Results 31 to 40 of about 170 (99)
Remote Sensing, 2023 Interrupted-sampling repeater jamming (ISRJ) is a kind of intra-pulse coherent deception jamming that can generate false target peaks in the range profile and interfere with the detection and tracking of real targets.
Huahua Dai +5 more
doaj +2 more sources
Leida xuebao, 2019 Through partial intercepting and multiple forwarding of a radar transmitting signal, Digital Radio Frequency Memory (DRFM)-based Interrupted Sampling Repeater Jamming (ISRJ) possesses advantages of small size, light weight, and flexibility.
ZHOU Chao, LIU Quanhua, HU Cheng
doaj +2 more sources
Remote SensingInterrupted-sampling repeater jamming (ISRJ) is widely used in the field of electronic countermeasures, and can severely affect radar detection. Therefore, the problem of ISRJ suppression is a compelling task.
Xiaoge Wang +6 more
doaj +2 more sources
Leida xuebao, 2023 The interrupted-sampling repeater jammer can sample, store, process and transmit part of the radar transmitter signal multiple times and the fake targets will form on the radar receiver.
Jiyu GAI +5 more
doaj +1 more source
IET Radar, Sonar &Navigation, Volume 17, Issue 12, Page 1796-1811, December 2023., 2023 This paper proposes a random pulse repetition interval and intra‐pulse frequency agile radar waveform and captures the range‐dimensional centroid feature of the echo. Accordingly, a jamming identification method based on the scale constrained Gaussian mixture model (SCGMM) and an entity radar target energy recovery algorithm based on the neighbourhood ...
Tai Guo +3 more
wiley +1 more source
Radar active deception jamming recognition based on Siamese squeeze wavelet attention network
IET Radar, Sonar &Navigation, Volume 17, Issue 12, Page 1886-1898, December 2023., 2023 In actual complex battlefields, the abundant deceptive jamming signals are extremely difficult to obtain and the deceptive jamming signals leveraged by the adversarial jammers are often significantly influenced by noise. To address these challenges a Siamese squeeze wavelet attention network (SSWAN) for radar active deception jamming recognition method
Zhenhua Wu +4 more
wiley +1 more source
Light‐weight deep learning method for active jamming recognition based on improved MobileViT
IET Radar, Sonar &Navigation, Volume 17, Issue 8, Page 1299-1311, August 2023., 2023 In this study, we propose a lightweight neural network model called MobileViT_CA, an improved version of MobileViT, for jamming recognition in small sample scenarios. The algorithm aims at the problems of large model sizes and low recognition accuracy in small sample sizes.
Wenxu Zou, Kai Xie, Jinjian Lin
wiley +1 more source
Flexible blanket synthetic aperture radar jamming using joint frequency and phase modulation
IET Radar, Sonar &Navigation, Volume 17, Issue 7, Page 1129-1141, July 2023., 2023 In this study, a flexible blanket jamming method against SAR is proposed using joint frequency and phase modulation. The proposed method can form two‐dimensional square‐shaped blanket sidelobes in the SAR image by the coded phase modulation in both fast and slow time domain.
Qihua Wu +5 more
wiley +1 more source
Consensus based target tracking against deception jamming in distributed radar networks
IET Radar, Sonar &Navigation, Volume 17, Issue 4, Page 683-700, April 2023., 2023 In this paper, a data‐level anti‐deception jamming target tracking algorithm is proposed for distributed radar network by exploiting the spatial position differences between physical and false targets. Through numerical simulations, the effectiveness of the algorithm is verified, where both the collaborative and non‐collaborative false targets can be ...
Ye Yang +4 more
wiley +1 more source
Quasi-Coherent Noise Jamming to LFM Radar Based on Pseudo-random Sequence Phase-modulation [PDF]
, 2015 A novel quasi-coherent noise jamming method is proposed against linear frequency modulation (LFM) signal and pulse compression radar. Based on the structure of digital radio frequency memory (DRFM), the jamming signal is acquired by the pseudo-random ...
Pan, Y. J., Tai, N., Yuan, N. C.
core +2 more sources