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Article

A Novel De-Noising Method for Improving the Performance of Full-Waveform LiDAR Using Differential Optical Path

by 1,2,†, 1,3,†, 1,*, 1, 1, 1,2, 1 and 2
1
Key Laboratory of Biomimetic Robots and Systems, Ministry of Education, Beijing Institute of Technology, Beijing 100081, China
2
Department of Biomedical Engineering, National University of Singapore, Singapore 117575, Singapore
3
NUS Suzhou Research Institute (NUSRI), Suzhou Industrial Park, Suzhou 215123, China
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Remote Sens. 2017, 9(11), 1109; https://doi.org/10.3390/rs9111109
Received: 18 August 2017 / Revised: 29 September 2017 / Accepted: 27 October 2017 / Published: 30 October 2017
(This article belongs to the Section Remote Sensing Image Processing)
A novel de-noising method for improving the performance of full-waveform light detection and ranging (LiDAR) based on differential optical path is proposed, and the mathematical models of this method are developed and verified. Backscattered full-waveform signal (BFWS) is detected by two avalanche photodiodes placed before and after the focus of the focusing lens. On the basis of the proposed method, some simulations are carried out and conclusions are achieved. (1) Background noise can be suppressed effectively and peak points of the BFWS are transformed into negative-going zero-crossing points as stop timing moments. (2) The relative increment percentage of the signal-to-noise ratio based on the proposed method first dramatically increases with the increase of the distance, and then the improvement gets smaller by increasing the distance. (3) The differential Gaussian fitting with the Levenberg-Marquardt algorithm is applied, and the results show that it can decompose the BFWS with high accuracy. (4) The differential distance should not be larger than c/2 × τrmin, and two variable gain amplifiers can eliminate the inconsistency of two differential beams. The results are beneficial for designing a better performance full-waveform LiDAR. View Full-Text
Keywords: full-waveform LiDAR; differential optical path; background noise; SNR; backscattered full-waveform signal; Levenberg-Marquardt full-waveform LiDAR; differential optical path; background noise; SNR; backscattered full-waveform signal; Levenberg-Marquardt
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MDPI and ACS Style

Cheng, Y.; Cao, J.; Hao, Q.; Xiao, Y.; Zhang, F.; Xia, W.; Zhang, K.; Yu, H. A Novel De-Noising Method for Improving the Performance of Full-Waveform LiDAR Using Differential Optical Path. Remote Sens. 2017, 9, 1109. https://doi.org/10.3390/rs9111109

AMA Style

Cheng Y, Cao J, Hao Q, Xiao Y, Zhang F, Xia W, Zhang K, Yu H. A Novel De-Noising Method for Improving the Performance of Full-Waveform LiDAR Using Differential Optical Path. Remote Sensing. 2017; 9(11):1109. https://doi.org/10.3390/rs9111109

Chicago/Turabian Style

Cheng, Yang; Cao, Jie; Hao, Qun; Xiao, Yuqing; Zhang, Fanghua; Xia, Wenze; Zhang, Kaiyu; Yu, Haoyong. 2017. "A Novel De-Noising Method for Improving the Performance of Full-Waveform LiDAR Using Differential Optical Path" Remote Sens. 9, no. 11: 1109. https://doi.org/10.3390/rs9111109

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