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Journal of Projectiles, Rockets, Missiles and Guidance >

2010 , Vol. 30 >Issue 2: 263 - 267

DOI: https://doi.org/10.15892/j.cnki.djzdxb.2010.02.052

CORRELATION TECHNOLOGY

Classification-aided Neural Network Data Association in Multi-target Tracking

  • DU Peng ,
  • WU Jun ,
  • WU Zhifeng ,
  • WANG Rui
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  • 1 The Engineering Institute, Air Force Engineering University, Xi'an 710038,China
    2 School of Materials & Metallurgy, Northeastern University, Shenyang 110004, China

Received date: 2009-02-09

  Online published: 2025-05-28

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Abstract

To solve the problem of data association in multiple target tracking system, the UKF neural network and classification-aided algorithm was brought into the algorithms. The classification information likelihood function was defined by class confusion matrix, and this function was used to adjust the measurement likelihood function so that the classification information could effectively aid the probabilistic data association. By using Hopfield network solving TSP problem, NJPDA algorithm avoided the large computational burden in JPDA. Based on the prime data association received from NJPDA, the simulation of multi-target tracking in clutter shows that data association is improved by the proposed technique.

Key words： JPDA; UKF; data association; neural network; classification

Cite this article

DU Peng , WU Jun , WU Zhifeng , WANG Rui . Classification-aided Neural Network Data Association in Multi-target Tracking[J]. Journal of Projectiles, Rockets, Missiles and Guidance, 2010 , 30(2) : 263 -267 . DOI: 10.15892/j.cnki.djzdxb.2010.02.052

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