A novel full-waveform LiDAR echo decomposition method and simulation verification

作者：Li Duan^*; Xu Lijun; Li Xiaolu; Wu Di

来源：IEEE International Conference on Imaging Systems and Techniques (IST) / IEEE International School on Imaging, 2014-10-14 to 2014-10-17.

• full-waveform LiDAR
• waveform fitting
• nonlinear least squares
• Gaussian smoothing

In this paper, a novel decomposition method of full-waveform Light Detection And Ranging (LiDAR) echo is proposed. This decomposition method includes four steps. In the first step, the noise mean value and deviation are estimated, meanwhile noise threshold and fitting threshold are configured. In the second step, full-waveform echoes are smoothed using the Gaussian kernel function. In third step, maximum points and inflection points are detected aiming at filtered echoes in the second step. Meanwhile, the number of echo component in full-waveform echo and initial parameters of each echo component are estimated based on the maximum points and inflection points, and echo components are sorted depending on the area of echo components. In the fourth step, the full-waveform echoes are one by one addition fitted using Levenburg-Marquardt (LM) method based on sorted result and fitting threshold. At last, the correct rate, and relative and absolute error of this decomposition method are simulation verified using MATLAB software based on randomly generated data. The result shows that the whole decomposition correct rate of this method is 82%, the maximal relative error of location is 0.18%, the maximal absolute error of amplitude is 1.2157 millivolts, the maximal absolute error of location is 0.5548 nanoseconds, and the maximal absolute error of FWHM is -2.219 nanoseconds. The decomposition correct rate and parameter error show that decomposition coefficients can be further used for target feature extraction and classification.

• 出版日期2014
• 单位北京航空航天大学