DOA, power and polarization angle estimation using sparse signal reconstruction with a COLD array
Existing polarized source localization methods mostly rely on subspace technique. In this paper, a very different framework, namely sparse signal reconstruction, is extended to estimate direction-of-arrival (DOA), power and polarization angle parameters using a cocentered orthogonal loop and dipole (COLD) array. The key points of the proposed algorithm can be summarized as three aspects: (i) this paper first constructs a special second-order statistics vector by using sum-average arithmetic, which is only the function of DOA and power parameters; (ii) then this paper constructs another three special second-order statistics vectors, which are only the function of polarization parameters; (iii) this paper exploits Zhang penalty to enforce sparsity, which lead to almost unbiased index and amplitude estimation. This paper also demonstrates how to distinguish two sources using their polarization characteristics. Simulation results validate the effectiveness and superiority of the proposed algorithm.
doa power and polarization angle estimation sparse signal reconstruction cold array array signal processing