DOA Estimation of Direction Vector Estimation Algorithm Based on Second-order Statistical Properties
In order to reduce the influence of errors of antenna array manifold on Direction of Arrival (DOA) estimation results, and to overcome the shortcoming of DOA estimation algorithm based on traditional blind source separation algorithm that can not be applied to direction-finding equipment with few channel receivers, a DOA estimation algorithm of direction vector estimation algorithm based on second-order statistical properties is proposed. Firstly, according to the characteristics of spectral function of Deterministic Maximum Likelihood (DML) estimation algorithm, an optimization problem with unitary constraints on covariance matrix is constructed. Then, the actual direction vector of each single signal is obtained by optimizing the problem. Finally, the actual direction vectors of each single signal are input into the spatial spectral algorithm to achieve DOA estimation. Because the DOA estimation of multiple signals is transformed into the DOA estimation of multiple single signals, the proposed algorithm has better DOA estimation performance than the traditional DOA method when the antenna array manifold has errors. Because the proposed algorithm only uses covariance matrix, the proposed algorithm can be applied to direction-finding equipment with few channel receivers. The simulation results show that the proposed algorithm has higher accuracy, immunity and resolution than the traditional DOA estimation algorithm when the array manifold has errors and the equipment is the direction-finding equipment with few channel receivers.
Direction of Arrival (DOA) estimationErrors of antenna array manifoldBlind source separationUnitary constraint