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

Yang Cheng,Jie Cao,Kaiyu Zhang,Qun Hao,Fanghua Zhang,Haoyong Yu,Yuqing Xiao,Wenze Xia

doi:10.3390/rs9111109

Abstract

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.

Highlights

Light Detection and Ranging (LiDAR) is an active, remote-sensing system that provides direct range measurement and is capable of collecting three-dimensional (3D) spatial information [1,2]
(1) Background noise can be suppressed effectively and peak points of the backscattered full-waveform signal (BFWS) are transformed into negative-going zero-crossing points as stop timing moments
(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

Summary

Introduction

Light Detection and Ranging (LiDAR) is an active, remote-sensing system that provides direct range measurement and is capable of collecting three-dimensional (3D) spatial information [1,2]. A discrete-echo LiDAR records only a few discrete-echo backscattered waveform signals for each transmitted laser pulse and provides only 3D coordinates and range information about objects [8,12]. Unlike the discrete-echo LiDAR, a full-waveform LiDAR can record the entire backscattered full-waveform signal (BFWS) for each transmitted laser pulse as a function of time, followed by a digital sampling with an extremely high temporal resolution (typically by 1 ns intervals) [13]. Compared with the discrete-echo LiDAR, the full-waveform LiDAR is more suitable in many applications, including surface topography, airborne vegetation mapping, disaster and crisis management, natural resource monitoring, mission planning, and target identification [16,17]

Objectives

Methods

Results