Authors:
Il Young Song
and
Moongu Jeon
Affiliation:
Gwangju Institute of Science and Technology, Korea, Republic of
Keyword(s):
Distribute Fusion, Multi Sensor, Kalman Filter, Time-delayed System, Receding Horizon.
Related
Ontology
Subjects/Areas/Topics:
Informatics in Control, Automation and Robotics
;
Modeling, Analysis and Control of Discrete-event Systems
;
Sensors Fusion
;
Signal Processing, Sensors, Systems Modeling and Control
Abstract:
In this paper, we provide two computational effective multi sensor fusion filtering algorithms for discrete-time linear uncertain systems with state and observation time delays. The first algorithm is shaped by algebraic forms for multi rate sensor systems, and then we propose a matrix form of filtering equations using block matrices. The second algorithm is based on exact cross-covariance equations. These equations are useful to compute matrix weights for fusion estimation in a multidimensional-multisensor environment. Also, our proposed filtering algorithm is based on the receding horizon strategy in order to achieve high estimation accuracy and stability under parametric uncertainties. We demonstrate the low computational complexities of the proposed fusion filtering algorithm and how the proposed algorithm robust against dynamic model uncertainties comparing with Kalman filter with time delays.