Nested阵列的矩阵重构高精度DOA估计算法

Matrix reconstruction high accuracy DOA estimation algorithm on the Nested array

针对Nested阵列利用Khatri-Rao积操作,将接收数据的协方差矩阵拉成列向量,即接收数据变为单快拍的问题,提出了一种新矩阵重构方法.该方法可恢复接收数据的协方差矩阵的秩,并提出了矩阵重构旋转不变测向算法.该算法可构造出Nested阵列虚拟阵元的协方差矩阵,利用这种矩阵重构的方法,可构造多个矩阵根据旋转不变方法进行测向.仿真结果表明,通过使用该种矩阵重构旋转不变测向算法,能够准确地估计出目标数多于阵元个数的信号的波达方向.

For the nested array, the covariance matrix of the receiving data is pulled into a column vector by using the Khatri-Rao product, which is equivalent receiving data turned into the single snapshot. In the case ol the covariance matrix being vectored, a new matrix reconstruction is presented to build up the rank of the new covariance matrix and the ESPRIT algorithm of an improved matrix reconstruction is proposed in this paper. The covariance matrix on the virtual array will be restored and more matrices can be reconstructed by using this approach. Then, the DOA estimation is obtained based on the ESPRIT algorithm of matrix reconstruction. Simulation results demonstrate that the proposed method achieves accurate DOA estimation when the number of targets is larger than that of array elements.