Adaptive Unscented Kalman Filter for Tracking GPS Signals in the Case of an Unknown and Time-Varying Noise Covariance

Abstract

A new adaptive unscented Kalman filter (AUKF) is proposed to estimate the radio navigation parameters of a GPS signal tracking system in noisy environments and on a highly dynamic object. The experimental results have shown that the proposed AUKFbased method improves the GPS tracking margin by approximately 8 dB and 3 dB as compared to the conventional algorithm and the KF-based tracking, respectively. At the same time, the accuracy of Doppler frequency measurements increases as well.