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Improved UPF algorithm based on Gaussian Sigma points selected

  

  • Received:2013-03-07 Revised:2013-04-18 Published:2013-06-20

Abstract: An improved UPF algorithm is proposed for the problem of particles degradation in the standard particle filter. The algorithm uses adaptive unscented Kalman filter based on Gaussian Sigma points selected to generate the proposal distribution function, and then uses the Metropolis-Hastings to optimize particles, so that the approximation of the posterior probability density of the system is improved. Simulation results show that the improved algorithm reduces particle degradation which exists in the particle filter,and improves tracking accuracy. Key words: particle filter, Gaussian Sigma points, unscented Kalman filter, Metropolis-Hastings.

Key words: particle filter, Gaussian Sigma points, unscented Kalman filter, Metropolis-Hastings.

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