A radar anti-jamming strategy optimisation based on Stackelberg game

Cheng Feng, Xiongjun Fu*, Jian Dong*, Congxia Zhao, Hao Chang, Ping Lang, Teng Pan

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)

Abstract

Radar is an important sensor in electromagnetic spectrum warfare. Its confrontation with naval vessels has become increasingly competitive in recent years. However, current radar anti-jamming methods are limited to some extent in complex electromagnetic environments, which poses a severe challenge to radar's detection and anti-jamming capabilities. To improve the anti-jamming capacity of radar, the authors propose a Stackelberg game-based optimisation method to enhance the decision-making of anti-jamming strategies. First, we analyse the radar's winning conditions by considering the temporal constraints of non-real-time radar recognition and preparation actions and construct the radar's actual utility matrix. Second, we construct a Stackelberg game-based model under the condition of a certain recognition probability, and update the recognition probability and recognition interval during the game. Finally, we discuss the conditions under which the radar can obtain a positive benefit in the game and compare the benefit to the reinforcement learning optimisation method. The simulation experimental results show that the proposed strategy can significantly improve the radar's winning probability in the confrontation.

Original languageEnglish
Pages (from-to)1248-1258
Number of pages11
JournalIET Radar, Sonar and Navigation
Volume17
Issue number8
DOIs
Publication statusPublished - Aug 2023

Keywords

  • game theory
  • optimisation
  • radar

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