Joint DOA and polarization estimation for 1-D PS-MA via implicit rotation invariance analysis and PARAFAC decomposition

This paper investigates the joint estimation of direction-of-arrival (DOA) and polarization parameters using a one-dimensional polarization-sensitive mirrored array (1-D PS-MA) within the framework of parallel factor (PARAFAC) decomposition. The implicit rotational invariance property of the cosine-form spatial manifold is first derived, providing both a theoretical explanation for the formation of virtual signals during array expansion and an exact expression for their spatial manifold. Then, a full-rank hybrid co-array output is constructed via Toeplitz matrix reconstruction, and an explicit signal model is formulated based on the derived rotation invariance. To fully exploit polarization information, this model is incorporated into the PARAFAC decomposition framework. By analyzing the permutation and scaling ambiguities of the decomposed spatial and polarization manifolds, the proposed method enables efficient and automatically paired estimation of DOA and polarization parameters. Numerical results demonstrate that the proposed approach achieves higher estimation accuracy and resolution ability compared to several state-of-the-art methods.