Title :
Fusion Predictors for Multisensor Discrete-Time Linear Systems
Author :
Song, Ha Ryong ; Kim, Du Yong ; Shin, Vladimir
Author_Institution :
Gwangju Inst. of Sci. & Technol., Gwangju
Abstract :
Two novel fusion predictors for linear dynamic systems with different types of observations are proposed. They are formed by summing of the local Kalman filters/predictors with matrix weights depending only on time instants. The relationships between them and the optimal Kalman predictor are discussed. High accuracy and computational efficiency of the fusion predictors are demonstrated on the first-order Markov process and the GMTI with multisensor environment.
Keywords :
Kalman filters; Markov processes; discrete time systems; linear systems; matrix algebra; sensor fusion; first-order Markov process; fusion predictors; linear dynamic systems; local Kalman filters; matrix weights; multisensor discrete-time linear systems; optimal Kalman predictor; Aircraft navigation; Equations; Gaussian noise; Kalman filters; Linear systems; Prediction algorithms; Sensor fusion; Sensor systems; Sensor systems and applications; Signal processing algorithms;
Conference_Titel :
Industrial Electronics Society, 2007. IECON 2007. 33rd Annual Conference of the IEEE
Conference_Location :
Taipei
Print_ISBN :
1-4244-0783-4
DOI :
10.1109/IECON.2007.4460053
