幅相误差下基于MIMO雷达的相干信号高精度DOA估计OA

The performance of direction of arrival(DOA)estimation for coherent signals in multiple-input multiple-output(MIMO)radar deteriorates under the condition of amplitude-phase errors.An improved Multiple Signal Classification(MUSIC)algorithm based on power adaptive subarray smoothing and iterative optimization of noise subspaces is proposed.This method improves the robustness of the traditional algorithm through a two-stage optimization strategy.Firstly,a power adaptive subarray smoothing mechanism is designed to dynamically weight the covariance matrix according to the signal strength of subarrays to suppress the energy mismatch between subarrays caused by amplitude-phase errors.Secondly,the iterative optimization algorithm of noise subspace projection matrix is introduced,and the random error compensation technology is used to correct the noise space distortion to reduce the interference of error on the orthogonality criterion.Finally,the new noise subspace is obtained by eigen-decomposition of the optimized projection matrix,and the DOA estimation is realized by combining the MUSIC algorithm.The simulation results show that,compared with the traditional algorithm,the proposed algorithm can reduce the root mean square error(RMSE)of DOA estimation by 25%and improve the success rate of coherent signal resolution by 30%in typical amplitude-phase error scenarios.