基于联合对角化的近场源三维参数估计

提出了一种基于联合对角化的近场源频率、到达角（DOA）和距离的联合估计算法。首先利用二阶统计量构造白化矩阵，再基于白化后的接收数据构造一组高阶累积量矩阵，利用联合对角化方法来得到高阶累积量矩阵的对角结构信息以及对角化矩阵来分别估计阵列流形和信号源的频率，进而由阵列导向矢量结合对应的信号源频率联合估计信号源的到达方向和距离。与基于高阶累积量的类 ESPRIT方法相比，算法可以提高阵元利用率，具有更好的估计效果，同时不需要谱峰搜索且各参数自动配对，计算机仿真结果验证了该方法的有效性。

Estimating 3-D Parameters of Near-Field Sources Based Joint Diagonalization

A new algorithm to jointly estimate the frequency,direction-of-arrival（DOA）and range of near field sources is presented.Firstly,the whiten matrix is constructed by using the second order statistics, and a set of higher-order cumulant matrices are devised.Then the array steering matrix and the source fre-quency of near-field sources are estimated from the higher-order cumulant matrices＇structural information, which is achieved by using the technology of joint diagonalization of the cumulant matrices.Thus the DOA and range can be estimated via combining the array steering vectors and sources＇frequency.Compared with the ESPRIT-like method based on high-order statistics,the algorithm can improve the efficiency of elements and get better performance.In addition,it doesn＇t need spectral peak searching or parameters pairing,the ef-fectiveness of the proposed algorithm is verified by computer simulation results.