2D DOA Estimation Algorithm for Coherently Distributed Source
相干分布式信源二维波达方向估计算法

In many two-dimensional (2D) Direction Of Arrival (DOA) estimation approaches for coherently distributed source, the computational complexity induced by 2D searching manipulation is prohibitively high. A decoupled 2D DOA estimation algorithm is proposed. The integral steering vector of coherently distributed source is deduced to be a Schur-Hadamard product comprising the steering vector of the point source and a real vector. And then a second statistics is proposed for the data collected at subarray X, the rotational invariance matrices can be estimated based on propagator method. So the azimuth and elevation angle can be obtained by the proposed second statistics and the rotational invariance matrices even if elevation angle approaches 90°. In addition, the presented method does not apply any peak-finding searching and eigenvalue decomposition, which has significantly reduced the computational complexity compared with classical subspace algorithm. Simulation results verify the effectiveness of the proposed algorithm.