基于稀疏表示的不相关分布式信源参数估计算法

在分析不相关分布式信源(Incoherently Distributed Source, IDS)信号模型的基础上，该文给出一种基于稀疏表示的IDS参数估计方法。该方法利用IDS协方差矩阵的Toeplitz性质，结合IDS协方差矩阵的两点近似及Jacobi-Anger级数展开模型，分别采用两个1维稀疏表示问题对IDS的角度扩展及中心入射角度进行估计。同现有算法相比，该文方法不需要进行2维搜索，计算量较小。仿真结果表明，该文算法在低信噪比及小快拍情况下具有良好的参数估计性能。

Parameter Estimation Method of Incoherently Distributed Source via Sparse Representation

By analyzing the signal model of the Incoherently Distribute Source (IDS), a sparse representation based parameter estimation method of IDS is presented. Through using the Toeplitz characteristic and the two point approximation model as well as the Jacobi-Anger expansion model of the covariance matrix of the IDS, the angle spread and the central direction angle of the IDS is estimated by adopting two sparse representation problems. Compared with the present method, the proposed method does not need two dimensional searches and has low computational burden. Simulation results show that the proposed method has good parameter estimation performance in the low signal-to-noise ratio and small snapshot number scenario.