Comprehensive study on deconvolution and denoising of LiDAR back-scattered signal

Light Detection and Ranging (LiDAR) is an efficient tool for remote sensing and for target detection. This technology has been used for years with a variety of applications. One of the major challenges in the field of LiDAR is the resolution enhancement. Improvement of the resolution may be achieved by applying the deconvolution of the measured signal with the system response function. However, the deconvolution process itself is a noise sensitive process. Recent progresses of signal processing techniques in the area of LiDAR are reviewed. Extensive reviews of such techniques are presented. In this paper the LiDAR system equation, operation, and signal processing techniques like Fourier based deconvolution, regularized deconvolution, and Fourier wavelet based regularized deconvolution, Richardson-Lucy algorithm and non-negative least square method of deconvolution are discussed.