DOA Estimation Algorithm for Array Error Self-calibration Based on Channel Compression

To enhance the efficiency and accuracy of direction of arrival (DOA) estimation, a novel self-calibrating algorithm is introduced, which incorporates channel compression to address array amplitude-phase errors. By initially compressing the received signal within the channels, the algorithm reduces complexity and computation time. Utilizing atomic norm minimization (ANM), the proposed method leverages signal sparsity to build a model that accommodates amplitude-phase errors, introducing a constraint term for the amplitude error trace. This innovation broadens the applicability of ANM to error-prone data. Simulation outcomes confirm the algorithm’s superior estimation precision.