Research On Noise Suppression And Signal Drift Correction Of Scheimflug Lidar System

This paper based on the new scheimpflug lidar technology developed in recent years,focuses on the digital signal processing of atmospheric echo signals.The scheimpflug lidar system is based on the principle of scheimpflug law.The image sensor is used to receive the backscattered signal of the continuous laser,and the pixel sequence is used to obtain the atmospheric echo signals at different distances.Compared with the traditional pulsed laser radar,due to the difference between the transmitting and receiving systems,it saves a lot of economic costs,and has good applicability and popularization.The purpose of this thesis is to solve the noise problem in the scheimpflug lidar system,improve the signal-to-noise ratio of the system,and provide the atmospheric echo signal with high signal-to-noise ratio for the next inversion analysis.At the same time,a preliminary solution is proposed for the signal drift problem existing in the system and the excessive data collection at the near.This paper first introduces the background of atmospheric environmental monitoring and the principle of scheimpflug lidar system,and then analyzes the noise source and noise properties of the system from the hardware and principle of the system.According to the noise characteristics of the scheimpflug lidar system,three filtering schemes of superimposing average filter,finite impulse response filter(FIR Filter)and Savitzky-Golay filter are selected.The filtering principle and design of the filter are elaborated in detail.After that,the corresponding digital filter was carefully designed.After filtering the signal,in order to evaluate the noise processing effect of the signal,an evaluation index of the noise level is established.According to the quantitative evaluation criteria,the appropriate filter is finally selected,which improves the stability of the system and significantly improves the signal-to-noise ratio under the condition that the signal is not distorted.In addition,for the characteristics of the unique data points unique to the scheimpflug lidar,the resampling algorithm is designed to compress the near-end data volume by about 4 times without affecting the signal-to-noise ratio.For the signal drift problem existing in the scheimpflug lidar system,an algorithm with automatic correction capability in a certain period of time is realized.The research work of this thesis provides high SNR experimental data for signal analysis in the scheimpflug lidar system,which makes the subsequent inversion calculation accuracy of the scheimpflug lidar system significantly improved.At the same time,the resampling algorithm and the automatic correction drift algorithm for the near-end data point acquisition and signal drift design of the system further enhance the robustness of the system.