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LIAO Xiaorong, SUN Guohao, ZHONG Suchuan, et al. Joint optimization of radar and jammer space-time cooperative beamforming for a multitasking dynamic scene[J]. Journal of Radars, in press. doi: 10.12000/JR23243
Citation: LIAO Xiaorong, SUN Guohao, ZHONG Suchuan, et al. Joint optimization of radar and jammer space-time cooperative beamforming for a multitasking dynamic scene[J]. Journal of Radars, in press. doi: 10.12000/JR23243

Joint Optimization of Radar and Jammer Space-time Cooperative Beamforming for a Multitasking Dynamic Scene

doi: 10.12000/JR23243
Funds:  The National Natural Science Foundation of China (62201371), Sichuan Provincial Natural Science Foundation (2022NSFSC1952), Municipal Government of Quzhou (2022D013)
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  • Corresponding author: SUN Guohao, sghsjw2005@126.com
  • Received Date: 2023-12-25
  • Rev Recd Date: 2024-03-22
  • Available Online: 2024-03-29
  • The modern radar confrontation situation is complex and changeable, and inter-system combat has become a basic feature. The overall system performance affects the initiative on the battlefield and even the final victory or defeat. By optimizing the beam resources of radar and jammers in a system, the overall performance can be improved, and the effective low-intercept detection effect can be obtained in the spatial and temporal domains. However, joint optimization of cooperative beamforming in the spatial and temporal domains is a nonconvex problem with complex multiparameter coupling. In this paper, an optimization model is established for a multitasking dynamic scene in the spatial and temporal domains. Radar detection performance is the optimization goal, while the interference performance and energy limitation of jammers are the constraints. To solve the model, a joint design method of space-time cooperative beamforming based on iterative optimization was proposed; that is, iterative optimization of radar transmitting, receiving, and multiple jammers transmitting beamforming vectors was alternately optimized. To solve the Quadratically Constrained Quadratic Programs (QCQP) problem with indefinite matrices for multijammer collaborative optimization, this paper is based on the Feasible-Point-Pursuit Successive Convex Approximation (FPP-SCA) algorithm. In other words, on the basis of the SCA algorithm, algorithm feasibility is ensured through reasonable relaxation by introducing relaxation variables and a penalty term, which solves the difficulty of obtaining a feasible solution when a problem contains indefinite matrices. Simulation results show that under the constraint of certain jammer energy, the proposed method achieves the effect of multiple jammers interfering with each enemy platform in the spatial and temporal domains to cover our radar detection. This effect is achieved while ensuring high-performance radar detection of the target without interference. Compared with traditional algorithms, the collaborative interference based on the FPP-SCA algorithm exhibits a better performance in the dynamic scene.

     

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