High‐degree cubature Kalman filter for nonlinear state estimation with missing measurements
Xing Zhang, Zhibin Yan, Yunqi Chen
Abstract
Abstract This paper proposes high‐degree cubature Kalman filter for nonlinear systems with missing measurements. We derive out the explicit formulas for the prediction and update in the filtering. To fulfill the numerical computation, especially the numerical integrals, of these formulas, the fifth‐degree spherical‐radial cubature rule is adopted to give a high‐degree cubature Kalman filtering algorithm. Through numerical example, it is shown that the fifth‐degree cubature Kalman filter has better precision and stability than the extended Kalman filter, the unscented Kalman filter, and the fifth‐degree unscented Kalman filter.
Topics & Concepts
Kalman filterFast Kalman filterEnsemble Kalman filterExtended Kalman filterDegree (music)Invariant extended Kalman filterAlpha beta filterUnscented transformControl theory (sociology)ComputationMathematicsNonlinear systemFilter (signal processing)Computer scienceApplied mathematicsAlgorithmMoving horizon estimationStatisticsPhysicsArtificial intelligenceComputer visionAcousticsControl (management)Quantum mechanicsTarget Tracking and Data Fusion in Sensor NetworksInertial Sensor and NavigationControl Systems and Identification