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Fuzzy logic approach to multisensor data association

Author

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  • Chen, Y.M.
  • Huang, H.C.

Abstract

There are some problems in the multitarget tracking using multisensor data association with the conventional non-Bayesian or Bayesian method. In addition to some specific limitations of priori condition, such an association could not perform well under a high clutter tracking environment. This paper proposes an association algorithm based on fuzzy-logic called fuzzy data association (FDA) for radar/infrared sensor data fusion. The results of simulation show that the performance of FDA is superior to JPDA which is based on a Bayesian approach. Furthermore, the paper proves that we can get a better improvement of performance when choosing proper numbers of fuzzy rule on FDA. When setting up the FDA, we use efficiency indicator of target tracking performance improvement to avoid the burden of complicated computation.

Suggested Citation

  • Chen, Y.M. & Huang, H.C., 2000. "Fuzzy logic approach to multisensor data association," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 52(5), pages 399-412.
    • Handle: RePEc:eee:matcom:v:52:y:2000:i:5:p:399-412
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    Cited by:

    1. Coelho, Leandro dos Santos & Sauer, João Guilherme & Rudek, Marcelo, 2009. "Differential evolution optimization combined with chaotic sequences for image contrast enhancement," Chaos, Solitons & Fractals, Elsevier, vol. 42(1), pages 522-529.

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