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Proceedings Paper

IMMPDA algorithm for infrared target tracking based on multifeature fusion
Author(s): Jin Zhang; Jianxun Song; Qinzhang Wu
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Paper Abstract

The interacting multiple model probability data association (IMMPDA) algorithm is widely used to target tracking in clutter. However, it is difficult for IMMPDA to get high precision track when measurements of kinematics state is inaccurate, because it only considers kinematics feature of targets. To overcome the disadvantage, this paper presents an IMMPDA algorithm based on multi-feature fusion that utilizes multiple features of infrared targets such as kinematics state, size and gray. Association probabilities for targets position are calculated based on IMMPDA algorithm in the polar coordinates. Then the statistic distances of the size and gray are calculated according to state predictions and measurements. After that, statistic distances are further used to compute related association probabilities of targets that are in the validation region. The decision of synthetic data association of all targets in the validation region is made based on the information fusion, which uses fuzzy logic to get different weights of each feature. Experiments indicate that the proposed algorithm has high quality tracking performance. Compared with conventional IMMPDA algorithm, the new algorithm cannot only get higher accurate target association but also improve the stability of the infrared target tracking system.

Paper Details

Date Published: 8 January 2008
PDF: 9 pages
Proc. SPIE 6835, Infrared Materials, Devices, and Applications, 68351J (8 January 2008); doi: 10.1117/12.756229
Show Author Affiliations
Jin Zhang, Institute of Optics and Electronics (China)
Graduate Univ. of the Chinese Academy of Sciences (China)
Jianxun Song, Institute of Optics and Electronics (China)
Graduate Univ. of the Chinese Academy of Sciences (China)
Qinzhang Wu, Institute of Optics and Electronics (China)

Published in SPIE Proceedings Vol. 6835:
Infrared Materials, Devices, and Applications
Yi Cai; Haimei Gong; Jean-Pierre Chatard, Editor(s)

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