Continuous-Discrete Unscented Kalman Filtering
نویسنده
چکیده
The unscented Kalman filter (UKF) is formulated for the continuous-discrete state space model. The exact moment equations are solved approximately by using the unscented transform (UT) and the measurement update is obtained by computing the normal correlation, again using the UT. In contrast to the usual treatment, the system and measurement noise sequences are included from the start and are not treated later by extension of the state vector. The performance of the UKF is compared to Taylor expansions (extended Kalman filter EKF, second and higher order nonlinear filter SNF, HNF), the Gaussian filter, and simulated Monte Carlo filters using a bimodal Ginzburg-Landau model and the chaotic Lorenz model.
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