Volume 14 Issue 2
Apr.  2025
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Article Navigation >  Journal of Radars  > 2025  >  14(2): 456-469
ZHANG Peng, YAN Junkun, GAO Chang, et al. Integrated transmission resource management scheme for multifunctional radars in dynamic electromagnetic environments[J]. Journal of Radars, 2025, 14(2): 456–469. doi: 10.12000/JR24230
Citation: ZHANG Peng, YAN Junkun, GAO Chang, et al. Integrated transmission resource management scheme for multifunctional radars in dynamic electromagnetic environments[J]. Journal of Radars, 2025, 14(2): 456–469. doi: 10.12000/JR24230
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Integrated Transmission Resource Management Scheme for Multifunctional Radars in Dynamic Electromagnetic Environments

DOI: 10.12000/JR24230 CSTR: 32380.14.JR24230

  • National Key Laboratory of Radar Signal Processing, Xidian University, Xi’an 710071, China

Funds:  The National Natural Science Foundation of China (62471356, 62101350, 62192714), Industry University-Research Cooperation of the 8th Research Institute of China Aerospace Science and Technology Corporation (SAST2023-068)
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  • Corresponding author: YANJunkun, jkyan@xidian.edu.cn
  • Received Date: 2024-11-19
  • Rev Recd Date: 2025-03-10
    • Available Online: 2025-03-14
  • Publish Date: 2025-03-27
    Abstract
  • Traditional multifunctional radar systems optimize transmission resources solely based on target characteristics. However, this approach poses challenges in dynamic electromagnetic environments owing to the intelligent time-varying nature of jamming and the mismatch between traditional optimization models and real-world scenarios. To address these limitations, this paper proposes a data-driven integrated transmission resource management scheme designed to enhance the Multiple Target Tracking (MTT) performance of multifunctional radars in complex and dynamic electromagnetic environments. The proposed scheme achieves this by enabling online perception and utilization of dynamic jamming information. The scheme initially establishes a Markov Decision Process (MDP) to mathematically model the risks associated with radar interception and adversarial jamming. This MDP provides a structured approach to perceive jamming information, which is then integrated into the calculation of MTT. The integrated resource management challenge is formulated as an optimization problem with constraints on the action space. To solve this problem effectively, a greedy sorting backtracking algorithm is introduced. Simulation results demonstrate the efficacy of the proposed method, demonstrating its ability to significantly reduce the probability of radar interception in dynamic jamming environments. Furthermore, the method mitigates the impact of jamming on radar performance during adversarial interference, thereby improving MTT performance.

     

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