Inverse Covariance Intersection Fusion Steady-state Kalman filter for Uncertain Systems with Multiplicative Noises, Missing Measurements and Linearly Correlated White Noises
- Resource Type
- Conference
- Authors
- Hu, Huihua; Wang, Xuemei; Tao, Guili
- Source
- 2022 41st Chinese Control Conference (CCC) Chinese Control Conference, 2022 41st. :3174-3178 Jul, 2022
- Subject
- Computing and Processing
Robotics and Control Systems
Signal Processing and Analysis
Transportation
Linear systems
Uncertain systems
Uncertainty
Measurement uncertainty
White noise
Steady-state
Linear matrix inequalities
fictitious noise
covariance intersection (CI)
inverse covariance intersection (ICI)
Kalman filter
- Language
- ISSN
- 1934-1768
This paper is concerned with inverse covariance intersection fusion problem of uncertain linear systems with multiplicative noises, missing measurements and uncertain linearly correlated white noises. By introducing the fictitious noises to compensate the stochastic uncertainties, the system under consideration can be converted into one with only uncertain noise variances. The steady-state Kalman filter is designed by inverse covariance intersection (ICI) fuser. It overcomes the disadvantage that the covariance intersection (CI) fuser has larger conservativeness. The accuracy of the ICI filter is higher than CI filter and that of local filter. A simulation example is given to verify the accuracy relations.