Dual polarization beamforming algorithm for multipath mitigation in {GNSS}

Kurzfassung

Abstract This paper treats the problem of line-of-sight (LOS) parameter estimation in strong multipath environments. In the case of highly temporally and spatially correlated {LOS} and multipath signals, such as urban canyons, common multipath mitigation methods are highly degraded, as signal separation cannot be performed in the spatio temporal domain. In this case, we exploit the {LOS} and multipath polarization diversity to decouple the signals using an antenna array with right-hand-circular polarization (RHCP) and left-hand-circular polarization (LHCP) feeds. The multipath direction- of-arrival (DOA) and polarization coefficients can effectively be estimated from the {LHCP} spatial covariance matrix. The {LOS} {DOA} can be estimated from the {RHCP} spatial covariance matrix. The spatial covariance matrices are calculated from the outputs of a matched correlator bank. The {DOA} and polarization estimates are used to implement a dual polarization beamformer, which maximizes the {LOS} energy and suppresses multipath energy over both polarizations. The {LOS} time-delay is estimated from the beamformer output with a maximum-likelihood estimator with a significantly reduced number of parameters and computational complexity in comparison to a full model estimator. Simulation results for {GPS} show that the proposed dual polarization beamforming algorithm performs better than an equivalent single-polarization beamformer in a dense multipath environment.