多频带水声信道的时频联合稀疏估计

多频带水声信道多径结构在相邻数据块和不同子频带存在相关性,从分布式压缩感知的角度可对这种时频联合稀疏特性进行利用。但是,在传统联合稀疏模型下水声信道间存在的不同多径时延部分形成差异支撑集,由此引入的干扰导致估计性能下降,提出利用多路径选择机制进行差异支撑集检测;同时,进一步结合频域子频带信道间、时域相邻数据块信道间存在的相关性进行频带-时间域联合稀疏估计.利用数值仿真及海试实验结果进行了性能验证和比较,表明利用时频联合稀疏估计构造的水声通信接收机改善了匹配性能,可获得较为明显的输出信噪比、误比特率等通信性能提升.从而说明:利用多频带水声信道在时域、频域存在的联合相关性可有效提高信道估计性能。 

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.