STABLE DECONVOLUTION OF NOISY LIDAR SIGNALS

A main application of lidar remote sensing is to provide spatial resolved data. Based on the fundamental relationship between space and time the distance can be calculated from the photons’ time of flight. Accordingly, the distance resolution is limited by the time resolution of the lidar detector. Furthermore, if the system response function of the lidar is longer than the time resolution interval of the detector, the measured lidar signal is smeared, and the effective distance resolution decreases. In theory, this loss of resolution can be corrected by deconvolution of the measured signal with the system response function. Measured lidar signals are superposed by noise which makes a direct deconvolution impossible because of the effect of noise amplification. In this paper, a technique is presented which allows for a stable deconvolution of lidar signal returns without any filtering in the frequency domain. It is based on the Richardson-Lucy algorithm for image reconstruction. Simulations of short distance lidar signals have been used to compare the method with conventional deconvolution algorithms such as the Fourier transformation.