Abstract
Tracking maneuvering targets in a radar system is m ore complicated because the target accelerations cannot be directly measured. It may occur severe tracking error even diverge the estimates when the m aneuvering situations are happened. In this paper, we develop a Dual-Kalman filtering algorithm to handle the m aneuvering targets' tracking problems. In this approach, two collaborativ e Kalman filters are devised which one for pursuing the track estimation and the other for estimating the status of m aneuver. Based on this approach, the m ost approximate target's acceleration can be detected and estimated in real tim e. Moreover, it is also shown that one Com petitive Hopfield Neural Network-based data association combined with a multiple-target tracking system demonstrates target tracking capability.
Original language | English |
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Pages (from-to) | 1479-1490 |
Number of pages | 12 |
Journal | Journal of Information Science and Engineering |
Volume | 26 |
Issue number | 4 |
Publication status | Published - 2010 Jul 1 |
All Science Journal Classification (ASJC) codes
- Software
- Human-Computer Interaction
- Hardware and Architecture
- Library and Information Sciences
- Computational Theory and Mathematics