Title :
Evaluating hierarchical track fusion with information matrix filter
Author_Institution :
Dept. of Syst. Eng. & Oper. Res., George Mason Univ., Fairfax, VA, USA
Abstract :
This paper examines track fusion performance under various degrees of non-deterministicity of the target dynamics, i.e., process noises. There are three approaches to state vector fusion: weighted covariance, information matrix and pseudo-measurement. This paper focuses on performance evaluation of the information matrix form of state vector fusion. Closed form analytical solution of steady state fused covariance for the hierarchical fusion architecture both with and without feedback have been derived. These results provide interesting insight into the mechanism of track fusion and greatly simplify the evaluation of fusion performance. In addition, availability of such a solution facilitates the trade-off studies for designing fusion systems under various operating conditions.
Keywords :
matrix algebra; performance evaluation; sensor fusion; target tracking; feedback; hierarchical track fusion; information matrix; information matrix filter; multisensor data fusion; performance evaluation; process noise; pseudo-measurement; state vector fusion; steady state fused covariance; target dynamics; weighted covariance; Covariance matrix; Information filtering; Information filters; Performance analysis; Sensor fusion; Sensor phenomena and characterization; State estimation; State feedback; Steady-state; Target tracking;
Conference_Titel :
Information Fusion, 2000. FUSION 2000. Proceedings of the Third International Conference on
Conference_Location :
Paris, France
Print_ISBN :
2-7257-0000-0
DOI :
10.1109/IFIC.2000.862450