Open AccessJamming effect evaluation method based on radar behavior recognition
Author(s) -
Zhenyong Chu,
Nan Xiao,
Jun Liang
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1629/1/012001
Subject(s) - jamming , radar , computer science , radar jamming and deception , support vector machine , artificial intelligence , dimension (graph theory) , machine learning , pattern recognition (psychology) , pulse doppler radar , radar imaging , telecommunications , mathematics , physics , thermodynamics , pure mathematics
Rapid and accurate evaluation of radar jamming effect is an important link to enhance the effectiveness of cognitive electronic warfare. Based on the correlation between nodes of networked combat systems, this paper proposes a method to judge the jamming effect of radar through behavior recognition. The attacker utilizes its own sensors to perceive the behaviors of victim radar and its cooperative radar, uses support vector machine (SVM) algorithm to identify and classify their behaviors, marks the classification result as jamming effect label, determines the influence of jamming on the working state of radar, and evaluates the jamming effect of the victim radar. The simulation results show that the proposed method has higher accuracy than the traditional method that only considers victim radar’s behaviors, and the kernel function selection and the dimension of behavior parameters are closely related to the accuracy of the evaluation results.