Title :
Tracking multiple objects in terrain
Author :
Sobiesk, Edward ; Hamilton, John A., Jr. ; Marin, John A. ; Brown, Donald E. ; Gini, Maria
Author_Institution :
Dept. of Electr. Eng. & Comput. Sci., US Mil. Acad., West Point, NY, USA
Abstract :
The digitized battlefield of the 21st Century will revolutionize the methods used to maintain military command and control. The tremendous amount of data available will necessitate the use of intelligent automated systems that augment, and in some cases replace, the human structures currently in place. One aspect of such systems is terrain-based tracking. We discuss an intelligent terrain-based system for tracking multiple vehicles moving across terrain. Specifically, our system extracts and utilizes knowledge about groups to improve the performance of a discrete state-space motion model. Parallel programming techniques are utilized to compute probability densities for the vehicles. A learning component allows for real-time adjustment based on performance
Keywords :
command and control systems; knowledge based systems; object detection; parallel programming; probability; real-time systems; state-space methods; target tracking; technological forecasting; vehicles; 21st Century; digitized battlefield; discrete state-space motion model; group knowledge; intelligent automated systems; learning component; military command and control; multiple object tracking; parallel programming techniques; performance; probability densities; real-time adjustment; terrain-based vehicle tracking; Air traffic control; Command and control systems; Computer science; Data mining; Intelligent systems; Land vehicles; Military computing; Sensor phenomena and characterization; Target tracking; Working environment noise;
Conference_Titel :
Systems, Man, and Cybernetics, 1998. 1998 IEEE International Conference on
Conference_Location :
San Diego, CA
Print_ISBN :
0-7803-4778-1
DOI :
10.1109/ICSMC.1998.725093