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Cubature Kalman Filter. 27052009 Cubature Kalman Filters Abstract. Cubature Kalman filter is the closest known approximate filter in the sense of com. Cubature Kalman Filter The CKF algorithm is a novel nonlinear filtering algorithm proposed by Ienkaran Arasaratnam and Simon Haykin in 2009 which solves the problem that Kalman filtering has a poor estimation effect when the state variable is high-dimensional. The cubature Kalman filter CKF is the closest approximation known so far to the Bayesian filter that could be designed in a nonlinear setting under the Gaussian assumptionUnlike the extended Kalman filter EKF CKF does not require evaluation of Jacobians during the estimation process while in EKF the nonlinear functions are approximated by their.
The cubature Kalman filter CKF is a derivative-free on-line sequential-state estimator. Cubature Kalman filter is the closest known approximate filter in the sense of com. To be consistent with the literature the resulting nonlinear filter is referred to as the continuous-discrete cubature Kalman filter CD-CKF. It relies on integration for its operation. 5022021 To associate your repository with the cubature-kaman-filter topic visit your repos landing page and select manage topics. We use the It-Taylor expansion of order 15 to transform the process equation modeled in the form of stochastic ordinary differential equations into a set of stochastic difference equations.
The heart of the CKF is a spherical-radial cubature rule which makes it possible to numerically compute multivariate moment integrals encountered in the nonlinear Bayesian filter.
A robust state estimation technique based on the Huber-based Cubature Kalman Filter HCKF is proposed for Global Positioning System GPS navigation processing. 1032014 The fifth-degree cubature Kalman filter CKF has been proved to be a kind of algorithm that has higher precision than the third-degree CKF and unscented Kalman filter UKF. The cubature Kalman filter has been developed by Arasaratnam and Haykin 30 and it has been commonly used in many fields such as spacecraft attitude and position estimation 31 mobile location estimation 32. First an improved cubature Kalman filter CKF is derived by considering colored measurement noise where the time-differencing approach is applied to yield new. Thus it works in a way similar to the UKF can be used for highly nonlinear motion models. 1112019 On the other hand a Cubature Kalman filter is adapted for high robust state estimation and a fuzzy controller is proposed to decrease the effect of model error. The heart of the CKF is a spherical-radial cubature. The cubature Kalman filter CKF. To be consistent with the literature the resulting nonlinear filter is referred to as the continuous-discrete cubature Kalman filter CD-CKF. The heart of the CKF is a spherical-radial cubature rule which makes it possible to numerically compute multivariate moment integrals encountered in the nonlinear Bayesian filter. However its performance may decline in accuracy and even diverge in the presence of process uncertainties.
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