Systems Engineering and Electronics ›› 2026, Vol. 48 ›› Issue (6): 1838-1847.doi: 10.12305/j.issn.1001-506X.2026.06.06

• Sensors and Signal Processing • Previous Articles     Next Articles

Combined ISRJ-SMSP jamming identification based on kernel density estimation and multi-domain feature fusion

Siyu WANG(), Zhiyong SONG(), Zhanling WANG   

  1. College of Electronic Science and Technology,National University of Defense Technology,Changsha 410073,China
  • Received:2025-01-21 Revised:2025-05-05 Accepted:2026-04-09 Online:2026-06-25 Published:2025-07-03
  • Contact: Zhiyong SONG E-mail:2862639595@qq.com;songzhiyong08@nudt.edu.cn

Abstract:

To address the problems of instability and strong dispersion of characteristics in the identification of interrupted sampling repeater jamming (ISRJ), smeared spectrum (SMSP) jamming, and their combined forms, which make single-characteristic methods ineffective and neural network methods limited by insufficient training samples and timeliness issues, a likelihood function construction method is proposed based on kernel density estimation, which achieves accurate identification of single-class and combined jamming by combining the statistical distributions of multiple characteristics, overcoming the problem of unstable combined jamming characteristics. Digital simulation experiments show that under different signal to interference ratio csonditions, the accuracy of the proposed method is more than 10% higher than that of the decision tree method, and the required samples are much fewer than those of the neural network method, providing an effective approach for radar active jamming identification in complex electromagnetic environments.

Key words: interrupted sampling repeater jamming (ISRJ), smeared spectrum (SMSP) jamming, combined jamming, kernel density estimation

CLC Number: 

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