Bayesian Time Delay Estimation of GNSS Signals in Dynamic Multipath Environments

Abstract

A sequential Bayesian estimation algorithm for multipath mitigation is presented, with an underlying movement model that is especially designed for dynamic channel scenarios. In order to facilitate efficient integration into receiver tracking loops, it builds upon complexity reduction concepts that previously have been applied within maximum likelihood (ML) estimators. To demonstrate its capabilities under different GNSS signal conditions, simulation results are presented for both BPSK‐modulated and BOC‐(1,1) modulated navigation signals.