Effective Moving Target Deception Jamming Against Multichannel SAR-GMTI Based on Multiple Jammers

Sun, Qing; Shu, Ting; Tang, Mang; Yu, Kai-Bor; Wang, Yu

doi:10.1109/lgrs.2019.2921678

Cited by 22 publications

(4 citation statements)

References 13 publications

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“…antijamming mainly focuses on the main-lobe, as the side-lobe canceller and blanking can effectively suppress the side-lobe jamming [7]. According to the different jamming effects, the existing main-lobe jamming mainly includes deceptive jamming [8] and suppressive jamming [9]. In recent years, digital radio-frequency memory (DRFM) has been widely applied in radar jamming, where the jammer can intercept radar signals in real-time, and modulate and forward them quickly.…”

Section: Introductionmentioning

confidence: 99%

Deep Neural Network-Based Interrupted Sampling Deceptive Jamming Countermeasure Method

Quan

Sha³

et al. 2022

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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With the development of digital radio frequency memory technology, the main-lobe deception jamming represented by interrupted-sampling repeater jamming (ISRJ) poses a severe challenge to radar. Traditional antijamming methods usually need to estimate the jamming parameters and have the risk of losing target information. For the above problems, this article proposes a deep neural network-based ISRJ recognition and antijamming target detection method which consists of four serial steps. First, the proposed method obtains the time-frequency image set of radar echoes by short-time Fourier transform (STFT). Second, a youonly-look-once (YOLO) model is used to detect the jammed echoes, and the positioning result is automatically corrected to avoid losing the target information. Third, the anti-ISRJ target ranging and velocity measurement datasets are constructed according to the positioning result. Finally, an anti-ISRJ target detection model based on the convolution neural network (CNN) is designed to extract features along different dimensions and obtain the range and velocity of the real targets. Experiments on simulated and measured datasets show that the proposed method has better antijamming detection performance than the traditional method, and does not need to estimate the jamming parameters.

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Section: Introductionmentioning

confidence: 99%

Deep Neural Network-Based Interrupted Sampling Deceptive Jamming Countermeasure Method

Quan

Sha³

et al. 2022

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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show abstract

“…However, SAR system often suffers from complex electromagnetic interference in practical radar imaging. For the purpose of protecting the target from reconnaissance, many jamming methods are designed for SAR system, such as barrage jamming and deceptive jamming [3]. Currently, the anti-barrage jamming technology is relatively mature [4] [6], but deceptive jamming is difficult to identify and suppress since its high fidelity and strong concealment characteristics.…”

Section: і Introductionmentioning

confidence: 99%

An Anti-2D Deceptive Jamming Method for Multi-Baseline Interferometric SAR Based on Co-Localization Jammer

Lang

Tang

Mei

et al. 2022

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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─Aimed at the problem that range-azimuth joint jamming can effectively generate high fidelity false targets in synthetic aperture radar (SAR) images, an anti-2D deceptive jamming method for multi-baseline interferometric SAR is proposed in this paper. The method consists of three steps: identification, classification and suppression. Firstly, the target is detected in the sea clutter background using constant false alarm rate algorithm, and then the false target is identified base on the difference of the spatial position of the target in different SAR images. Secondly, through the analysis of the generating principle of deceptive jamming, the false target is classified by multibaseline interferometric SAR according to partial prior knowledge, which is designed based on the differences between the interferometric phase of the true and false target. Finally, the position of the active jammer is co-located underlying the phase equalization characteristics between multiple baselines and the geometric configuration of the SAR, and the adaptive beamforming method is supplied to suppress the jamming signal. The proposed method has a significantly improved ability to suppress jamming relative to interferometric phase cancellation. The effectiveness of the proposed method is verified by simulation.

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“…Similarly, the deception jamming techniques against the SAR-GMTI system can be categorized as template-based ones and model-based ones. Most of the existing deception jamming techniques are focused on template-based techniques [15]- [18]. Some of the techniques focus on generating jamming signals for static extended scenes, which can be regarded as static jamming and have limited impact on the SAR-GMTI system.…”

Section: Introductionmentioning

confidence: 99%

A Moving Target Deception Jamming Method Based on Fast Azimuth-Domain Block EM Calculation Against SAR-GMTI

et al. 2021

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This paper presents a novel moving target deception jamming method against synthetic aperture radar (SAR)-ground moving target indication (GMTI) based on fast azimuth-domain block EM calculation. In this method, a fast electromagnetic(EM) calculation based on equivalent bistatic scattered fields is used to simulate the scattering characteristics of moving false target, which greatly improves the computational efficiency. With the azimuth-domain block implementation, the jammer's frequency response (JFR) can be calculated by fast searching and interpolating with EM database, and the computation load is further reduced. The implementation and the performance of the proposed method are discussed. Comparing with the traditional methods based on a point model, the proposed method is able to generate more verisimilar moving false targets for different attitudes and resolutions. The simulation experiments are provided to demonstrate the validity of the proposed method.INDEX TERMS Synthetic aperture radar (SAR); deception jamming; moving target; electromagnetic(EM) calculation.

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Effective Moving Target Deception Jamming Against Multichannel SAR-GMTI Based on Multiple Jammers

Cited by 22 publications

References 13 publications

Deep Neural Network-Based Interrupted Sampling Deceptive Jamming Countermeasure Method

Deep Neural Network-Based Interrupted Sampling Deceptive Jamming Countermeasure Method

An Anti-2D Deceptive Jamming Method for Multi-Baseline Interferometric SAR Based on Co-Localization Jammer

A Moving Target Deception Jamming Method Based on Fast Azimuth-Domain Block EM Calculation Against SAR-GMTI

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