Robust Underwater Acoustic Channel Estimation in Impulsive Noise Environment

Impulsive noise is one key factor limiting the performance of underwater acoustic (UWA) communications. This paper proposes an UWA channel estimation algorithm based on variational Bayesian inference (VBI) in an impulsive noise environment. Different from existing methods, we model observations as a combination of normal data not disturbed by impulsive noise and outliers affected by impulsive noise, and utilize a set of binary indicator variables to automatically identify outliers. Under the proposed mixed model, we use VBI to alternately infer the posterior distribution of the UWA channel and impulsive noise, and compensate for the impulsive noise during the estimation of the UWA channel. Experiment results show that the proposed algorithm has better performance than existing methods in suppressing impulsive noise.