针对组网雷达的无人机集群航迹欺骗综合误差分析

时晨光; 蒋泽宇; 严牧; 周建江; 闻雯

doi:10.11999/JEIT240289

针对组网雷达的无人机集群航迹欺骗综合误差分析

doi: 10.11999/JEIT240289

1.
南京航空航天大学雷达成像与微波光子技术教育部重点实验室南京 210016
2.
电磁空间认知与智能控制技术实验室北京 100191

基金项目: 国家自然科学基金(62271247)，江苏省自然科学基金优秀青年基金(BK20240181)，江苏高校“青蓝工程”，国防基础科研计划(JCKY2021210B004)，航空科学基金(20220055052001)，江淮前沿技术协同创新中心追梦基金(2023-ZM01D001)

详细信息

作者简介:
时晨光：男，副教授，博士生导师，研究方向为射频隐身技术、网络化雷达资源管理、分布式协同探测

蒋泽宇：男，硕士生，研究方向为无人集群对抗

严牧：男，博士，助理研究员，研究方向为电磁空间认知、群体频谱智能等

周建江：男，教授，博士生导师，研究方向为飞行器射频隐身技术、雷达目标特性分析以及阵列信号处理等

闻雯：男，硕士生，研究方向为无人集群航迹规划、飞行器射频隐身技术

通讯作者:
时晨光　scg_space@163.com

中图分类号: TN974
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出版历程
- 收稿日期: 2024-04-17
- 修回日期: 2024-11-13
- 网络出版日期: 2024-11-30

Comprehensive Error in UAV Cluster Trajectory Deception for Networked Radar

1.
Key Laboratory of Radar Imaging and Microwave Photonics, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China
2.
Laboratory of Electromagnetic Space Cognition and Intelligent Control, Beijing 100191, China

Funds: The National Natural Science Foundation of China (62271247), The Natural Science Foundation of Jiangsu Province (BK20240181), Qing Lan Project of Jiangsu Province, National Defense Basic Scientific Research Program of China (JCKY2021210B004), The National Aerospace Science Foundation of China (20220055052001), Dreams Foundation of Jianghuai Advance Technology Center (2023-ZM01D001)

摘要

摘要: 无人机集群在对组网雷达进行航迹欺骗过程中通过延时转发截获的雷达信号生成虚假目标点，而雷达站址误差、无人机抖动误差及转发时延误差均会造成虚假目标点偏离预设位置，进而使航迹欺骗效果恶化。针对上述问题，该文在雷达量测位置、无人机预设位置和欺骗距离已知以及组网雷达空间分辨单元(SRC)一定的情况下，分析了雷达站址误差、无人机抖动误差及转发时延误差同时存在时无人机集群成功欺骗组网雷达的边界条件，并总结了上述误差对航迹欺骗效果的影响规律。数值仿真结果表明，当3种误差同时存在时，推导结果可以有效评估无人机集群对组网雷达的欺骗能力。
- 航迹欺骗 /
- 组网雷达 /
- 无人机集群 /
- 误差分析
Abstract: In the process of trajectory deception against the networked radar using an Unmanned Aerial Vehicle (UAV) cluster, false target points are generated by delaying and forwarding intercepted radar signals. Errors such as radar station location errors, UAV jitter errors, and forwarding delay errors can all cause these false target points to deviate from their intended positions, thereby degrading the effectiveness of the deception. Considering known radar measurement positions, UAV preset positions, deception distances, and a specific Space Resolution Cell (SRC) of the networked radar, the boundary condition of successfully deceiving networked radar by a UAV cluster is analyzed in this paper. The impact patterns of these errors on deception effectiveness are also summarized in the paper. The numerical simulation results show that when all three kinds of errors are present, the derived results can effectively evaluate the deception ability of the UAV cluster to the networked radar.
- Track deception /
- Networked radar /
- UAV cluster /
- Error analysis

HTML全文

图 1 转发式航迹欺骗干扰示意图

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图 2 空间分辨单元示意图

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图 3 无人机集群对组网雷达实施航迹欺骗示意图

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图 4 无人机同时欺骗任意两部雷达示意图

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图 5 两架无人机干扰两部雷达综合误差分析

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图 6 时延误差不同情况下实际虚假目标点之间的距离

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图 8 无人机抖动误差不同情况下实际虚假目标点之间的距离

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图 7 雷达站址误差不同情况下实际虚假目标点之间的距离

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表 1 坐标参数设置

名称	位置(km)
雷达R₁	(0.00,0.00,0.00)
雷达R₂	(8.00,6.00,0.00)
雷达R₃	(14.00,20.00,0.00)
无人机A₁	(4.25,10.20,17.00)
无人机A₂	(5.75,10.50,15.00)
无人机A₃	(8.15,14.80,13.00)
虚假目标点C	(5.00,12.00,20.00)

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表 2 组网雷达误差和最小分辨率计算表

雷达站址误差(m)	无人机抖动误差(m)	转发时延误差(μs)	最小分辨率(m)
$ {e_{r1}} \le 4250.0 $	$ {e_{j1}} = 0.0 $	$ {e_{t1}} = 0.0 $	$ {\delta _{\min }} = 1500.0 $
$ {e_{r2}} \le 2250.0 $	$ {e_{j2}} = 0.0 $	$ {e_{t2}} = 0.0 $
$ {e_{r3}} \le 1392.9 $	$ {e_{j3}} = 0.0 $	$ {e_{t3}} = 0.0 $
$ {e_{r1}} = 0.0 $	$ {e_{j1}} \le 637.5 $	$ {e_{t1}} = 0.0 $	$ {\delta _{\min }} = 1500.0 $
$ {e_{r2}} = 0.0 $	$ {e_{j2}} \le 562.5 $	$ {e_{t2}} = 0.0 $
$ {e_{r3}} = 0.0 $	$ {e_{j3}} \le 487.5 $	$ {e_{t3}} = 0.0 $
$ {e_{r1}} = 0.0 $	$ {e_{j1}} = 0.0 $	$ {e_{t1}} \le 5.0 $	$ {\delta _{\min }} = 1500.0 $
$ {e_{r2}} = 0.0 $	$ {e_{j2}} = 0.0 $	$ {e_{t2}} \le 5.0 $
$ {e_{r3}} = 0.0 $	$ {e_{j3}} = 0.0 $	$ {e_{t3}} \le 5.0 $
$ {e_{r1}} \le 700.0 $	$ {e_{j1}} = 150.0 $	$ {e_{t1}} = 3.0 $	$ {\delta _{\min }} = 1500.0 $
$ {e_{r2}} \le 725.0 $	$ {e_{j2}} = 100.0 $	$ {e_{t2}} = 2.5 $
$ {e_{r3}} \le 692.9 $	$ {e_{j3}} = 50.0 $	$ {e_{t3}} = 2.0 $
$ {e_{r1}} = 1200.0 $	$ {e_{j1}} \le 75.0 $	$ {e_{t1}} = 3.0 $	$ {\delta _{\min }} = 1500.0 $
$ {e_{r2}} = 800.0 $	$ {e_{j2}} \le 81.3 $	$ {e_{t2}} = 2.5 $
$ {e_{r3}} = 600.0 $	$ {e_{j3}} \le 82.5 $	$ {e_{t3}} = 2.0 $
$ {e_{r1}} = 1200.0 $	$ {e_{j1}} = 150.0 $	$ {e_{t1}} \le 2.4 $	$ {\delta _{\min }} = 1500.0 $
$ {e_{r2}} = 800.0 $	$ {e_{j2}} = 100.0 $	$ {e_{t2}} \le 2.3 $
$ {e_{r3}} = 600.0 $	$ {e_{j3}} = 50.0 $	$ {e_{t3}} \le 2.3 $
$ {e_{r1}} = 1200.0 $	$ {e_{j1}} = 150.0 $	$ {e_{t1}} = 3.0 $	$ {\delta _{\min }} \geqslant 1400.0 $
$ {e_{r2}} = 800.0 $	$ {e_{j2}} = 100.0 $	$ {e_{t2}} = 2.5 $
$ {e_{r3}} = 600.0 $	$ {e_{j3}} = 50.0 $	$ {e_{t3}} = 2.0 $

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