Fusion predictors for continuous-time linear systems with different types of observations

Author

Song, Ha-Ryong ; Lee, Kyung-Min ; Shin, Vladimir

Author_Institution

Sch. of Inf. & Mechatron., Gwangju Inst. of Sci. & Technol., Gwangju

fYear

2008

Firstpage

2284

Lastpage

2289

Abstract

New fusion predictors for continuous-time linear systems with different types of observations are proposed. The fusion predictors are formed by summation of the local Kalman filters/predictors with matrix weights depending only on time instants. The relationship between fusion predictors is established. High accuracy and computational efficiency of the fusion predictors are demonstrated on the several examples such as the damper harmonic oscillator motion with multisensor environment.

Keywords

Kalman filters; computational complexity; continuous time systems; linear systems; matrix algebra; prediction theory; sensor fusion; Kalman predictors; computational efficiency; continuous-time linear systems; damper harmonic oscillator motion; fusion predictors; local Kalman filters; matrix weights; multisensor environment; Additive white noise; Aircraft navigation; Control systems; Information filtering; Information filters; Kalman filters; Linear systems; Sensor fusion; Sensor systems; Yttrium; Continuous-time linear system; Kalman predictor; fusion formula; multisensor;

fLanguage

English

Publisher

ieee

Conference_Titel

Control, Automation and Systems, 2008. ICCAS 2008. International Conference on

Conference_Location

Seoul

Print_ISBN

978-89-950038-9-3

Electronic_ISBN

978-89-93215-01-4

Type

conf

DOI

10.1109/ICCAS.2008.4694189

Filename

4694189