DOA estimation of one-bit sparse cross-dipole array based on atomic norm minimization

The existing direction of arrival (DOA) estimation methods for one-bit sparse cross-dipole arrays are all methods for subspace. The DOA estimation accuracy is affected by the decreasing of statistical efficiency and lacking usage of the structure of the covariance matrix. In order to improve the DOA estimation accuracy by one-bit sparse cross-dipole arrays, a DOA estimation method based on atomic norm minimization is proposed in this paper. The proposed method transforms the DOA estimation of sparse cross-dipole array into that of a scalar array with the same configuration, and then constructs an atomic set-based sparse model of the received signal according to the continuity of parameter space. By using the sparsity of noise under one-bit sampling, an additional l_1-norm constraint is introduced to make the model suitable for one-bit data. A fast method based on alternating direction multiplier is then developed to reduce the computational complexity of atomic norm minimization. Numerical results show that the proposed method outperforms the existing ones from the viewpoint of estimation accuracy, the mean square error of its estimation accuracy is reduced by 17.9 dB on a nested array when the signal-to-noise ratio is −5 dB. The proposed method is also suitable for large array due to its low complexity as O(N^3) , where N is the number of a uniform linear array (ULA) which has the same array length and the sensor spacing.