The dual-kalman filtering and neural solutions to maneuvering estimation problems

Y. I.Nung Chung, Dend Jyi Juang, Kuo Chang Hu, Ming Liang Li, Kai Chih Chuang

Research output: Contribution to journalArticle

1 Citation (Scopus)

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 languageEnglish
Pages (from-to)1479-1490
Number of pages12
JournalJournal of Information Science and Engineering
Volume26
Issue number4
Publication statusPublished - 2010 Jul 1

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Target tracking
neural network
Hopfield neural networks
Radar systems
Kalman filters
Ores

All Science Journal Classification (ASJC) codes

  • Software
  • Human-Computer Interaction
  • Hardware and Architecture
  • Library and Information Sciences
  • Computational Theory and Mathematics

Cite this

Chung, Y. I.Nung ; Juang, Dend Jyi ; Hu, Kuo Chang ; Li, Ming Liang ; Chuang, Kai Chih. / The dual-kalman filtering and neural solutions to maneuvering estimation problems. In: Journal of Information Science and Engineering. 2010 ; Vol. 26, No. 4. pp. 1479-1490.
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The dual-kalman filtering and neural solutions to maneuvering estimation problems. / Chung, Y. I.Nung; Juang, Dend Jyi; Hu, Kuo Chang; Li, Ming Liang; Chuang, Kai Chih.

In: Journal of Information Science and Engineering, Vol. 26, No. 4, 01.07.2010, p. 1479-1490.

Research output: Contribution to journalArticle

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