ECCM Scheme for Countering Main-Lobe Interrupted Sampling Repeater Jamming via Signal Reconstruction and Mismatched Filtering

Tian, Dezhi; Wang, Changjie; Ren, Weili; Liang, Zhennan; Liu, Quanhua

doi:10.1109/jsen.2023.3271116

Cited by 7 publications

(1 citation statement)

References 31 publications

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“…Since the waveform design of conventional coherent radars, such as moving target detection (MTD) radar, usually has a steady pulse repeat period based on energy prioritisation and optimum detection, these waveforms come with inherent flaws, such as low uncertainty, ease of interception and replication, which struggle to deal with more complex jamming, such as intermittent sampling repeater jamming, slice jamming, and spectral dispersion. Currently, technology, such as frequency/waveform agility between coherent pulse trains [1][2][3][4][5][6], frequency diversity [7][8][9], phase coding [10][11][12], and filter design [13][14][15][16], which are the frontier hot research fields of radar antijamming technology, can improve the ability to resist new jamming styles by reducing the intercept ability of radar signals and destroying the correlation of forwarding jamming signals.…”

Section: Introductionmentioning

confidence: 99%

Anti‐interrupted sampling repeater jamming method for random pulse repetition interval and intra‐pulse frequency agile radar

Guo,

Zhan,

et al. 2023

IET Radar Sonar & Navi

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Interrupted sampling repeater jamming can produce numerous active false targets with high fidelity, which is a significant challenge for coherent pulse radar. This poses a threat to the effectiveness of anti‐jamming technology, such as time‐frequency analysis and frequency agility for conventional constant pulse repetition interval (PRI) radar, which will render the radar inoperable to detect and track the actual target. A random PRI and intra‐pulse frequency agile radar waveform with low interception properties is proposed, which can effectively restrict the acquisition of radar waveform parameters by the jammer, destroy the coherence of jamming signals, and capture the range‐dimensional centroid feature of the echo. Accordingly, a jamming identification method based on the scale constrained Gaussian mixture model and an entity radar target energe recovery algorithm based on the neighbourhood weighted maximum entropy are proposed for target detection. Theoretical analysis and simulation experiments demonstrate the effectiveness of the proposal.

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Section: Introductionmentioning

confidence: 99%

Anti‐interrupted sampling repeater jamming method for random pulse repetition interval and intra‐pulse frequency agile radar

Guo,

Zhan,

et al. 2023

IET Radar Sonar & Navi

View full text Add to dashboard Cite

show abstract

Anti-jamming radar waveform design for repeater jammer using reinforcement learning

Aziz,

Habib,

Maud

et al. 2024

Vehicular Communications

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Interrupted sampling repeater jamming suppression based on multiple extended complex‐valued convolutional auto‐encoders

Meng,

Yu,

Wei

2024

IET Radar Sonar & Navi

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Interrupted sampling repeater jamming (ISRJ) with flexible modulation parameters and coherent processing gain seriously threatens the radar detection system. The jamming suppression and target detection performance of existing anti‐jamming methods are limited by strong noise and jamming signals. An ISRJ suppression method combining multiple extended complex‐valued convolutional auto‐encoders (CVCAEs) and compressed sensing (CS) reconstruction is proposed. For the different tasks of parameter estimation and signal denoising, the extended CVCAEs including a complex‐valued convolutional shrinkage network (CVCSNet) and a complex‐valued UNet (CVUNet) are developed. Based on the time‐domain discontinuity of ISRJ signals, the CVCSNet is first used to directly estimate the parameters representing signal components and extract jamming‐free signals from received signals. Then, the extracted signals are denoised using the CVUNet. After that, relying on the denoised signals and the frequency sparsity of de‐chirped target signals, a CS model is established and solved to recover complete target signals for jamming suppression. Utilising the advantages of deep neural networks in weak feature extraction and signal representation, the CVCSNet and CVUNet can effectively improve the signal extraction accuracy and alleviate the limitation of noise on target signal reconstruction. Experimental results verify that the proposed method has superior ISRJ suppression performance and is robust to varying signal‐to‐noise ratios, jamming‐to‐signal ratios and jamming parameters.

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ECCM Scheme for Countering Main-Lobe Interrupted Sampling Repeater Jamming via Signal Reconstruction and Mismatched Filtering

Cited by 7 publications

References 31 publications

Anti‐interrupted sampling repeater jamming method for random pulse repetition interval and intra‐pulse frequency agile radar

Anti‐interrupted sampling repeater jamming method for random pulse repetition interval and intra‐pulse frequency agile radar

Anti-jamming radar waveform design for repeater jammer using reinforcement learning

Interrupted sampling repeater jamming suppression based on multiple extended complex‐valued convolutional auto‐encoders

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