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Unscented Kalman filter (UKF) has been extensively used for state estimation of nonlinear stochastic systems, which suffers from performance degradation and even divergence when the noise distribution used in the UKF and the truth in a real system are mismatched. For state estimation of nonlinear stochastic systems with non-Gaussian measurement noise, the Masreliez–Martin extended Kalman filter (EKF)...
This paper studies the problem of distributed estimation for a class of discrete-time nonlinear non-Gaussian systems in a not fully connected sensor network environment. The non-Gaussian process noise and measurement noise are approximated by finite Gaussian mixture models. A distributed Gaussian mixture unscented Kalman filter (UKF) is developed in which each sensor node independently calculates...
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