A Novel Chaff Cloud Recognition Method Based on Wideband Polarization Radar

Mingling Li, Ping Lang, Xiongjun Fu*, Jian Dong, Chang Liu, Jiahuan Jiang

*Corresponding author for this work

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

2 Citations (Scopus)

Abstract

Chaff cloud recognition (CCR) is a vital anti-jamming way in modern warfare. The existing recognition methods have poor performance in complex electromagnetic environment. Therefore, in this paper, a novel convolutional neural network based CCR (CNN-CCR) method relying on wideband polarization radar is proposed. First, the chaff cloud echo is simulated at different stages, in different polarization types and sea conditions. Second, the CNN-CCR is built, whose inputs are the range profile sequences on the same range unit detected by the greatest of constant false alarm rate detector (GO-CFAR). Finally, the effectivity of our proposed method is verified by the simulated data. The experimental results show that our proposed method can effectively address the CCR in high sea conditions and high jamming-to-signal ratios (JSR).

Original languageEnglish
Title of host publication2021 CIE International Conference on Radar, Radar 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1927-1930
Number of pages4
ISBN (Electronic)9781665498142
DOIs
Publication statusPublished - 2021
Event2021 CIE International Conference on Radar, Radar 2021 - Haikou, Hainan, China
Duration: 15 Dec 202119 Dec 2021

Publication series

NameProceedings of the IEEE Radar Conference
Volume2021-December
ISSN (Print)1097-5764
ISSN (Electronic)2375-5318

Conference

Conference2021 CIE International Conference on Radar, Radar 2021
Country/TerritoryChina
CityHaikou, Hainan
Period15/12/2119/12/21

Keywords

  • chaff cloud modeling
  • chaff cloud recognition
  • convolutional neural network
  • wideband polarization radar

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