Underwater Acoustic Sparse Channel Estimation Based on DW-SACoSaMP Reconstruction Algorithm

Abstract

The compressive sampling matching pursuit (CoSaMP) algorithm is widely used in orthogonal frequency division multiplexing (OFDM) underwater acoustic (UWA) sparse channel estimation with good estimation accuracy. However, the algorithm requires channel sparsity a priori information as well as a large number of columns in the measurement matrix because of the large delay of the UWA channel during channel estimation, which greatly increases the complexity of CoSaMP. Therefore, a sparsity adaptive CoSaMP based on a dynamic threshold and weak selection of atoms (DW-SACoSaMP) is proposed in this letter. The algorithm can quickly estimate the channel impulse response (CIR) without channel sparsity when used for UWA sparse channel estimation. Simulation results show that, compared with other reconstruction algorithms, the estimation accuracy of this algorithm is higher and the complexity is lower; when the signal to noise ratio (SNR) is greater than 8dB, the advantage of estimation accuracy is more obvious.