Anti-interrupted Sampling Repeater Jamming Method Based on down-sampling Processing Blind Source Separation
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摘要: 间歇采样转发干扰(ISRJ)作为一种新型相干干扰，兼具压制和欺骗效果，对雷达探测造成了极大的威胁。随着数字射频存储器的发展，其轻量化特性使得目标能够携带ISRJ干扰机产生自卫干扰，因此传统的盲源分离等空域抗干扰方法难以进行有效抑制。该文针对间歇采样转发干扰抑制问题，提出了一种基于下采样处理盲源分离的抗间歇采样转发干扰方法。首先对单路含干扰的回波信号进行解线频调处理，并对其进行下采样，通过改变下采样保留位置得到多路下采样输出信号，其中的干扰和目标成分满足盲源分离的线性混合模型；随后对多路下采样输出进行盲源分离，从而分离出干扰分量和目标分量，并通过脉冲压缩和目标检测输出目标回波信号，达到抗干扰效果。仿真结果表明，该方法在自卫干扰场景下，能够有效抑制直接转发、重复转发以及频移转发等多种ISRJ类型；此外无需对ISRJ参数进行高精度估计，受干扰能量和切片宽度影响更小，更有利于工程应用。Abstract:
Objective Advancements in radar jamming technology have made coherent jamming generated by Digital Radio Frequency Memory (DRFM) a significant threat to radar detection. This type of jamming exhibits considerable spectral overlap with target echo signals and shares similar time-frequency characteristics. Even after matched filtering is applied to the received signal, the jamming can still achieve high gain. Among various forms, Interrupted Sampling Repeater Jamming (ISRJ) presents both suppression and deception effects, combined with high agility and diversity, posing a considerable challenge to radar detection systems. Existing ISRJ suppression methods face several limitations, including reliance on prior knowledge of jamming parameters, reduced robustness against ISRJ style variations, and the need for advance detection of ISRJ forwarding strategies. Blind Source Separation (BSS) can extract source signals based solely on the received mixture, without requiring prior information about the source or transmission parameters. BSS is widely applied in radar anti-jamming scenarios due to its high robustness. However, as ISRJ is primarily deployed for self-defense jamming, conventional BSS methods lack spatial degrees of freedom and cannot effectively suppress such interference. To address this limitation, this study proposes a down-sampling BSS method for ISRJ suppression. By applying dechirping and down-sampling to the echo signal, varying the down-sampling retention positions produces multiple down-sampled output signals. Theoretical analysis demonstrates that the jamming and target signals in these multi-channel down-sampled outputs satisfy the linear mixing model required for BSS. BSS is subsequently applied to separate the ISRJ and target components. This study introduces BSS into ISRJ suppression, providing a highly robust approach that does not depend on prior knowledge, with theoretical validation supporting the method. Methods In self-defense ISRJ scenarios, the jamming and target share the same azimuth angle, resulting in a loss of spatial freedom in the received signal. Therefore conventional BSS methods based on linear instantaneous mixing models are no longer applicable. When all source signals originate from the same azimuth, the rank of the receiving array manifold matrix reduces to one, causing the array receiving model to degenerate into an effective single-channel system. However, BSS requires multiple mixed signals to perform signal separation. To overcome this limitation, this study proposes a down-sampling BSS method for ISRJ suppression. The approach begins by applying oversampling to the received signal, followed by dechirp processing of the single-channel echo signal that contains both jamming and target components. Through conjugate multiplication of the echo signal with a reference signal, both the ISRJ and target echo are converted into sinusoidal signals with fixed frequencies and time-domain windowing characteristics. Subsequently, the signal undergoes down-sampling, during which multiple down-sampled output signals are generated by varying the retention positions of the sampled data. This process effectively restores the degrees of freedom required for separation. Theoretical analysis confirms that the ISRJ and target components in the down-sampled output signals satisfy the linear mixing model necessary for BSS processing. The multi-channel down-sampled signals are then used as input for BSS, enabling the separation of jamming and target components. Pulse compression is performed via Fourier transform to enhance detection resolution. Finally, target detection is conducted on each separated component to isolate the jamming signals and recover the target echoes, thereby achieving anti-jamming performance. Results and Discussions The key innovation of the proposed method is the application of BSS to ISRJ suppression, eliminating the requirement for precise estimation of ISRJ parameters and demonstrating high robustness. Furthermore, a single-frequency, single-channel BSS approach based on down-sampling is presented, which has potential application beyond jamming suppression. Simulation results confirm that the proposed method effectively separates ISRJ from the target signal ( Fig. 7 ) and suppresses multiple ISRJ types, including direct forwarding ISRJ (Fig. 5 ), repeated forwarding ISRJ (Fig. 7 ), and frequency-shift forwarding ISRJ (Fig. 6 ). Comparative experiments demonstrate that this method resolves the problem of degraded suppression performance caused by the jamming azimuth in existing BSS approaches. Compared with conventional ISRJ suppression algorithms, the proposed method maintains stable performance regardless of ISRJ slice width or jamming power. Moreover, it achieves superior output Signal-to-Interference-plus-Noise Ratio (SINR), confirming its effectiveness in enhancing anti-jamming capabilities.Conclusions To address the threat posed by ISRJ to radar systems, this study proposes an ISRJ suppression method based on down-sampling BSS. By applying down-sampling and dechirp processing to the received signal, multiple signals are generated, and the Joint Approximate Diagonalization of Eigenmatrices (JADE) BSS algorithm is employed to separate the jamming and target components. This method overcomes the dependence of conventional BSS approaches on spatial separability and remains effective in self-defense jamming scenarios where the jamming and target share the same azimuth. The proposed method demonstrates effective suppression of various ISRJ types, including direct forwarding, repeated forwarding, and frequency-shift forwarding. Compared with existing ISRJ suppression techniques, this approach provides improved anti-jamming performance, as it is largely unaffected by ISRJ slice width, does not require prior knowledge of jamming parameters, and exhibits minimal sensitivity to variations in Signal-to-Interference Ratio (SIR). -
[1] ZHANG Jindong, ZHU Daiyin, and ZHANG Gong. New antivelocity deception jamming technique using pulses with adaptive initial phases[J]. IEEE Transactions on Aerospace and Electronic Systems, 2013, 49(2): 1290–1300. doi: 10.1109/TAES.2013.6494414. [2] FENG Dejun, XU Letao, PAN Xiaoyi, et al. Jamming wideband radar using interrupted-sampling repeater[J]. IEEE Transactions on Aerospace and Electronic Systems, 2017, 53(3): 1341–1354. doi: 10.1109/TAES.2017.2670958. [3] HANBALI S B S. Technique to counter improved active echo cancellation based on ISRJ with frequency shifting[J]. IEEE Sensors Journal, 2019, 19(20): 9194–9199. doi: 10.1109/JSEN.2019.2925004. [4] WU Qihua, ZHAO Feng, AI Xiaofeng, et al. Two-dimensional blanket jamming against ISAR using nonperiodic ISRJ[J]. IEEE Sensors Journal, 2019, 19(11): 4031–4038. doi: 10.1109/JSEN.2019.2897363. [5] 吴传章, 陈伯孝. 间歇非均匀采样转发干扰产生方法研究[J]. 系统工程与电子技术, 2021, 43(1): 1–10. doi: 10.3969/j.issn.1001-506X.2021.01.01.WU Chuanzhang and CHEN Boxiao. Study on generating method of interrupted non-uniform sampling repeater jamming[J]. Systems Engineering and Electronics, 2021, 43(1): 1–10. doi: 10.3969/j.issn.1001-506X.2021.01.01. [6] LIU Zhidong, ZHANG Qun, LI Guangming, et al. Improved blanket jamming against ISAR based on nonperiodic interrupted sampling modulation[J]. IEEE Sensors Journal, 2021, 21(1): 430–437. doi: 10.1109/JSEN.2020.3014650. [7] RIIHONEN T, KORPI D, RANTULA O, et al. Inband full-duplex radio transceivers: A paradigm shift in tactical communications and electronic warfare?[J]. IEEE Communications Magazine, 2017, 55(10): 30–36. doi: 10.1109/MCOM.2017.1700220. [8] XIAO Jie, WEI Xizhang, and SUN Jia. Interrupted-sampling multi-strategy forwarding jamming with amplitude constraints based on simultaneous transmission and reception technology[J]. Digital Signal Processing, 2024, 147: 104416. doi: 10.1016/j.dsp.2024.104416. [9] 余涛, 周正春, 杜小勇, 等. 一种基于完全互补码波形设计的抗间歇式采样转发干扰方法[J]. 电子与信息学报, 2023, 45(11): 3896–3905. doi: 10.11999/JEIT230331.YU Tao, ZHOU Zhengchun, DU Xiaoyong, et al. An anti-interrupted sampling repeater jamming method based on complete complementary code waveform design[J]. Journal of Electronics & Information Technology, 2023, 45(11): 3896–3905. doi: 10.11999/JEIT230331. [10] DAI Huahua, ZHAO Yingxiao, SU Hanning, et al. Research on an intra-pulse orthogonal waveform and methods resisting interrupted-sampling repeater jamming within the same frequency band[J]. Remote Sensing, 2023, 15(14): 3673. doi: 10.3390/rs15143673. [11] GUO Tai, ZHAN Haihong, SU Xingde, et al. Anti‐interrupted sampling repeater jamming method for random pulse repetition interval and intra‐pulse frequency agile radar[J]. IET Radar, Sonar & Navigation, 2023, 17(12): 1796–1811. doi: 10.1049/rsn2.12465. [12] WANG Xiaoge, LI Binbin, LIU Weijian, et al. Anti-interrupted sampling repeater jamming based on intra-pulse frequency modulation slope agile radar waveform joint FrFT[J]. Digital Signal Processing, 2024, 147: 104418. doi: 10.1016/j.dsp.2024.104418. [13] ZHOU Kai, LI Dexin, SU Yi, et al. Joint design of transmit waveform and mismatch filter in the presence of interrupted sampling repeater jamming[J]. IEEE Signal Processing Letters, 2020, 27: 1610–1614. doi: 10.1109/LSP.2020.3021667. [14] 王福来, 庞晨, 殷加鹏, 等. 一种多普勒容忍的抗间歇采样转发干扰恒模互补波形和接收滤波器联合设计方法[J]. 雷达学报, 2022, 11(2): 278–288. doi: 10.12000/JR22020.WANG Fulai, PANG Chen, YIN Jiapeng, et al. Joint design of Doppler-tolerant complementary sequences and receiving filters against interrupted sampling repeater jamming[J]. Journal of Radars, 2022, 11(2): 278–288. doi: 10.12000/JR22020. [15] WANG Fulai, LI Nanjun, PANG Chen, et al. Complementary sequences and receiving filters design for suppressing interrupted sampling repeater jamming[J]. IEEE Geoscience and Remote Sensing Letters, 2022, 19: 4022305. doi: 10.1109/LGRS.2022.3156164. [16] ZHANG Yang, YU Lei, and WEI Yinsheng. Interrupted sampling repeater jamming countermeasure technology based on random interpulse frequency coding LFM signal[J]. Digital Signal Processing, 2022, 131: 103755. doi: 10.1016/j.dsp.2022.103755. [17] WEI Song, FANG Yuyuan, SONG Yuxiao, et al. Joint jam perception and adaptive waveform optimization for anti-interrupted sampling repeater jamming[J]. IEEE Transactions on Aerospace and Electronic Systems, 2024, 60(1): 1129–1147. doi: 10.1109/TAES.2023.3334255. [18] YUAN Hui, WANG Chunyang, LI Xin, et al. A method against interrupted-sampling repeater jamming based on energy function detection and band-pass filtering[J]. International Journal of Antennas and Propagation, 2017, 2017: 6759169. doi: 10.1155/2017/6759169. [19] CHEN Jian, WU Wenzhen, XU Shiyou, et al. Band pass filter design against interrupted‐sampling repeater jamming based on time‐frequency analysis[J]. IET Radar, Sonar & Navigation, 2019, 13(10): 1646–1654. doi: 10.1049/iet-rsn.2018.5658. [20] WANG Zijian, LI Jiamu, YU Wenbo, et al. Energy function‐guided histogram analysis for interrupted sampling repeater jamming suppression[J]. Electronics Letters, 2023, 59(7): e12778. doi: 10.1049/ell2.12778. [21] ZHOU Chao, LIU Quanhua, and CHEN Xinliang. Parameter estimation and suppression for DRFM‐based interrupted sampling repeater jammer[J]. IET Radar, Sonar & Navigation, 2018, 12(1): 56–63. doi: 10.1049/iet-rsn.2017.0114. [22] LU Lu and GAO Meiguo. An improved sliding matched filter method for interrupted sampling repeater jamming suppression based on jamming reconstruction[J]. IEEE Sensors Journal, 2022, 22(10): 9675–9684. doi: 10.1109/JSEN.2022.3159561. [23] WU Wenzhen, ZOU Jiangwei, CHEN Jian, et al. False-target recognition against interrupted-sampling repeater jamming based on integration decomposition[J]. IEEE Transactions on Aerospace and Electronic Systems, 2021, 57(5): 2979–2991. doi: 10.1109/TAES.2021.3068443. [24] CHEN Xiaoying and CHEN Baixiao. Interrupted-sampling repeater jamming suppression based on iterative decomposition[J]. Digital Signal Processing, 2023, 138: 104059. doi: 10.1016/j.dsp.2023.104059. [25] MENG Yunyun, YU Lei, and WEI Yinsheng. Interrupted sampling repeater jamming suppression based on multiple extended complex-valued convolutional auto-encoders[J]. IET Radar, Sonar & Navigation, 2024, 18(8): 1274–1290. doi: 10.1049/rsn2.12568. [26] HUANG Quan, WEI Shaopeng, and ZHANG Lei. Interpretable ADMM-CSNet for interrupted sampling repeater jamming suppression[J]. Digital Signal Processing, 2025, 156: 104850. doi: 10.1016/j.dsp.2024.104850. [27] ZHANG Yang, WEI Yinsheng, and YU Lei. Interrupted sampling repeater jamming recognition and suppression based on phase-coded signal processing[J]. Signal Processing, 2022, 198: 108596. doi: 10.1016/j.sigpro.2022.108596. [28] DUAN Jia, ZHANG Lei, WU Yifeng, et al. Interrupted-sampling repeater jamming suppression with one-dimensional semi-parametric signal decomposition[J]. Digital Signal Processing, 2022, 127: 103546. doi: 10.1016/j.dsp.2022.103546. [29] HUANG Quan, WEI Shaopeng, and ZHANG Lei. Robust adaptive time-frequency filtering for frequency shift jamming suppression[J]. IEEE Transactions on Aerospace and Electronic Systems, 2023, 59(6): 7963–7976. doi: 10.1109/TAES.2023.3297559. [30] TIAN Dezhi, WANG Changjie, REN Wei, et al. ECCM scheme for countering main-lobe interrupted sampling repeater jamming via signal reconstruction and mismatched filtering[J]. IEEE Sensors Journal, 2023, 23(12): 13261–13271. doi: 10.1109/JSEN.2023.3271116. [31] 于雷, 刘一品, 位寅生. 基于信干噪比最大化的盲提取抗主瓣干扰方法[J]. 系统工程与电子技术, 2024, 46(9): 2968–2979. doi: 10.12305/j.issn.1001-506X.2024.09.09.YU Lei, LIU Yipin, and WEI Yinsheng. Anti-mainlobe jamming method via blind extraction based on maximizing SINR[J]. Systems Engineering and Electronics, 2024, 46(9): 2968–2979. doi: 10.12305/j.issn.1001-506X.2024.09.09. [32] HINDERER S. Blind source separation of radar signals in time domain using deep learning[C]. Proceedings of 2022 23rd International Radar Symposium (IRS), Gdansk, Poland, 2022: 486–491. doi: 10.23919/IRS54158.2022.9904990. [33] LUO Weilin, JIN Hongbin, LI Hao, et al. Radar main-lobe jamming suppression based on adaptive opposite fireworks algorithm[J]. IEEE Open Journal of Antennas and Propagation, 2021, 2: 138–150. doi: 10.1109/OJAP.2020.3036878. [34] LEI Zhenshuo, QU Qizhe, CHEN Hao, et al. Mainlobe jamming suppression with space–time multichannel via blind source separation[J]. IEEE Sensors Journal, 2023, 23(15): 17042–17053. doi: 10.1109/JSEN.2023.3278709. [35] GE Mengmeng, CUI Guolong, YU Xianxiang, et al. Mainlobe jamming suppression with polarimetric multi-channel radar via independent component analysis[J]. Digital Signal Processing, 2020, 106: 102806. doi: 10.1016/j.dsp.2020.102806. [36] 高霞, 全英汇, 李亚超, 等. 基于BSS的FDA-MIMO雷达主瓣欺骗式干扰抑制方法[J]. 系统工程与电子技术, 2020, 42(9): 1927–1934. doi: 10.3969/j.issn.1001-506X.2020.09.07.GAO Xia, QUAN Yinghui, LI Yachao, et al. Main-lobe deceptive jamming suppression with FDA-MIMO radar based on BSS[J]. Systems Engineering and Electronics, 2020, 42(9): 1927–1934. doi: 10.3969/j.issn.1001-506X.2020.09.07. [37] WAN Pengfei, LIAO Guisheng, XU Jingwei, et al. SMSP mainlobe jamming suppression with FDA-MIMO radar based on FastICA algorithm[J]. Sensors, 2023, 23(12): 5619. doi: 10.3390/s23125619. [38] CARDOSO J F and SOULOUMIAC A. Blind beamforming for non-Gaussian signals[J]. IEE Proceedings F (Radar and Signal Processing), 1993, 140(6): 362–370. doi: 10.1049/ip-f-2.1993.0054. -
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