基于稀疏表示的相干分布式非圆信号的参数估计

基于稀疏表示技术，该文提出一种相干分布式非圆信号的参数估计新方法。该方法将信号的非圆特性引入分布式信源模型，充分利用非圆信号的特性，联合阵列输出协方差矩阵和椭圆协方差矩阵，并将其矢量化之后表示在受制于稀疏限制的过完备字典上；然后将DOA估计转化为一个稀疏重构问题，能够一次性求解出中心DOA和角度扩展。仿真结果表明，该方法适用于各种非圆率的非圆信号，具有较好的信噪比性能和分辨力，所提出的方法还能对圆和非圆信号同时存在的情况进行有效估计。

Parameters Estimation of Coherently Distributed Non-circular Signal Based on Sparse Representation

A novel method for parameters estimation of coherently distributed non-circular signal based on the concept of sparse representation is proposed. The non-circular property is introduced into the model of distributed source, and the non-circular property is fully used to unite the covariance and elliptic covariance matrix of the array output. By representing them on overcomplete dictionaries subject to sparse constraint, and transforming DOA estimation into a sparse reconstruction problem, the method is able to solve the central DOA and angular spread at a time. Simulation results show that the proposed method can be used in different kinds of non-circular rate with better performance of low SNR and resolution, and the proposed algorithm can also effectively estimate the DOA in the case of both circular and non-circular signal existing.