基于定向天线的GNSS分布式压制干扰方法

doi:10.11947/j.AGCS.2026.20260107

摘要/Abstract

摘要：

针对传统全向天线在GNSS分布式压制干扰中存在的能量利用效率低、部署成本高且隐蔽性差等问题，本文提出一种基于定向天线的GNSS分布式压制干扰方法。该方法以基于斜率最优点的三维空间GNSS分布式压制干扰方法为基础，通过构建定向天线三维椭球辐射模型并建立坐标系转换关系，设计基于几何约束的改进欧氏聚类算法以精准求解天线最优波束指向，同时重构了适配定向天线特性的干扰源部署流程；进一步设计全向-定向天线组合干扰模式，采用逐次择优策略融合双天线优势。仿真结果表明，本文方法在实现约95%目标干扰覆盖率的前提下，相比全向天线方案可减少34.62%~65.63%的干扰源数量；全向-定向组合模式相较纯定向方案可再减少20%~50%的干扰源数量，且天线增益越大，部署规模优化越显著；同时显著降低了信号重叠冗余，提升了能量利用效率与部署隐蔽性。

关键词: 定向天线, 欧氏聚类, 分布式压制干扰, 卫星导航, 可视域分析

Abstract:

To address the issues of low energy utilization efficiency, high deployment costs, and poor concealment associated with traditional omnidirectional antennas in GNSS distribute suppression jamming, this paper proposes a GNSS distribute suppression jamming method based on directional antennas. This method is built upon the 3D space GNSS distributed suppression jamming method based on slope optimal point. By constructing a 3D ellipsoidal radiation model for directional antennas and establishing coordinate transformation relationships, an improved Euclidean clustering algorithm based on geometric constraints is designed to accurately solve the optimal beam pointing of the antenna. Meanwhile, the deployment process of jamming sources is reconstructed to match the characteristics of directional antennas. Furthermore, a combined omnidirectional-directional antenna jamming mode is designed, employing a sequential selection strategy to integrate the advantages of both antennas types. Simulation results show that the proposed method can reduce the number of jamming sources by 34.62% to 65.63% compared with the omnidirectional antenna scheme on the premise of achieving approximately 95% of the target jamming coverage. The combined omnidirectional-directional mode further reduces the number of jamming sources by 20% to 50% relative to the purely directional solution. Moreover, the higher the antenna gain, the more significant the deployment scale optimization. At the same time, it significantly reduces signal overlap redundancy, improving energy utilization efficiency and deployment concealment.

Key words: directional antenna, Euclidean clustering, distribute suppression jamming, satellite navigation, viewshed analysis

中图分类号:

P228

刘志衡, 刘伟平, 吕志伟, 焦博. 基于定向天线的GNSS分布式压制干扰方法[J]. 测绘学报, 2026, 55(9): 1530-1541.

Zhiheng Liu, Weiping Liu, Zhiwei Lü, Bo Jiao. GNSS distribute suppression jamming method based on directional antennas[J]. Acta Geodaetica et Cartographica Sinica, 2026, 55(9): 1530-1541.

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链接本文: http://xb.chinasmp.com/CN/10.11947/j.AGCS.2026.20260107

http://xb.chinasmp.com/CN/Y2026/V55/I9/1530

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参考文献 27

[1]	Pyrgies J. The UAVs threat to airport security: risk analysis and mitigation[J]. Journal of Airline and Airport Management, 2019, 9(2): 63.
[2]	Spanghero M, Geib F, Panier R, et al. Uncovering GNSS interference with aerial mapping UAV[C]//Proceedings of 2024 IEEE Aerospace Conference. Big Sky: IEEE, 2024: 1-10.
[3]	Chen Peilin, Li Haobo, Ma Lejing. Distributed massive UAV jamming optimization algorithm with artificial bee colony[J]. IET Communications, 2023, 17(2): 197-206.
[4]	Ran Weizhi, Luo Rong, Zhang Funing, et al. Research on efficient multiagent reinforcement learning for multiple UAVs' distributed jamming strategy[J]. Electronics, 2023, 12(18): 3874.
[5]	寇瑞雄. 城市立体空间导航卫星时空可见性分析[J]. 测绘学报, 2024, 53(11): 2231. DOI: . doi: 10.11947/j.AGCS.2024.20230395
	Kou Ruixiong. The spatio-temporal visibility analysis of navigation satellites in 3D urban space[J]. Acta Geodaetica et Cartographica Sinica, 2024, 53(11): 2231. DOI: . doi: 10.11947/j.AGCS.2024.20230395
[6]	刘志衡, 刘伟平, 焦博. 基于局部最优点的GNSS分布式压制干扰源部署算法[J]. 兵工学报, 2024, 45(9): 3240-3252.
	Liu Zhiheng, Liu Weiping, Jiao Bo. GNSS distributed interference source deployment algorithm based on locally optimal point[J]. Acta Armamentarii, 2024, 45(9): 3240-3252.
[7]	刘志衡, 刘伟平, 焦博. 基于斜率最优点的三维空间GNSS分布式压制干扰方法[J]. 兵工学报, 2026, 47(1): 250095.
	Liu Zhiheng, Liu Weiping, Jiao Bo. 3D space GNSS distribute suppression jamming method based on slope optimal point[J]. Acta Armamentarii, 2026, 47(1): 250095.
[8]	徐悦, 张颖, 刘杨, 等. 一种分布式卫星导航干扰防护区域评估方法[J]. 微波学报, 2024, 40(S1): 394-397.
	Xu Yue, Zhang Ying, Liu Yang, et al. An evaluation method of distributed satellite navigation interference protection area[J]. Journal of Microwaves, 2024, 40(S1): 394-397.
[9]	Noghanian S. Textile omnidirectional antenna for wearable WiFi-7 applications using higher order modes[J]. Frontiers in Antennas and Propagation, 2024, 2: 1419391.
[10]	Xia Minghua, Aissa S. On the efficiency of far-field wireless power transfer[J]. IEEE Transactions on Signal Processing, 2015, 63(11): 2835-2847.
[11]	Huang Yingchun, Li Xiaoxiao, Li Hang. Design and simulation of the algorithm on the distribution and coverage of GPS jamming shells[C]//Proceedings of the 3rd International Conference on Intelligent Networks and Intelligent Systems. Shenyang: IEEE, 2010: 634-637.
[12]	George R, Mary T A J. Review on directional antenna for wireless sensor network applications[J]. IET Communications, 2020, 14(5): 715-722.
[13]	马新生, 郭萌, 张正谦, 等. 应用于电子侦收的小型化高增益超宽带定向天线[J]. 天线学报, 2023, 12(3): 29-38.
	Ma Xinsheng, Guo Meng, Zhang Zhengqian, et al. Miniaturized high-gain ultra-wide band (UWB) directional antenna for electronic reconnaissance applications[J]. Journal of Antennas, 2023, 12(3): 29-38.
[14]	Taskhiri M M. Axis-symmetric ellipsoidal lens antenna design with independent E and H radiation pattern beamwidth[J]. Optics & Laser Technology, 2021, 140: 107037.
[15]	Pillai J, Prajapati J, Upadhayay M D. Wide half power beamwidth MIMO antenna for vehicular radar system[J]. International Journal of Applied Electromagnetics & Mechanics, 2025, 77(4): 276-290.
[16]	Yang Fan, Liu Yuhan. Research on alternative GNSS methods for UAV pseudolite networking[J]. Journal of Geodesy and Geoinformation Science, 2025, 8(1): 89-99.
[17]	Mitch R H, Dougherty R C, Psiaki M L, et al. Signal characteristics of civil GPS jammers[C]//Proceedings of the 24th International Technical Meeting of the Satellite Division of the Institute of Navigation. Portland: the Institute of Navigation, 2011: 1907-1919.
[18]	Reis S, Silva F, Albuquerque D, et al. General overview of antennas for unmanned aerial vehicles: a review[J]. Electronics, 2025, 14(16): 3205.
[19]	Sangenis E, Shkel A M. Fast-alignment of AR headset from local to geodetic coordinate frame for navigation and mixed reality applications[J]. IEEE Sensors Letters, 2025, 9(2): 6002404.
[20]	Hartigan J A, Wong M A. A K-means clustering algorithm[J]. Applied Statistics, 1979, 28(1): 100-108.
[21]	Sander J, Ester M, Kriegel H P, et al. Density-based clustering in spatial databases: the algorithm GDBSCAN and its applications[J]. Data Mining and Knowledge Discovery, 1998, 2(2): 169-194.
[22]	谢一涵, 毕鹏飞, 王爱萍. 种群优化联合鲁棒距离度量的公平性K-means算法[J]. 电子测量与仪器学报, 2025, 39(06): 121-133.
	Xie Yihan, Bi Pengfei, Wang Aiping. Population optimization combined with robust distance metric for fair K-means clustering algorithm[J]. Journal of Electronic Measurement and Instrumentation, 2025, 39(6): 121-133.
[23]	Zhang Xingguo, Xu Li, Jia Weikuan. EGBDPM: efficient granular ball density peaks clustering for manifold data[J]. Neurocomputing, 2026, 682: 133427.
[24]	Wei Ya, Gan Shu, Yuan Xiping, et al. Analysis of topographic feature parameters of dinosaur valley ring tectonic geomorphology based on the advanced land observing satellite digital elevation model (ALOS DEM)[J]. Applied Sciences, 2023, 13(24): 13137.
[25]	Wang Xiaolei, He Xiufeng, Zhang Qin, et al. The preliminary discussion of the potential of GNSS-IR technology for terrain retrievals[J]. Journal of Geodesy and Geoinformation Science, 2021, 4(2): 79-88.
[26]	U. S. Department of Defense. Navstar GPS space segment/navigation user interfaces[R]. Washington, D. C.: Department of Defense, 2004.
[27]	伍启燕. 复杂地形中的无线电波传播损耗特性研究[D]. 广汉: 中国民用航空飞行学院, 2023.
	Wu Qiyan. Research on propagation attenuation characteristic of radio wave in complex terrain[D]. Guanghan: Civil Aviation Flight University of China, 2023.

	天线类型	增益范围/dB	典型应用场景
全向天线	标准全向	2~5	车载干扰
	中增益全向	6~9	中型区域覆盖
	特种全向	5~8	固定式干扰系统
定向天线	八木天线	6~12	固定点定向干扰
	平板/对数周期	8~16	基站式干扰
	螺旋定向	10~18	无人机反制

试验区域大小	待聚类点数	定向天线模型参数			欧氏聚类参数设置			分簇结果
试验区域大小	待聚类点数	a/m	b/m	c/m	搜索半径R/m	最小簇数量N_min	最大簇数量N_max	分簇个数	最大簇编号
10 km×10 km	12 456	1500	1500	3000	100	1	10 000	3	1
10 km×10 km	12 456	1500	1500	3000	100	1	8000	3	1
10 km×10 km	12 456	1500	1500	3000	100	1	6000	5	1
10 km×10 km	12 456	1500	1500	3000	100	1	4000	7	1
10 km×10 km	12 456	1500	1500	3000	100	1	2000	6	2
10 km×10 km	12 456	1500	1500	3000	100	1	1000	12	2

场景编号	组别序号	发射功率/W	干扰信号最大覆盖距离/m	全向天线增益/dB	定向天线增益/dB	干扰源数量			干扰源数量减少百分比/（%）
场景编号	组别序号	发射功率/W	干扰信号最大覆盖距离/m	全向天线增益/dB	定向天线增益/dB	全向	定向	全/定向	定向vs全向	组合vs定向
1	1	0.01	90	2	6	26	17	12	34.62	29.41
	1	0.01	90	2	8	26	15	12	42.31	20.00
	2	0.03	156	2	6	21	12	8	42.86	33.33
	2	0.03	156	2	8	21	12	8	42.86	33.33
2	1	3	1560	5	12	32	19	11	40.63	42.11
	1	3	1560	5	18	32	11	8	65.63	27.27
	2	5	2139	5	12	19	10	5	47.36	50.00
	2	5	2139	5	18	19	7	5	63.16	28.57