Volume 12 Issue 3
Jun.  2023
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Article Navigation >  Journal of Radars  > 2023  >  12(3): 529-540
CHEN Hui, WEI Fengqi, and HAN Chongzhao. UAV path planning strategy based on threat avoidance in multiple extended target tracking optimization[J]. Journal of Radars, 2023, 12(3): 529–540. doi: 10.12000/JR22116
Citation: CHEN Hui, WEI Fengqi, and HAN Chongzhao. UAV path planning strategy based on threat avoidance in multiple extended target tracking optimization[J]. Journal of Radars, 2023, 12(3): 529–540. doi: 10.12000/JR22116
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UAV Path Planning Strategy Based on Threat Avoidance in Multiple Extended Target Tracking Optimization

DOI: 10.12000/JR22116
  • 1.

    College of Electrical and Information Engineering, Lanzhou University of Technology, Lanzhou 730050, China

  • 2.

    College of Automation Science and Engineering, Xi’an Jiaotong University, Xi’an 710049, China

Funds:  The National Natural Science Foundation of China (62163023, 62173266, 62103318, 61873116), The Industrial Support Project of Education Department of Gansu Province (2021CYZC-02)
More Information
  • Corresponding author: CHEN Hui, huich78@hotmail.com
  • Received Date: 2022-06-17
  • Accepted Date: 2022-07-25
  • Rev Recd Date: 2022-07-22
    • Available Online: 2022-08-01
  • Publish Date: 2022-08-11
    Abstract
  • To reduce the probability of UAV (Unmanned Aerial Vehicle) being destroyed during a reconnaissance mission, this study proposes an effective path planning algorithm to reduce the target threat. First, high-resolution airborne radar is used for robust tracking and estimation of multiple extended targets. Subsequently, the targets are classified based on the threat degree calculated via fuzzy TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution). Next, path planning of a UAV is performed considering joint optimization of multiple task decision-making (the joint evaluation of the target threat degree and target tracking performance) as an evaluation criterion. The simulation results indicate that the fuzzy threat assessment method is effective in multiple extended target tracking, and the proposed UAV path planning algorithm is reasonable. Thus the target threat is efficiently reduced without losing the tracking accuracy.

     

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