An Error Self-Corrected DOA Estimation Model for Sparse Array Based on ANM

Abstract

This paper proposes a model based on atomic norm minimization for sparse array, which corrects the amplitude-phase errors and estimates direction-of-arrival parameters. The method performs error self-correction by adding the constraint condition of the inverse matrix of the error matrix. In order to conform to the atomic norm minimization model, the array sensor selection matrix is constructed to link the expected complete data with the actual received data. Finally, we give the atomic norm model suitable for this problem. The algorithm makes full use of the advantages of the atomic norm minimization method, making it more suitable for scenarios where sparse arrays have inconsistencies of the amplitude-phase errors between the receive channels. Simulation experiments verify the feasibility and effectiveness of the proposed method.