Joint temporal-spectral sparse estimation of underwater acoustic multiband channel

Joint temporal-spectral sparse estimation of underwater acoustic multiband communication channel is investigated.While the similar multipath structure of channels from multiple sub-bands offers the possibility for Distributed Compressed Sensing(DCS) sparsity exploitation,channel responses among multiple sub-bands may simultaneously exhibit different components that deteriorate the performance of joint sparse recovery.To address such differences at the sub-bands,a multiple selection strategy is applied to select multiple candidates at individual sub-bands during the iteration.Moreover,to explore channel coherence between adjacent data blocks from different sub-bands,the multiple selection strategy is also applied over time.This leads to the derivation of DCS channel estimation algorithm that enables time-frequency joint sparsity exploitation.Numerical simulations verify the superiority of the proposed algorithms over the classic sparse estimation algorithms.Finally,experimental results obtained from a shallow water multiband communication system demonstrate the effectiveness of the proposed approach.