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Ensemble Consider Kalman Filtering

2018 IEEE CSAA Guidance, Navigation and Control Conference (CGNCC)(2018)

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Abstract
For the nonlinear systems, the ensemble Kalman filter can avoid using the Jacobian matrices and reduce the computational complexity. However, the state estimates still suffer greatly negative effects from uncertain parameters of the dynamic and measurement models. To mitigate the negative effects, an ensemble consider Kalman filter (EnCKF) is designed by using the "consider" approach and resampling the ensemble members in each step to incorporate the statistics of the uncertain parameters into the state estimation formulations. The effectiveness of the proposed EnCKF is verified by two numerical simulations.
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Key words
state estimation formulations,EnCKF,Kalman filtering,nonlinear systems,ensemble Kalman filter,Jacobian matrices,computational complexity,uncertain parameters,dynamic measurement models,ensemble members
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