Direction-of-Arrival Estimation Based on the Moving Array With/Without Model Mismatch
Shaozhuang Wu, Qiao Su, Lu Bai, Sihang Yang, Yang Chen, Zhiqing Ma · 2024
This paper proposes the Direction-of-Arrival (DOA) estimation algorithms based on the moving array with and without model mismatch. Firstly, without model mismatch, dividing the uniform linear subarray extracted from the extended model based on the moving array into two parts, two selected receive signal vectors are obtained. By calculating the auto-covariance matrix and the cross-covariance matrix of these receive signal vectors, the DOAs can be estimated though eigenvalue decomposition. As for the model mismatch case, another receive signal vector can be gotten by introducing more delays, then, the DOAs can be obtained similarly with the proposed algorithm without model mismatch. Simulation results testify the effectiveness of the proposed algorithms, and provide the suggestions of the scope of application of two proposed algorithms.