Title :
Interval models for target tracking algorithms
Author :
Shan Gong ; Hong, Lang
Author_Institution :
Dept. of Electr. Eng., Wright State Univ., Dayton, OH, USA
Abstract :
Presents a set of models which utilize the target information implied by more than two scans of measurements. The new models are called interval models. Simulations prove that interval models have significant advantages over existing models in certain common scenarios
Keywords :
geometry; matrix algebra; statistics; target tracking; interval models; target information; target tracking algorithms; Acceleration; Electric variables measurement; Equations; Gaussian distribution; Sampling methods; State-space methods; Target tracking; Traffic control; Uncertainty;
Conference_Titel :
American Control Conference, 1997. Proceedings of the 1997
Conference_Location :
Albuquerque, NM
Print_ISBN :
0-7803-3832-4
DOI :
10.1109/ACC.1997.611836
