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Frontiers of Information Technology & Electronic Engineering
ISSN 2095-9184 (print), ISSN 2095-9230 (online)
2022 Vol.23 No.4 P.617-629
Supermodular interference suppression game for multistatic MIMO radar networks and multiple jammers with multiple targets
Abstract: To deal with the threat of the new generation of electronic warfare, we establish a non-cooperative countermeasure game model to analyze power allocation and interference suppression between multistatic multiple-input multiple-output (MIMO) radars and multiple jammers in this study. First, according to the power allocation strategy, a supermodular power allocation game framework with a fixed weight (FW) vector is constructed. At the same time, a constrained optimization model for maximizing the radar utility function is established. Based on the utility function, the best power allocation strategies for the radars and jammers are obtained. The existence and uniqueness of the Nash equilibrium (NE) of the supermodular game are proved. A supermodular game algorithm with FW is proposed which converges to the NE. In addition, we use adaptive beamforming methods to suppress cross-channel interference that occurs as direct wave interferences between the radars and jammers. A supermodular game algorithm for joint power allocation and beamforming is also proposed. The algorithm can ensure the best power allocation, and also improves the interference suppression ability of the MIMO radar. Finally, the effectiveness and convergence of two algorithms are verified by numerical results.
Key words: Supermodular game; Power allocation; Beamforming; MIMO radar; Multiple jammers
1西安电子科技大学雷达信号处理国家重点实验室,中国西安市,710071
2中国电子科技集团公司第五十四研究所,中国石家庄市,050081
摘要:为应对新一代电子战的威胁,本文建立一种非合作对抗博弈模型,分析了多基地多入多出(MIMO)雷达与多干扰机之间的功率分配和干扰抑制问题。首先,根据功率分配策略,构造了一种具有固定权矢量的超模功率分配博弈框架。同时,建立了一种极大化雷达效用函数的约束优化模型。基于效用函数,分别得到雷达和干扰机的最佳功率分配策略,并证明该超模博弈的纳什均衡的存在性和唯一性。然后,提出一种具有固定权矢量的超模博弈算法,该算法收敛于博弈的纳什均衡。此外,采用自适应波束形成方法抑制互通道干扰,如干扰机到雷达的直达波干扰。为抑制这些干扰,提出一种联合功率分配和波束形成的超模博弈算法。该算法在保证最佳功率分配的同时,提高了MIMO雷达的干扰抑制能力。最后通过数值结果验证了两种算法的优越性和收敛性。
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DOI:
10.1631/FITEE.2000652
CLC number:
TN958
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On-line Access:
2024-08-27
Received:
2023-10-17
Revision Accepted:
2024-05-08
Crosschecked:
2021-06-23