基于MIMO雷达的极化平滑降维酉ESPRIT算法

相干目标的波达方向估计一直是雷达信号处理中的一个难题.为了获得更好的相干信号角度估计精度,并提高算法可实现性,在多输入、多输出雷达的基础上,提出一种极化平滑降维酉旋转不变性参数估计算法.首先通过降维矩阵对接收信号数据进行降维处理,然后利用降维后的接收数据构造中心复共轭对称矩阵,再构建适当的酉矩阵对其进行实值处理,然后对...

Unitary ESPRIT algorithm of polarization smoothing dimension reduction based on MIMO radar

The direction of arrival (DOA) estimation of coherent targets has always been a difficult problem in the field of radar signal processing.In order to obtain better angle estimation accuracy for coherent signals and improve the achievability of the algorithm, a polarization smoothing and dimensionality reduction unitary estimation of signal parameters via rotational invariance (ESPRIT) technique is proposed on the basis of multi-input and multi-output radar.First, reduce the dimension of the received signal data through the dimension reduction matrix, then use the reduced dimension to construct the central complex conjugate symmetric matrix, and then construct an appropriate unitary matrix to perform real-value processing, and then polarize and smooth it Solve the coherent processing, and finally construct a real-value rotation invariance equation to estimate the direction of arrival of the target. Compared with the conventional polarization smoothing rotation invariance parameter estimation algorithm, the polarization smoothing dimensionality reduction unitary rotation invariance parameter estimation algorithm proposed in this paper not only has higher coherent signal angle estimation accuracy and lower robustness, but also has Lower the amount of calculation and more conducive to engineering realization. The fifth section uses MATLAB software to simulate the proposed algorithm and the comparison algorithm. The simulation experiment proves the validity and authenticity of the algorithm.