基于降维累积量和矩阵重构的相干DOA估计OA

In this paper,a direction of arrival(DOA)estimation method for multi-source coherent signals based on reduced-dimensional higher-order cumulants and low-rank matrix reconstruction is proposed to improve the performance of DOA estimation in radar systems caused by low signal-to-noise ratio(SNR),insufficient snapshot sampling data,non-Gaussian clutter interference,and multipath propagation effects in complex electromagnetic environments.Firstly,by constructing a fourth-order cumulant matrix,the array aperture is expanded to suppress Gaussian noise.Then,an effi-cient reduced-dimensional strategy is employed to reduce computational complexity.Finally,the alternating direction method of multipliers is used to solve the reconstruction problem of Toeplitz covariance matrix under low-rank con-straints,achieving high-precision localization of multi-source coherent signals in complex environments.Experimental results demonstrate that the proposed algorithm maintains excellent estimation performance for multi-source coherent signals under low SNR and limited snapshots,combining high accuracy and strong anti-interference capabilities.