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- Title
Design Method of High-Order Kalman Filter for Strong Nonlinear System Based on Kronecker Product Transform.
- Authors
Liu, Xiaohan; Wen, Chenglin; Sun, Xiaohui
- Abstract
In this paper, a novel design idea of high-order Kalman filter based on Kronecker product transform is proposed for a class of strong nonlinear stochastic dynamic systems. Firstly, those augmenting systems are modeled with help of the Kronecker product without system noise. Secondly, the augmented system errors are illustratively charactered by Gaussian white noise. Thirdly, at the expanded space a creative high-order Kalman filter is delicately designed, which consists of high-order Taylor expansion, introducing magical intermediate variables, representing linear systems converted from strongly nonlinear systems, designing Kalman filter, etc. The performance of the proposed filter will be much better than one of EKF, because it uses more information than EKF. Finally, its promise is verified through commonly used digital simulation examples.
- Subjects
KRONECKER products; NONLINEAR systems; NONLINEAR dynamical systems; LINEAR systems; RANDOM noise theory
- Publication
Sensors (14248220), 2022, Vol 22, Issue 2, p653
- ISSN
1424-8220
- Publication type
Article
- DOI
10.3390/s22020653