Lidar signal denoising using least-squares support vector machine

Abstract

The noise in a Lidar signal is analyzed first, and then a novel method that applies least-square support vector machine (LS-SVM) to denoising Lidar signals is proposed. In order to improve the performance of denoising, the a priori knowledge about Lidar signals is also incorporated in the training of the LS-SVM. Finally, the experimental results demonstrate the effectiveness and efficiency of our approach.