ESPRIT-based DOA and polarization estimation for coherent cyclostationary signals with a uniform linear array of trimmed vector sensors

With a uniform linear array of trimmed vector sensors (TVS-ULA), a novel cyclic ESPRIT-based algorithm is proposed to estimate the direction-of-arrival (DOA) and polarization of the coherent cyclostationary signals. By exploiting the cyclostationarity and the invariance property among the outputs of the trimmed vector sensors, the proposed method increases the resolution power and improves the noise robustness. In addition, the proposed algorithm reduces the computational load. The performance of the proposed approach is confirmed through numerical examples, and it is shown that this method is superior in resolving the closely-spaced cyclostationary signals in multipath environment.