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PMT gain self-adjustment system for high-accuracy echo signal detection.

Authors :
Zhou, Guoqing
Xu, Chao
Zhang, Haotian
Zhou, Xiang
Zhao, Dawei
Wu, Gongbei
Lin, Jinchun
Liu, Zhexian
Yang, Jiazhi
Nong, Xueqin
Zhang, Lieping
Source :
International Journal of Remote Sensing. Oct-Dec2022, Vol. 43 Issue 19-24, p7213-7235. 23p.
Publication Year :
2022

Abstract

The intensity difference between the echo signals from the water surface and bottom during bathymetry LiDAR operation requires a photomultiplier tube (PMT) gain self-adjustment. Otherwise, noise echo signals are collected, while weak and useful signals are not. For this reason, this paper proposes a PMT gain self-adjustment system for the high-accuracy detection of LiDAR echo signals. The developed system uses a field programmable gate array (FPGA) collector as a feedback signal generator, an STM32 controller as the PMT gain and voltage control signal generator and a DA module as the PMT gain voltage conversion circuit. The system controls the PMT gain voltage by judging the feedback signal to achieve PMT gain self-adjustment. The system was verified in an indoor tank, building roof, and outdoor pond experiments. By comparing the experiments, the developed system is shown to detect laser energy intensity with a sensitivity of at least 2.26 times stronger than the traditional system, and can measure water depth at least 2.5 times deeper than the traditional system. Therefore, it can be concluded that the proposed PMT gain self-adjusting system can effectively adapt to the changes in laser energy, improve the measurement of water depth, control the amplitude of the echo signals, increase the accuracy of water depth detection, reduce the saturation of the PMT detector, and protect PMT from damages. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
01431161
Volume :
43
Issue :
19-24
Database :
Academic Search Index
Journal :
International Journal of Remote Sensing
Publication Type :
Academic Journal
Accession number :
161081937
Full Text :
https://doi.org/10.1080/01431161.2022.2155089