Using lightweight denoising network to suppress multiple barrage jamming in range‐Doppler domain

Abstract Barrage jamming technology poses a significant threat to radar detection functions, yet there is limited research on anti‐multiple barrage jamming using single‐channel radar systems. Addressing this gap, this paper proposes a framework for anti‐multiple barrage jamming based on range‐Doppler domain denoising. This framework first performs pulse compression and Doppler processing on the echo signal to enhance the signal‐to‐jamming ratio. The range‐Doppler spectrum data is then input into a deep denoising network to suppress multiple types of jamming. Additionally, the paper proposes a lightweight deep denoising network comprising a feature extraction module, a jamming suppression module, and a feature fusion module. The feature extraction module preliminarily extracts jamming features using multiple layers of depth‐wise and point‐wise convolution. The jamming suppression module removes noise at various resolutions through a lightweight encoding and decoding structure, effectively suppressing the barrage jamming signal. The feature fusion module uses convolution kernels with different sizes to merge the multiple features output by the jamming suppression module. Simulation results demonstrate that the proposed method effectively suppresses ten types of barrage jamming. Furthermore, a measured dataset is constructed to verify the method’s effectiveness.

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Publication Details

Journal
IET Radar Sonar & Navigation
Published
2024-10-17
DOI
https://doi.org/10.1049/rsn2.12645
Citations
1
Primary Topic
Radar Systems and Signal Processing
Type
article
Field-Weighted Citation Impact
1.30

Funders

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article

Using lightweight denoising network to suppress multiple barrage jamming in range‐Doppler domain

Bin Rao, Dongyang Cheng, Dan Song, Yupei Lin et al.
1 citations
IET Radar Sonar & Navigation
Radar Systems and Signal Processing
1.30
article

Using lightweight denoising network to suppress multiple barrage jamming in range‐Doppler domain

Bin Rao, Dongyang Cheng, Dan Song, Yupei Lin, Minghua Wu, Wei Wang
article en
1 citations

Abstract

Abstract Barrage jamming technology poses a significant threat to radar detection functions, yet there is limited research on anti‐multiple barrage jamming using single‐channel radar systems. Addressing this gap, this paper proposes a framework for anti‐multiple barrage jamming based on range‐Doppler domain denoising. This framework first performs pulse compression and Doppler processing on the echo signal to enhance the signal‐to‐jamming ratio. The range‐Doppler spectrum data is then input into a deep denoising network to suppress multiple types of jamming. Additionally, the paper proposes a lightweight deep denoising network comprising a feature extraction module, a jamming suppression module, and a feature fusion module. The feature extraction module preliminarily extracts jamming features using multiple layers of depth‐wise and point‐wise convolution. The jamming suppression module removes noise at various resolutions through a lightweight encoding and decoding structure, effectively suppressing the barrage jamming signal. The feature fusion module uses convolution kernels with different sizes to merge the multiple features output by the jamming suppression module. Simulation results demonstrate that the proposed method effectively suppresses ten types of barrage jamming. Furthermore, a measured dataset is constructed to verify the method’s effectiveness.

IET Radar Sonar & NavigationVol. 18(11)
Sun Yat-sen University (CN), National University of Defense Technology (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 12%
Radar Systems and Signal Processing
1.30
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Using lightweight denoising network to suppress multiple barrage jamming in range‐Doppler domain — Bin Rao, Dongyang Cheng, et al. · IET Radar Sonar & Navigation (2024) | TGRS Research Map | TGRS