Radar Active Jamming Signal Identification Method Based on Time-frequency Image Features

Wanbing Hao, Xiaoyi Feng, Xiaoyue Jiang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

In this paper, the Choi-Williams method is used to describe five typical jamming signals, and the grayscale images of the time-frequency two-dimensional distribution of the jamming signals are obtained. The contour information is maximally enhanced by median filtering and image segmentation processing algorithms for the grayscale images. The effective time-frequency domain feature parameter set is extracted and the dimensionality reduction is done. SVM is used to identify typical radar active jamming signals and provide a priori information for radar anti-jamming. This paper verifies the adopted method by MATLAB simulation experiments and analyzes the performance and feasibility of the adopted method.

Original languageEnglish
Title of host publicationProceedings - 2023 2nd International Conference on Image Processing and Media Computing, ICIPMC 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages64-70
Number of pages7
ISBN (Electronic)9798350326611
DOIs
StatePublished - 2023
Event2nd International Conference on Image Processing and Media Computing, ICIPMC 2023 - Xi�an, China
Duration: 26 May 202328 May 2023

Publication series

NameProceedings - 2023 2nd International Conference on Image Processing and Media Computing, ICIPMC 2023

Conference

Conference2nd International Conference on Image Processing and Media Computing, ICIPMC 2023
Country/TerritoryChina
CityXi�an
Period26/05/2328/05/23

Keywords

  • active jamming
  • jamming identification
  • parameter estimation
  • time-frequency Image

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