Jamming suppression by blind source separation: from a perspective of spatial band-pass filters

doi:10.23919/JSEE.2025.000005

Journal of Systems Engineering and Electronics ›› 2025, Vol. 36 ›› Issue (5): 1169-1176.doi: 10.23919/JSEE.2025.000005

• DEFENCE ELECTRONICS TECHNOLOGY • Previous Articles

Jamming suppression by blind source separation: from a perspective of spatial band-pass filters

Quanhua LIU(), Xinran SUI(), Xinliang CHEN(), Zhennan LIANG(), Rui ZHU()

Radar Technology Research Institute, Beijing Institute of Technology, Beijing 100081, China

Received:2024-07-10 Accepted:2024-12-03 Online:2025-10-18 Published:2025-10-24
Contact: Xinliang CHEN E-mail:liuquanhua@bit.edu.cn;sxr051@yeah.net;chenxinliang@bit.edu.cn;liangzhennan@bit.edu.cn;zhurui_bit2020@bit.edu.cn
About author:
LIU Quanhua was born in 1982. He received his B.S. degree in telecommunications engineering from Beijing Information Technology Institute, Beijing, China, in 2005, and Ph.D. degree in target detection and recognition from Beijing Institute of Technology (BIT), Beijing, China, in 2010. From 2010 to 2011, he was a post-doctoral researcher with the Antenna and Microwave Laboratory, The University of Tennessee, Knoxville, TN, USA. Since 2011, he has been a faculty member with BIT, where he is currently a full professor. His research interests include wideband radar signal processing and distributed array radar system. E-mail: liuquanhua@bit.edu.cn

SUI Xinran was born in 1998. He received his B.E. degree in electronic and information engineering at Beijing Institute of Technology (BIT), Beijing, China, in 2021. He is currently pursing his M.S. degree at BIT. His research interests include distributed array radar signal processing and jamming suppression. E-mail: sxr051@yeah.net

CHEN Xinliang was born in 1984. He received his B.E. degree in electrical science and technology from the School of Physics Science and Technology, Wuhan University, in 2005, and Ph.D. degree from the Institute of Semiconductor, Chinese Academic of Sciences, in 2010. He was a postdoctoral researcher with the School of Information and Electronics, Beijing Institute of Technology (BIT) from 2010 to 2012. He joined BIT in 2012 as a lecturer. His research interests include radar signal processing and radar target detection. E-mail: chenxinliang@bit.edu.cn

LIANG Zhennan was born in in 1992. He received his B.S. degree in electronic science and engineering from Southeast University, Nanjing, China, in 2014, and Ph.D. degree from the School of Information and Electronics, Beijing Institute of Technology (BIT), Beijing, China, in 2020. From 2020, he was a post-doctoral researcher at BIT. At present, he is an assistant professor with BIT. His research interests include digital phased array radar system and wideband radar signal processing. E-mail: liangzhennan@bit.edu.cn

ZHU Rui was born in 1989. He received his B.S. degree in electronics engineering from Tsinghua University, Beijing, China, in 2011, and M.S. and Ph.D. degrees in electrical engineering from the University of California at Los Angeles, Los Angeles, CA, USA, in 2013 and 2017, respectively. From 2017 to 2020, he was a principal engineer at Axend Inc., Los Angeles. From 2020 to 2022, he was a postdoctoral researcher with the School of Information and Electronics, Beijing Institute of Technology (BIT). Since 2023, he has been an assistant professor with the School of Information and Electronics, BIT. His research interests include radio frequency front-end monolithic microwave integrated design, antenna array, and distributed radar systems. E-mail: zhurui_bit2020@bit.edu.cn
Supported by:
This work was supported by the National Natural Science Foundation of China (62371046; 62201048), and the Natural Science Foundation of Chongqing, China (cstc2020jcyj-msxmX0260).

Abstract

Abstract:

Jamming suppression is traditionally achieved through the use of spatial filters based on array signal processing theory. In order to achieve better jamming suppression performance, many studies have applied blind source separation (BSS) to jamming suppression. BSS can achieve the separation and extraction of the individual source signals from the mixed signal received by the array. This paper proposes a perspective to recognize BSS as spatial band-pass filters (SBPFs) for jamming suppression applications. The theoretical derivation indicates that the processing of mixed signals by BSS can be perceived as the application of a set of SBPFs that gate the source signals at various angles. Simulations are performed using radar jamming suppression as an example. The simulation results suggest that BSS and SBPFs produce approximately the same effects. Simulation results are consistent with theoretical derivation results.

Key words: blind source separation (BSS), jamming suppression, spatial filtering

Quanhua LIU, Xinran SUI, Xinliang CHEN, Zhennan LIANG, Rui ZHU. Jamming suppression by blind source separation: from a perspective of spatial band-pass filters[J]. Journal of Systems Engineering and Electronics, 2025, 36(5): 1169-1176.

Figures/Tables 8

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References 31

1	TIAN J, ZHANG W Robust adaptive radar beamforming based on iterative training sample selection using kurtosis of generalized inner product statistics. Journal of Systems Engineering and Electronics, 2024, 35 (1): 24- 30. doi: 10.23919/JSEE.2024.000025
2	LIAO Y, TANG H, WANG W Q, et al A low sidelobe deceptive jamming suppression beamforming method with a frequency diverse array. IEEE Trans. on Antennas and Propagation, 2022, 70 (6): 4884- 4889. doi: 10.1109/TAP.2021.3138529
3	YE X D, LI L, WANG H, et al An effective array beamforming scheme based on branch-and-bound algorithm. Journal of Systems Engineering and Electronics, 2023, 34 (6): 1483- 1489. doi: 10.23919/JSEE.2022.000123
4	ZHANG W Q, LI Y C, CHEN S Y, et al Robust adaptive beamforming based on deep unfolded ADMM network. Modern Radar, 2024, 46 (6): 43- 49.
5	CHEN J Y, XU Z H, XIAO S P Robust interference suppression of wideband irregular subarrayed phased array based on subarray level processing. Systems Engineering and Electronics, 2024, 46 (2): 367- 380.
6	XIAO Z Y, HAN Z, NALLANATHAN A, et al Antenna array enabled space/air/ground communications and networking for 6G. IEEE Journal on Selected Areas in Communications, 2022, 40 (10): 2773- 2804. doi: 10.1109/JSAC.2022.3196320
7	PENG F, WU J, WANG S, et al An anti-main-lobe jamming algorithm for airborne early warning radar based on APC-SVRGD joint optimization. Journal of Systems Engineering and Electronics, 2022, 33 (1): 134- 143. doi: 10.23919/JSEE.2022.000014
8	ZHANG Z X, WANG Y Y Enhanced approach to fusing automatic characteristic frequency extraction and adaptive array signals weighting for abnormal machine sound localization. ISA Transactions, 2024, 145, 443- 467. doi: 10.1016/j.isatra.2023.11.041
9	BUCCI O M, CROCCO L, SCAPATICCI R, et al On the design of phased arrays for medical applications. Proceedings of the IEEE, 2016, 104 (3): 633- 648. doi: 10.1109/JPROC.2015.2504266
10	FU W H, WEI J, LIU N A, et al Algorithm for source recovery in underdetermined blind source separation based on plane pursuit. Journal of Systems Engineering and Electronics, 2018, 29 (2): 223- 228. doi: 10.21629/JSEE.2018.02.01
11	GERTOSIO R, BOBIN J, ACERO F Semi-blind source separation with learned constraints. Signal Processing, 2023, 202, 108776. doi: 10.1016/j.sigpro.2022.108776
12	DU Y C, SCHEIBLER R, TOGAMI M, et al Computationally-efficient overdetermined blind source separation based on iterative source steering. IEEE Signal Processing Letters, 2022, 29, 927- 931. doi: 10.1109/LSP.2021.3134939
13	TONG C D, LAN T, SHI X H Double-layer ensemble monitoring of non-Gaussian processes using modiﬁed independent component analysis. ISA Transactions, 2017, 68, 181- 188. doi: 10.1016/j.isatra.2017.02.003
14	ZHANG H L, ZHANG G, XUE B, et al Mainlobe jamming suppression via improved BSS method for rotated array radar. Journal of Systems Engineering and Electronics, 2022, 33 (6): 1151- 1158.
15	CHANG S, DENG Y K, ZHANG Y Y, et al An advanced scheme for range ambiguity suppression of spaceborne SAR based on blind source separation. IEEE Trans. on Geoscience and Remote Sensing, 2022, 60, 5230112.
16	CAI X, WANG X, HUANG Z T, et al Single-channel blind source separation of communication signals using pseudo-MIMO observations. IEEE Communications Letters, 2018, 22 (8): 1616- 1619. doi: 10.1109/LCOMM.2018.2832215
17	GUO P C, YU M, SHEN L, et al Single-channel blind source separation in wireless communications: a complex-domain deep learning approach. IEEE Wireless Communications Letters, 2024, 13 (6): 1645- 1649. doi: 10.1109/LWC.2024.3384813
18	GALLI A, PERI E, RABOTTI C, et al Automatic optimization of multichannel electrode configurations for robust fetal heart rate detection by blind source separation. IEEE Trans. on Biomedical Engineering, 2023, 70 (4): 1196- 1207. doi: 10.1109/TBME.2022.3212587
19	PU W M, LIANG Z N, WU J X, et al Joint generalized inner product method for main lobe jamming suppression in distributed array radar. IEEE Trans. on Aerospace and Electronic Systems, 2023, 59 (5): 6940- 6953. doi: 10.1109/TAES.2023.3280892
20	WANG C J, ZHENG Z M, ZHANG K X, et al Adaptive main-lobe jamming suppression based on cascaded LMS filter with low-cost distributed radar. IEEE Sensors Journal, 2023, 23 (21): 26292- 26301. doi: 10.1109/JSEN.2023.3317407
21	LEI Z S, QU Q Z, ZHANG L, et al Main lobe deception jamming suppression approach via SVD and FrFT for LFM radars. IEEE Trans. on Aerospace and Electronic Systems, 2024, 60 (3): 2948- 2965. doi: 10.1109/TAES.2024.3357029
22	GAO S, YANG X P, LAN T, et al Radar main-lobe jamming suppression and identification based on robust whitening blind source separation and convolutional neural networks. IET Radar, Sonar and Navigation, 2021, 16 (3): 552- 563.
23	GE M M, CUI G L, YU X X, et al Main lobe jamming suppression via blind source separation sparse signal recovery with subarray configuration. IET Radar, Sonar and Navigation, 2020, 14 (3): 431- 438. doi: 10.1049/iet-rsn.2019.0500
24	HAN X F, HE H F, ZHANG Q, et al Main-lobe jamming suppression method for phased array netted radar based on MSNR-BSS. IEEE Sensors Journal, 2022, 22 (23): 22972- 22984. doi: 10.1109/JSEN.2022.3213986
25	ZHOU B L, LI R F, LIU W J, et al A BSS-based space-time multi-channel algorithm for complex-jamming suppression. Digital Signal Processing, 2019, 87, 86- 103. doi: 10.1016/j.dsp.2019.01.007
26	GONG J, GUO Y D, LI X A blind source separation jamming suppression method based on channel ratio function. International Journal of Electronics, 2020, 107 (11): 1773- 1789. doi: 10.1080/00207217.2020.1756435
27	YU X X, YAN Z X, PAN B N, et al Digital sub-array radar sum-difference DOA estimation method in the presence of mainlobe following jamming. Journal of University of Electronic Science and Technology of China, 2023, 52 (4): 498- 505.
28	JUNG H, KIM K, KANG J, et al An iALM-ICA-based antijamming DS-CDMA receiver for LMS systems. IEEE Trans. on Aerospace and Electronic Systems, 2018, 54 (5): 2318- 2328. doi: 10.1109/TAES.2018.2814319
29	ZHU H Z, WANG X, JIANG Y, et al Secure voice interactions with smart devices. IEEE Trans. on Mobile Computing, 2023, 22 (1): 515- 526. doi: 10.1109/TMC.2021.3069981
30	YAO F Q, YU M, GUO P C, et al Blind source separation communication anti-jamming technology and practice. Journal on Communications, 2023, 44 (10): 1- 12.
31	TONG L, LIU R W, SOON V C, et al Indeterminacy and identifiability of blind identification. IEEE Trans. on Circuits and Systems, 1991, 38 (5): 499- 509. doi: 10.1109/31.76486

Index	Average value	Standard deviation
ΔSINR of BSS	46.524	0.567
ΔSINR of SBPFs	46.534	0.567
Difference between ΔSINRs of BSS and SBPFs	0.010	0.043

[1]	Qihua WU, Feng ZHAO, Tiehua ZHAO, Xiaobin LIU, Zhiming XU, Shunping XIAO. Nonperiodic interrupted sampling repeater jamming suppression for inverse synthetic aperture radar [J]. Journal of Systems Engineering and Electronics, 2025, 36(4): 940-950.
[2]	Jing TIAN, Wei ZHANG. Robust adaptive radar beamforming based on iterative training sample selection using kurtosis of generalized inner product statistics [J]. Journal of Systems Engineering and Electronics, 2024, 35(1): 24-30.
[3]	Kong Wei & Yang Bin. Blind source separation of ship-radiated noise based on generalized Gaussian model [J]. Journal of Systems Engineering and Electronics, 2006, 17(2): 321-325.

Jamming suppression by blind source separation: from a perspective of spatial band-pass filters

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