Abstract
In this paper the dynamic compressed sensing (DCS) estimation of time varying underwater acoustic (UWA) channel is investigated. By modeling the time varying UWA channels as sparse set consisting with constant and time-varying supports, the estimation of time varying UWA channel is transformed into a problem of dynamic compressed sensing (DCS) sparse recovery. Employing the combination of Kalman filter and compressed sensing for channel estimation, a time reversal receiver is driven by the channel estimate to improve the performance of the underwater acoustic communication. Finally the experimental results with the field data obtained in a shallow water acoustic communication experiment indicate that, the proposed algorithm outperforms the classic channel estimation methods.
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