Scattering Suppression in Underwater LIDAR Signal Processing Based on Wavelet-ICA Method

Abstract

A new underwater lidar signal-processing method based on wavelet transform (WT) and independent component analysis (ICA) is presented in this paper. The proposed method combines WT and ICA to overcome that the number of observations required for ICA must be equal to or greater than the number of sources to be separated. In the new method, the observation matrix of ICA is constructed from multi-layer wavelet time-domain decomposition in a single measurement. The Wavelet-ICA method avoids the uncertainties in multiple measurements caused by the change of measurement conditions and reduces the error of ICA algorithm. In addition, the new method greatly improves the frequency resolution of the echo signal by introducing wavelet transform. It can remove both the noises caused by lowfrequency scattering and high-frequency electromagnetic clutters. The new approach was tested in an underwater lidar system. The pulse light source operates at a repetition rate of 50 kHz, with an average output power of 3 W and a pulse duration of less than 1 ns. An APD detector and the acquisition system with a bandwidth of 1 GHz is used to receive the echo signals. We used a piece of black rubber as the target. Underwater target ranging experiments were conducted when the attenuation length(AL) was 10. The ranging accuracies were compared: without any scattering suppression algorithm, the ranging accuracy was 12 cm; with only WT, the accuracy was 4 cm; using the Wavelet-ICA method, the ranging accuracy was improved to 2 cm. The signal processing method can suppress strong scattering clutter in turbid water, thus greatly improving the ranging accuracy.