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In this paper, a new extended Kalman particle filter based information fusion is proposed for state estimation problem of nonlinear and non-Gaussian systems. It uses extended Kalman filter algorithm to update particles in particle filter, with which the local state estimated values can be calculated. The multi-sensor information fusion filter is obtained by applying the standard linear minimum variance...
In this paper, an unscented particles filter based distributed information fusion is proposed for state estimation problem of nonlinear and non-Gaussian systems. It uses unscented Kalman filter algorithm to update particle; then calculates local state estimated values by particle filter. The system fusion estimation is obtained by applying the fusion rule weighted by scales. The simulation results...
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