Systems Engineering and Electronics ›› 2023, Vol. 45 ›› Issue (9): 2755-2760.doi: 10.12305/j.issn.1001-506X.2023.09.13

• Sensors and Signal Processing • Previous Articles     Next Articles

Intelligent radar jamming decision-making method based on POMDP model

Luwei FENG, Songtao LIU, Huazhi XU   

  1. Department of Information System, Dalian Naval Academy, Dalian 116018, China
  • Received:2022-01-04 Online:2023-08-30 Published:2023-09-05
  • Contact: Songtao LIU

Abstract:

In order to effectively improve the jamming efficiency and accuracy of intelligent radar with unknown working mode of non partners in complex electromagnetic environment, a jamming decision method based on partially observable Markov decision process (POMDP) is proposed. Firstly, according to the working characteristics of intelligent radar, the POMDP model of intelligent radar countermeasure system is constructed, the nonparametric and sample based belief distribution is used to reflect the agent's cognition of the environment, and the Bayesian filter is used to update the agent's belief in the environment. Then, taking the information entropy as the evaluation criterion, make the jammer choose the jamming style with the largest information entropy and try again and again. Finally, the simulation results are compared with the interference decision-making performance of traditional Q-learning method and empirical decision-making method to verify the superiority of the proposed method. The results show that the proposed method can dynamically select the optimal jamming mode according to the changes of unknown radar state, and realize the jamming decision of intelligent radar faster.

Key words: intelligent radar, reinforcement learning, partially observable Markov decision process (POMDP) model, Bayesian filtering

CLC Number: 

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