Tongxin xuebao (Feb 2016)
Jointing sparse recovery estimation algorithm of underwater acoustic channels with long time delay spread
Abstract
Efficient estimation of underwater acoustic channels with a large time ay spread was addressed. For the conventional channel estimation methods such as LS, this type of channel estimation would produce serious estimation noise in zero-value taps which lead to poor performance of channel estimation. At the same time, a large time delay spread posed significant difficulties such as large channel order and the corresponding huge computation complexity. Compressed sensing (CS)channel estimation algorithm offered a solution to this problem by exploiting the sparsity of channel to improve the estimation performance. However to ensure acceptable estimation performance, a long training sequence was needed, which unfortunately would cause additional overhead. A method was proposed which exploiting the joint correlation of sparse multipath structure between adjacent data blocks to deal with the estimation of long time delay channels under the framework of distributed compressed sensing (DCS).Thus the large time delay underwater acoustic channels can be jointly reconstructed by the simultaneous orthogonal matching t (SOMP)algorithm to fa-cilitate the system overhead reduction and estimation ance improvement. Simulation as well as the sea trial re-sults indicate the effectiveness of the proposed method.
