Chaff identification method based on Range‐Doppler imaging feature

Husheng Wang; Baixiao Chen; Dongchen Zhu; Fengsheng Huang; Xiangzhen Yu; Qingzhi Ye; Xiancheng Cheng; Jiaqiu Jing

doi:10.1049/rsn2.12302

journal article Open Access Aug 07, 2022

Chaff identification method based on Range‐Doppler imaging feature

Husheng Wang Baixiao Chen

Dongchen Zhu

Fengsheng Huang Xiangzhen Yu

Qingzhi Ye Xiancheng Cheng Jiaqiu Jing

IET Radar, Sonar & Navigation Vol. 16 No. 11 pp. 1861-1871 · Institution of Engineering and Technology (IET)

View at Publisher Save 10.1049/rsn2.12302

Abstract

Abstract
Chaff is widely used in electronic countermeasures as an effective passive jamming method. This study proposes a chaff identification method that integrates the distribution of distance, Doppler frequency, and power in Range‐Doppler imaging. The traditional radar signal processing method estimates the distance and Doppler frequency, and the mean‐shift algorithm is combined to complete the clustering after the constant false alarm detection. Then, the target and chaff cloud models are modelled in three dimensions: radar cross‐section, range, and Doppler frequency. Using the Neyman–Pearson criterion, three chaff likelihood ratio test detectors are designed based on these assumptions. The three detectors can effectively identify the chaff, and then the theoretical detection probability and influencing factors are analysed. At the same time, the Kullback–Leibler divergence is used to describe the distribution difference between the data to be detected and the theoretical target and chaff. Besides, the different classifiers are used to identify the features of the differences in Kullback–Leibler divergence in three dimensions. Finally, the real‐life chaff datasets verified the excellent recognition rate of the authors’ method for the chaff.

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Details

Published: Aug 07, 2022
Vol/Issue: 16(11)
Pages: 1861-1871
License: View

Authors

H

Husheng Wang