An application of MCMC methods for the multiple change-points problem
Signal Processing - Special section on Markov Chain Monte Carlo (MCMC) methods for signal processing
Mean time to loose lock of phase tracking by particle filtering
Signal Processing - Special section: Distributed source coding
GPS positioning in a multipath environment
IEEE Transactions on Signal Processing
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In this article we propose to process the code and phase delay of a dataless GNSS signal in open and semi-open loops. The aims of this processing are to get an accurate estimate of the phase and code delays by integration of the GNSS signal. We show that in an open loop the code delay evolution is a piecewise stationary process and we propose to model the phase delay as a circular random variable distributed according to a von Mises distribution. In this context the code tracking is realised on the GNSS signal by estimating the abrupt changes in the code discriminator values. We propose a Bayesian modeling of the problem in order to define the change point estimator. The proposed estimator involves in its definition the inaccurate prior information of Doppler and signal to noise density ratio provided by the phase delay tracking loop. Furthermore we propose a circular Bayesian modeling of the observations provided by the phase open loop. From this model, we derive a circular recursive filter for the estimation of phase delay and frequency of the carrier. The proposed tools are assessed using synthetic and real data.