song, Shalei, Ran, Yanhong, Chen, Yuxuan, Chen, Zhenwei, Wang, Binhui, Guo, Long
• Format: Article
• Language: English
• Subjects: Adaptive threshold; Correlation; correlation analysis; Correlation coefficient; Correlation coefficients; Data mining; Detection; Echoes; Image color analysis; Laser radar; Lasers; Lidar; multispectral light detection and ranging (MSL); Root-mean-square errors; System effectiveness; Target recognition; Three dimensional models; Three-dimensional displays; Timing; wave information detection and extraction; Waveforms; weak signal
• ISSN: 0196-2892; 1558-0644
• DOI: 10.1109/TGRS.2024.3371575

The information extracted from waveform data of full-waveform light detection and ranging (LiDAR) has been widely used in applications such as 3-D urban modeling, target recognition, and classification. However, the presence of weak signals is inevitable in LiDAR systems. To enhance its effective detection capability and extraction accuracy, we propose a multispectral LiDAR (MSL) weak signals extraction (MSL-WSE) method. The measurement data from our MSL system were used to evaluate the performance of the proposed method. The correlation coefficient ( {R}^{{2}} ), root mean square error (RMSE), and effective extraction rate show that the MSL-WSE method accurately detected and extracted the waveform parameters of weak echo signals, providing a more realistic and fine-grained true color 3-D point cloud.