Title :
Data association in multitarget tracking with multisensor
Author :
Xiaoquan, Song ; Longbin, MO ; Qi, Liu ; Zhongkang, Sun
Author_Institution :
Inst. of Electron. Eng., Nat. Univ. of Defense Technol., Hunan, China
Abstract :
One of the most important problem must be resolved in multitarget tracking with multisensor is the data association. It includes two folds: associating each observation of every sensor with each target, named scan association; associating-the track with track formed by different sensors, track association. There exist some difficulties in obtaining the models and in computing burden while tracking multitarget in a high density clutter environment. This paper presents an efficient method for tracking multitarget with multisensor, and the new method applied integer programming to associate the incoming measurements to established tracks. This paper assumes no new target appears and no target eliminates while the tracking goes on. Theory analysis and Monte Carlo simulations show the potential of this algorithm
Keywords :
Monte Carlo methods; military computing; sensor fusion; target tracking; tracking; Monte Carlo simulation; computing burden; data association; fusion method; high density clutter; integer programming; multisensor; multitarget tracking; scan association; sensor association; simulation; track association; Algorithm design and analysis; Clutter; Infrared sensors; Jamming; Linear programming; Motion measurement; Passive radar; Radar tracking; Sun; Target tracking;
Conference_Titel :
Aerospace and Electronics Conference, 1997. NAECON 1997., Proceedings of the IEEE 1997 National
Conference_Location :
Dayton, OH
Print_ISBN :
0-7803-3725-5
DOI :
10.1109/NAECON.1997.622745