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

A new underwater lidar signal-processing method based on wavelet transform (WT) and independent component analysis (ICA) is presented in this letter. The proposed method combines WT and ICA to overcome the drawbacks of ICA and WT applied independently. ICA requires the number of observations equal to or greater than the number of sources to be separated. In the new method, the observation matrix of ICA is constructed by multi-layer wavelet time-domain decomposition from a single measurement, which avoids the uncertainties in multiple measurements caused by the change of measurement conditions. In addition, the new method greatly improves the frequency resolution of the echo signal by introducing wavelet transform. It can remove both the low-frequency scattering and high-frequency electromagnetic noises in the obtained signals. The new approach was tested in an underwater lidar system. A pulsed 532 nm 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 Avalanche Photo Diode (APD) detector and the acquisition system with a bandwidth of 1 GHz is used to receive the echo signals. Underwater target ranging experiments were conducted when the attenuation length (AL) was 10. The ranging accuracies were compared with different signal processing methods. When there was no scattering suppression algorithm applied, the ranging accuracy was 12 cm; with only ICA, the ranging accuracy was 6.8 cm, with only WT, the accuracy was 5 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 improve the ranging accuracy.