Array-Based GNSS Signal Tracking With a Reduced State Signal Model

Abstract

This paper introduces a reduced state signal model in which interfering signals are suppressed with the help of beamforming. Based on our model, a particle filtering algorithm integrated with beamformer for satellite navigation signal tracking is proposed to increase the computational efficiency and the robustness to the signal model mismatch from unknown interference. Through extensive simulations and flop complexity analysis, we verify the superiority of the proposed algorithm against existing Bayesian filtering algorithms without beamforming.