单输入多输出水声信道的联合稀疏恢复估计

Joint Sparse Recovery Estimation of Underwater Acoustic Single-input-multiple-output Channels

单输入多输出(SIMO)水声通信系统可利用空间分集获取性能增益,考虑到水声信道垂直相关半径通常大于SIMO接收阵的阵元间距,因此各个SIMO信道响应的多径稀疏结构具有较强的相关性。利用SIMO信道间存在的稀疏相关性,提出分布式压缩感知(CS)框架的SIMO水声信道联合稀疏恢复估计算法,与传统CS信道估计方法只利用信道自身稀疏性相比,联合稀疏恢复估计方法可进一步利用信道间多径结构的相关性提高稀疏重构性能。仿真和海试SIMO水声通信实验表明:与传统估计方法相比,利用多通道联合稀疏恢复可有效提高SIMO信道估计性能,特别是可获取较低信噪比条件下的性能改善。

Underwater single-input-muhiple-output （SIMO） system enables the exploitation of space diversity to achieve performance enhancement. Considering that the vertical correlation radius of underwater channels is usually larger than the distance between array elements, the sparse structures of SIMO channels response exhibit considerable correlation feature. A channel estimation algorithm under the framework of distributed compressed sensing（CS） is presented to perform the joint sparse recovery estimation of SIMO channel via simultaneous orthogonal matching pursuit （OMP）. Compared with the traditional CS channel estimation algorithms which only exploit the sparsity of single channel, the proposed algorithm is capable of employing the joint sparse correlation of SIMO channels to improve the performance of SIMO channel estimation. The simulation and field experimental results show that the proposed algorithm effec- tively improves the performance of SIMO channel estimation in terms of estimation accuracy and communi- cation quality, especially under low signal-noise ratio.