基于联合对角化的近场源参数估计
Parameter Estimation of Near Field Sources Using Joint Diagonalization
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摘要: 该文提出了一种基于联合对角化的近场源信号到达方向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,再基于阵列接收数据的高阶累积量矩阵的对角结构信息利用联合对角化方法估计近场信号的阵列方向矩阵,从而由阵列导向矢量联合估计信号源的到达方向和距离。与高阶ESPRIT方法相比,该方法能够提高阵元利用效率,同时不需要参数配对算法。计算机仿真实验证实了所给算法的有效性。Abstract: A new algorithm to estimate jointly the Direction-Of-Arrival (DOA) and range of near field sources is presented. Firstly, the whiten matrix is constructed by use of the second order statistics, and then the array steering matrix of near field sources is estimated by use of joint diagonalization of the array cumulant matrices, which exploits the structural information of the higher order statistics of the data received by the array. Thus the DOA and range can be estimated from the array steering vectors simultaneously. Compared with the higher-order ESPRIT method, the new algorithm can improve the efficiency of elements. In addition, it does not need any operation of parameters pairing. Its good performance is verified by computer simulation results.
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