• Electronics Optics & Control
  • Vol. 24, Issue 11, 43 (2017)
LYU Li-ping1, BAI Xin1, and ZHANG Yu-hong2
Author Affiliations
  • 1[in Chinese]
  • 2[in Chinese]
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    DOI: 10.3969/j.issn.1671-637x.2017.11.009 Cite this Article
    LYU Li-ping, BAI Xin, ZHANG Yu-hong. Dynamic Data Association Algorithm Based on KL Distance for Heterogeneous Sensors[J]. Electronics Optics & Control, 2017, 24(11): 43 Copy Citation Text show less

    Abstract

    To solve the problem of dynamic data association in the multi-target tracking system of heterogeneous sensors,a dynamic data association algorithm for heterogeneous sensors is proposed based on KL distance.This method extends the static multi-dimensional assignment to dynamic tracking.The KL distance between the probability density function of the estimated position and the probability density function of the predicted position of the target track is taken as the association cost function,by merging the measurement set with the track set.Then,it is substituted into the multi-dimensional assignment model to realize the dynamic correlation between measurements and tracks.Simulation results show that the proposed cost function can reflect the association probability between measurements and tracks more accurately and can track multiple targets quickly and steadily.
    LYU Li-ping, BAI Xin, ZHANG Yu-hong. Dynamic Data Association Algorithm Based on KL Distance for Heterogeneous Sensors[J]. Electronics Optics & Control, 2017, 24(11): 43
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