Anti-sweep-jamming Method for PD Radar Based on Variational Signal Decomposition

doi:10.12382/bgxb.2023.0037

Abstract

Abstract:

When the pulse Doppler radar is subjected to sweep-jamming, its receiver channel is saturated by the jamming signal, which causes the radar false alarm or miss alarm. Aiming at the above problem, an IF signal model of pulse Doppler radar under sweep-jamming is established, and a separation method of target echo and jamming based on signal variational decomposition (SVD) is proposed. The proposed method uses total variation regularization to decompose the IF signal into two components: pulse and low-frequency narrowband signal. The pulse corresponds to the target echo, while the low-frequency narrowband signal corresponds to the jamming. The ow-frequency narrowband signal and noise are eliminated, and the pulse is retained and processed to detect the real target. The effectiveness of SVD was verified by simulation. The results show that the method can still effectively separate the target echo and jamming under the condition that signal-to-jamming ratio is lower than -20dB, and greatly improve the target detection ability of pulse Doppler radar under the effect of sweep-jamming.

Key words: pulse Doppler radar, sweep-jamming, anti-jamming method, signal variational decomposition, alternating direction method of multipliers

CLC Number:

TJ43⁺4.1

CHEN Qile, QIAN Pengfei, KONG Zhijie, QIAO Caixia, ZHANG Ruiheng. Anti-sweep-jamming Method for PD Radar Based on Variational Signal Decomposition[J]. Acta Armamentarii, 2024, 45(6): 2076-2084.

Figures/Tables 13

Fig.1 Time-frequency characteristics of radar intermediate frequency signal

Fig.2 Effect of sweep jamming

Fig.3 Scheme of anti-sweep-jamming method

Fig.4 Curve of MC function

Fig.5 Comparison of MC regularizer and L1 norm regularizer

Fig.6 Schematic diagram of variational regularization

Fig.7 Flow chart of VSD algorithm

Fig.8 Processing results of VSD algorithm

Fig.9 Simulated results of different algorithms

Fig.10 Range-Doppler simulated results based on different algorithms

Fig.11 Experimental scenario

Fig.12 Outputs of radar after correlation demodulation

Fig.13 Simulated results of anti-jamming success rates of different methods

References 25

[1]	于洪海, 闫晓鹏, 贾瑞丽, 等. M序列伪码调相脉冲多普勒引信抗干扰性能研究[J]. 兵工学报, 2020, 41(3): 417-425. doi: 10.3969/j.issn.1000-1093.2020.03.001
	YU H H, YAN X P, JIA R L, et al. Research on anti-jamming performance of M-sequence pseudo-random code phase modulation pulse doppler fuze[J]. Acta Armamentarii, 2020, 41(3): 417-425. (in Chinese) doi: 10.3969/j.issn.1000-1093.2020.03.001
[2]	张亮, 王国宏, 张翔宇, 等. 基于多阶次二维分数阶傅里叶变换的频谱弥散干扰抑制算法[J]. 兵工学报, 2020, 41(9): 1826-1836. doi: 10.3969/j.issn.1000-1093.2020.09.015
	ZHANG L, WANG G H, ZHANG X Y, et al. Smeared spectrum jamming suppression algorithm based on multiple orders 2D-FRFT[J]. Acta Armamentarii, 2020, 41(9): 1826-1836. (in Chinese) doi: 10.3969/j.issn.1000-1093.2020.09.015
[3]	陈建军, 王盛利. 基于匹配傅立叶变换的超高速运动目标检测[J]. 兵工学报, 2007, 28(11): 1315-1319.
	CHEN J J, WANG S L. Detection of ultra-high speed moving target based on matched fourier transform[J]. Acta Armamentarii, 2007, 28(11): 1315-1319. (in Chinese)
[4]	赵惠昌. 无线电引信设计原理与方法[M]. 北京: 国防工业出版社, 2012:147-161.
	ZHAO H C. Fundamentals and methodology of radio fuze[M]. Beijing: National Defense Industry Press, 2012:147-161. (in Chinese)
[5]	刘少坤, 闫晓鹏, 栗苹, 等. 基于码元重构的伪码调相脉冲多普勒引信干扰信号设计[J]. 兵工学报, 2018, 39(6): 1088-1094. doi: 10.3969/j.issn.1000-1093.2018.06.007
	LIU S K, YAN X P, LI P, et al. Design of jamming signal on pseudo-random code phase-modulation and pulse doppler combined fuze based on code reconstruction[J]. Acta Armamentarii, 2018, 39(6): 1088-1094. (in Chinese)
[6]	李剑锋, 闫晓鹏, 郝新红, 等. 基于生成对抗网络的伪码调相脉冲多普勒引信引导式干扰方法[J]. 兵工学报, 2022, 43(10): 2534-2544.
	LI J F, YAN X P, HAO X H, et al. Guided jamming method for pseudo-code phase-modulated pulse doppler fuze based on generative adversarial nets[J]. Acta Armamentarii, 2022, 43(10): 2534-2544. (in Chinese) doi: 10.12382/bgxb.2021.0504
[7]	ANDREW, DARDINE. ALQ-218(V) (ICAP III)[J]. Electronic Warfare Forecast, 2012: 23-28.
[8]	周新刚, 赵惠昌, 涂友超. 脉冲多普勒引信抗干扰性能评判方法和仿真[J]. 系统仿真学报, 2011, 23(1): 207-211.
	ZHOU X G, ZHAO H C, TU Y C. ECCM evaluation and simulation of pulse doppler fuze[J]. Journal of System Simulation, 2011, 23(1): 207-211. (in Chinese)
[9]	周新刚, 赵惠昌, 涂友超, 等. 基于多普勒效应的伪码调相及其与PAM复合引信的抗噪声性能分析[J]. 电子与信息学报, 2008, 30(8): 1874-1877.
	ZHOU X G, ZHAO H C, TU Y C, et al. Performance analysis concerning anti-noise for pseudo-random code phase modulation and pulse amplitude modulation combined fuze based on doppler effect[J]. Journal of Electronics & Information Technology, 2008, 30(8): 1874-1877. (in Chinese)
[10]	涂友超, 赵惠昌, 周新刚. 噪声调频干扰下伪码调相引信启动概率分析[J]. 南京理工大学学报, 2011, 35(2): 252-256.
	TU Y C, ZHAO H C, ZHOU X G. Analysis on starting probability of pseudo-random binary-phase-coded fuze under noise FM jamming[J]. Journal of Nanjing University of Science and Technology, 2011, 35(2): 252-256. (in Chinese)
[11]	李泽, 栗苹, 郝新红, 等. 脉冲多普勒引信抗有源噪声干扰性能研究[J]. 兵工学报, 2015, 36(6): 1001-1008. doi: 10.3969/j.issn.1000-1093.2015.06.006
	LI Z, LI P, HAO X H, et al. Anti-active noise jamming performance of pulse doppler fuze[J]. Acta Armamentarii, 2015, 36(6): 1001-1008. (in Chinese) doi: 10.3969/j.issn.1000-1093.2015.06.006
[12]	代健, 晏祺, 闫晓鹏, 等. 基于模糊c-均值增量更新的脉冲多普勒引信干扰与目标信号识别[J]. 兵工学报, 2018, 39(9): 1711-1718. doi: 10.3969/j.issn.1000-1093.2018.09.006
	DAI J, YAN Q, YAN X P, et al. Recognition of jamming and target signal for pulse doppler fuze based on fcm algorithm with incremental update[J]. Acta Armamentarii, 2018, 39(9): 1711-1718. (in Chinese) doi: 10.3969/j.issn.1000-1093.2018.09.006
[13]	代健, 李泽, 郝新红, 等. 基于目标联合特征提取的脉冲多普勒引信抗干扰方法[J]. 兵工学报, 2019, 40(2): 225-233. doi: 10.3969/j.issn.1000-1093.2019.02.001
	DAI J, LI Z, HAO X H, et al. Anti-jamming method for pulse doppler fuze based on joint feature extraction of target signal[J]. Acta Armamentarii, 2019, 40(2): 225-233. (in Chinese) doi: 10.3969/j.issn.1000-1093.2019.02.001
[14]	DAI J, HAO X H, LI Z, et al. Adaptive target and jamming recognition for the pulse doppler radar fuze based on a time-frequency joint feature and an online-updated naive bayesian classifier with minimal risk[J]. Defence Technology, 2022, 18(3): 457-466. doi: 10.1016/j.dt.2021.02.008
[15]	DAI J, HAO X H, LIU Q, et al. Repeater jamming suppression method for pulse doppler fuze based on identity recognition and chaotic encryption[J]. Defence Technology, 2021, 17(3): 1002-1012. doi: 10.1016/j.dt.2020.06.023
[16]	DAUBECHIES I, LU J F, WU H T. Synchrosqueezed wavelet transforms: an empirical mode decomposition-like tool[J]. Applied and Computational Harmonic Analysis, 2011, 30(2): 243-261.
[17]	HUANG N E, SHEN Z, LONG S R, et al. The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis[J]. Proceedings of the Royal Society of London. Series A: Mathematical Physical & Engineering Sciences, 1998, 454(1971): 903-995.
[18]	SONG C Y, XU J M, ZHAN Y. A method for specific emitter identification based on empirical mode decomposition[C]∥Proceedings of the 2010 IEEE International Conference on Wireless Communications, Networking and Information Security. Beijing, China: IEEE, 2010: 54-57.
[19]	DRAGOMIRETSKIY K, ZOSSO D. Variational Mode Decomposition[J]. IEEE Transactions on Signal Processing, 2013, 62(3): 531-544.
[20]	STALLONE A, CICONE A, MATERASSI M. New insights and best practices for the successful use of empirical mode decomposition, iterative filtering and derived algorithms[J]. Scientific Reports, 2020, 10(1): 156161.
[21]	SINGH P. Novel Fourier quadrature transforms and analytic signal representations for nonlinear and non-stationary ime-series analysis[J]. Royal Society Open Science, 2018, 11(5): 181131.
[22]	SELESNICK I, LANZA A, MORIGI S. Non-convex total variation regularization for convex denoising of signals[J]. Journal of Mathematical Imaging and Vision, 2020, 62(6): 825-841.
[23]	CICONE A. Iterative filtering as a direct method for the decomposition of nonstationary signals[J]. Numerical Algorithms, 2020, 85(3): 811-827.
[24]	ZHANG S, XIE W, ZHU H, et al. Combined eigenvector analysis and independent component analysis for multi-component periodic interferences suppression in PRCPM-PD detection system[J]. IEEE Access, 2017, 5: 12552-12562.
[25]	CHEN J J, ZHAO H Z, QIU W. A novel CFAR threshold estimated method for coherent integration detector of PD radar seeker[C] ∥Proceedings of the 2011 IEEE CIE International Conference on Radar, Chengdu, China: IEEE, 2011: 1712-1715.