Asynchronous Information Fusion in Intelligent Driving Systems for Target Tracking Using Cameras and Radars

Xiaohui Hao, Yuanqing Xia*, Hongjiu Yang, Zhiqiang Zuo

*Corresponding author for this work

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Abstract

In this article, an asynchronous information fusion issue is investigated for a camera and a radar in an intelligent driving system. Local camera and radar estimators with missed detections are developed independently at synchronized state update time for target tracking. A Kuhn-Munkers algorithm is used to match local tracking results of camera and radar for fusion estimation of a same target. A fusion estimator is obtained by a matrix-weighted fusion algorithm with wide detection range and reliable fused estimates. Effectiveness of the proposed asynchronous fusion estimator is displayed by experimental results on road vehicle tracking.

Original languageEnglish
Pages (from-to)2708-2717
Number of pages10
JournalIEEE Transactions on Industrial Electronics
Volume70
Issue number3
DOIs
Publication statusPublished - 1 Mar 2023

Keywords

  • Asynchronous information fusion
  • camera and radar
  • intelligent driving system
  • target tracking

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Hao, X., Xia, Y., Yang, H., & Zuo, Z. (2023). Asynchronous Information Fusion in Intelligent Driving Systems for Target Tracking Using Cameras and Radars. IEEE Transactions on Industrial Electronics, 70(3), 2708-2717. https://doi.org/10.1109/TIE.2022.3169717