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Cubature particle filter with Markovian Chain Monte Carlo process (CPF-MC) is proposed in order to alleviate the degeneracy and impoverishment problems existing in the particle filter, and the CPF-MC algorithm is improved from two aspects. On the one hand, CPF-MC uses the square root cubature Kalman filter (SRCKF) as proposal distribution that integrates the latest measurement into the particle filter and approximates the optimal posterior probability distribution more accurately. On the otherdoi:10.7763/ijet.2016.v6.860 fatcat:dupgigb4hzg3hojkwsmod2yoei