Abstract
This paper presents a modified particle filter for SINS/SAR (Strap-down Inertial Navigation System/Synthetic Aperture Radar) integrated navigation. This method is developed by adopting Markov Chain Monte Carlo (MCMC) moves to the p article regularization process. It combines local resampling with MCMC moves to prevent particle degeneracy and also guarantee that the resultant particles are in the same distribution as probability distribution function, without causing extra noise on state estimate. Simulation results demonstrate that the proposed method can effectively prevent the problem of particle degeneracy, and its filtering accuracy for SINS/SAR integrated navigation is much higher than that of the classical particle filter and regularized particle filter.
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