Robust Deconvolution of Underwater Acoustic Channels Corrupted by Impulsive Noise

Impulsive noise is one of the most challenging forms of interference in an underwater acoustic environment. In this paper, we present an underwater acoustic channel deconvolution method based on a sparse representation framework. The application of the method enables a channel impulse response reconstruction that is robust to impulsive noise. By exploiting the inherent structure in the channel response, the measured signal may be expressed as depending on the unknown channel in a multiplicative manner, enabling an efficient deconvolution framework. This allow us introduce an lp-norm optimization framework that is then adopted to deconvoluting the under-water acoustic channel in the presence of impulsive noise. The resulting framework is efficiently solved using the alternating direction method of multipliers (ADMM). The performance of the proposed algorithm is demonstrated using simulations and experimental data collected from South China Sea.