A Sparse Spatial Spectrum Reconstruction Algorithm in the Second-Order Statistical Domain

Traditional sparse recovery-based DOA estimation algorithms can achieve high-precision DOA estimation. However, these algorithms process the signal in receive domain, which has a large complexity. Moreover, traditional algorithms are proposed based on scalar sensor arrays, which cannot exploit the unique polarization information of electromagnetic waves. Therefore, in this paper, a sparse reconstruction algorithm in the second-order statistical domain is proposed for a more complex polarizationsensitive arrays. We firstly reconstruct the received domain signal to achieve parameter decoupling, then obtain the DOA estimation by reconstructing the sparse power spectrum, and finally obtain the polarization parameter by searching the spectral peaks. Simulation experiments demonstrate that the proposed method has higher estimation accuracy and lower complexity than the traditional algorithms.