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Design of unscented Kalman filter with noise statistic estimator. (Chinese. English summary) Zbl 1212.93304
Summary: For the problem that the accuracy of the conventional UKF declines and further diverges when the prior noise statistic is unknown or inaccurate, an unscented Kalman filter (UKF) with noise statistic estimator is designed. This UKF filtering algorithm based on maximum a posterior (MAP) estimation can estimate and correct the mean and covariance of the noise in real time while it estimates the states. The proposed UKF has the adaptive capability of dealing with variable noise statistic. The simulation results show the effectiveness of the proposed UKF filtering algorithm.
MSC:
93E11 Filtering in stochastic control theory
93E10 Estimation and detection in stochastic control theory
93C40 Adaptive control/observation systems
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