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Acta Aeronautica et Astronautica Sinica ›› 2024, Vol. 45 ›› Issue (12): 329466-329466.doi: 10.7527/S1000-6893.2023.29466

• Electronics and Electrical Engineering and Control • Previous Articles    

Intelligent TBD algorithm for maneuvering weak targets based on TransUNet

Xingrui WU1, Ruihui PENG1,2(), Dianxing SUN1, Shuncheng TAN3, Yihong ZHANG1, Wenbin WEI1   

  1. 1.Qingdao Innovation and Development Center,Harbin Engineering University,Qingdao 266000,China
    2.College of Information and Communication Engineering,Harbin Engineering University,Harbin 150001,China
    3.Information Fusion Research Institute,Naval Aviation University,Yantai 264001,China
  • Received:2023-08-22 Revised:2023-09-22 Accepted:2023-10-28 Online:2023-11-23 Published:2023-11-22
  • Contact: Ruihui PENG E-mail:pengruihui@hrbeu.edu.cn
  • Supported by:
    Natural Science Foundation of Shandong Province(ZR2020MF015);Aerospace Technology Group Stability Support Project(ZY0110020009)

Abstract:

The development and application of stealth technology have brought great challenges to radar target detection. As one of the important technical directions for weak target detection, the Tracking-Before-Detection (TBD) technology is often used in radar detection. However, the traditional TBD requires a large amount of computation and is limited by target motion models, making it difficult to effectively detect maneuvering targets in various motion states. To address this issue, a TransUNet based intelligent TBD algorithm for weak targets is proposed. The algorithm is not limited by any motion model and can effectively identify maneuvering targets in various motion states. Firstly, utilizing the spatio-temporal correlation characteristics of the target motion trajectory, a rough detection algorithm for maneuvering weak targets in different motion states is designed based on the TransUNet model to achieve preliminary detection of weak maneuvering targets. Then, the preliminary detection results are used to perform regional search for the target measurement, and achieve backtracking of weak maneuvering target points. Finally, to address the problem of missed detection in preliminary backtracking points at low Signal-to-Noise Ratio (SNR), the auxiliary information of partially successfully detected points, combined with the Optimal Parabolic (OP) value function, is utilized to achieve precise detection of target points and complete backtracking of tracks. Simulation experiments have verified that this method proposed can effectively detect weak maneuvering targets in various motion states.

Key words: Tracking-Before-Detection (TBD), weak target, TransUNet network, spatio-temporal correlation characteristics, target detection, optimal parabolic value function

CLC Number: