An application of neural network in multiple target tracking

Hui Li, An Zhang, Ying Shen, Cheng Cheng

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

To solve the problem of data association and state estimation in multiple targets tracking system, we brought the network into the algorithms. By using the thinking of Hopfield network in TSP problem, NJPDA algorithm avoided the large computational burden in JPDA, and the parameters in NJPDA can be confirmed online. Based on the prime data association received from NJPDA, we used simplified data fusion adaptive filtering algorithm to realize the state estimation and prediction. These algorithms make the best use of the merits of the neural network ensure the accuracy and real-time of multiple targets tracking.

Original languageEnglish
Pages (from-to)2563-2566+2570
JournalChinese Journal of Sensors and Actuators
Volume19
Issue number6
StatePublished - Dec 2006

Keywords

  • Adaptive filtering algorithm
  • Data fusion
  • Joint probabilistic data association
  • Neural network

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