Computer Science

Computer Science ›› 2020, Vol. 47 ›› Issue (11A): 321-326.doi: 10.11896/jsjkx.2004000145

• Computer Network • Previous Articles     Next Articles

Dynamic Adaptive Multi-radar Tracks Weighted Fusion Method

ZHANG Liang-cheng1,2, WANG Yun-feng1   

  1. 1 College of Computing,Sichuan University,Chengdu 610065,China
    2 Chengdu Yunwei Technology Co.,Ltd.,Chengdu 610042,China
  • Online:2020-11-15 Published:2020-11-17
  • About author:ZHANG Liang-cheng,born in 1996,postgraduate.His main research interests include multi-source information fusion and target tracking.
    WANG Yun-feng,born in 1975,Ph.D.His main research interests include multisource information fusion and big data analysis.
  • Supported by:
    This work was supported by the Project of Department of Science and Technology of Sichuan Province(2019JDRC0042).

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Abstract: In order to form a more accurate fused track by using multi-source radar track data,the theoretical method of multi-source information fusion classical dynamic weighting method and Kalman filter technology are studied.A dynamic adaptive weighted fusion method of multi-source radar information is designed.To overcome the disadvantage of the static assignment weighted fusion method when the radar detection accuracy and detection environment are unknown,setting up a quality factor which contains 4 subitem weights that reflect the quality characteristics of the data source,and real-time analysis of the quality of radar track reports.Depending on the quality factor to complete multi-source fusion dynamically,and obtain better accuracy fusion track.After practical testing and simulation test,it proves that this method is effective and steady.

Key words: Kalman filtering, Multi-source information fusion, Target tracking, Weighting fusion

CLC Number: 

  • TP301
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