基于仿生映射的无人机电磁防护设计

王玉明; 马立云; 陈亚洲

doi:10.11884/HPLPB202537.250277

基于仿生映射的无人机电磁防护设计

doi: 10.11884/HPLPB202537.250277

中国人民解放军陆军工程大学石家庄校区电磁环境效应重点实验室，河北石家庄 050003

基金项目: 稳定支持计划项目(JCKYS2023DC02、JCKYS2024DC02)

详细信息

作者简介:
王玉明，ymking2006@163.com

通讯作者:
陈亚洲，chen_yazhou@sina.com。

中图分类号: TN972
计量
- 文章访问数: 11
- HTML全文浏览量: 3
- PDF下载量: 1
- 被引次数: 0
出版历程
- 收稿日期: 2025-08-30
- 修回日期: 2025-10-10
- 录用日期: 2025-09-22
- 网络出版日期: 2025-10-17

Electromagnetic protection design for drones based on biomimetic mapping

National Key Laboratory on Electromagnetic Environment Effects, Army Engineering University, ShiJiaZhuang 050003, China

摘要

摘要: 以人为代表的生物智能可以在数据智能、感知智能、认知智能和自主智能四个层次上移植到通用智能，随着智能无人技术的发展，电子系统正依照这四个层次逐步向智能化、自主化发展。电磁防护仿生作为电子系统保持其自身电磁兼容性、具备复杂电磁环境适应性，并耐受一定电磁威胁的防护手段，与电子系统同步发展，追求将生物体的智能与智慧映射到电磁防护设计中。基于无人机通信、导航、探测与控制四项性能，文章初步探讨从数据智能、感知智能、认知智能和自主智能四个层次实现仿生映射的电磁防护设计方法。
- 无人机 /
- 电磁防护 /
- 仿生 /
- 智能化
Abstract: Background
Human-represented biological intelligence is transplantable into general intelligence across four levels, namely data intelligence, perceptual intelligence, cognitive intelligence, and autonomous intelligence. As intelligent unmanned technologies advance, electronic systems undergo evolution toward higher intelligence and autonomy; concurrently, bionic electromagnetic protection—an approach that enhances compatibility, adaptability, and threat resistance—evolves in tandem with these electronic systems. Nevertheless, significant gaps persist in the translation of biological mechanisms into practical applications for electronic systems.
Purpose
Focused on drones as the research subject, this study explores the implementation of biomimetic mapping for drone electromagnetic protection across the aforementioned four levels, with the exploration grounded in core drone performances including communication, navigation, detection, and control. The primary objective of this study is to advance the development of electromagnetic protection toward higher levels of intelligence.
Methods
Guided by fundamental design principles of structure-function integration and multi-level immune protection, the research categorizes biomimetic mapping into information and signal levels: the information level encompasses spectrum sensing and autonomous decision-making, while the signal level concentrates on limiting and filtering technologies. For key drone systems, an intelligent data link was designed using software-defined radio technology; navigation receivers were optimized through the integration of shielding, filtering, and anti-interference antennas; a GAN-based image self-repair algorithm incorporating hybrid attention was proposed; and the application of neuromorphic circuits and bionic structures for control systems was explored.
Results
The study successfully developed a spectrum-sensing adaptive data link and a reinforced navigation receiver, and verified the initial realization of perceptual intelligence in selected system components.
Conclusions
Biomimetic mapping contributes to the enhancement of drone electromagnetic protection; however, challenges remain, including the refinement of mapping methods, the development of novel devices, and the advancement of intelligent computing. Future research efforts directed at addressing these challenges will facilitate the full realization of autonomous intelligence in drone electromagnetic protection systems.
- unmanned aerial vehicle /
- electromagnetic protection /
- bionics /
- intelligence

HTML全文

图 1 初级智能数据链工作过程

Figure 1. Primary intelligent data link working process

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图 2 初级智能数据链系统组成

Figure 2. Composition of the primary intelligent data link system

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图 3 初级智能数据链软件结构图

Figure 3. Software structure diagram of primary intelligent data link

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图 4 导航接收机强电磁脉冲效应实验

Figure 4. Experiment on the effect of strong electromagnetic pulse on navigation receiver

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图 5 导航接收机多阵元天线

Figure 5. Multi-element antenna for navigation receiver

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图 6 结合混合注意力机制与残差学习的生成对抗网络图像自修复算法

Figure 6. Image inpainting algorithm of generative adversarial networks combining mixed attention mechanism and residual learning

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参考文献(24)

[1]	刘尚合, 马贵蕾, 满梦华, 等. 电磁防护仿生研究进展[J]. 高电压技术, 2022, 48(5): 1750-1761 Liu Shanghe, Ma Guilei, Man Menghua, et al. Research progress of electromagnetic protection biomimetics[J]. High Voltage Engineering, 2025, 48(5): 1750-1761
[2]	中国电子科技集团公司第三十三研究所, 中北大学. 基于仿生复眼结构的球冠状透明电磁防护材料设计方法: 118605015A[P]. 2024-09-06 China Electronics Technology Group Corporation No. 33th Research Institute, North University of China. Design method of spherical crown-shaped transparent electromagnetic protection material based on bionic compound eye structure: 118605015A[P]. 2024-09-06
[3]	张耀辉, 谢彦召, 李跃波, 等. 人体免疫机制对重要基础设施系统级电磁防护的借鉴[J]. 高电压技术, 2019, 45(8): 2662-2667 Zhang Yaohui, Xie Yanzhao, Li Yuebo, et al. Reference of human body immunity mechanism to system level electromagnetic protection of important infrastructures[J]. High Voltage Engineering, 2019, 45(8): 2662-2667
[4]	Zhu Shiqiang, Yu Ting, Xu Tao, et al. Intelligent computing: the latest advances, challenges, and future[J]. Intelligent Computing, 2023, 2: 0006. doi: 10.34133/icomputing.0006
[5]	王永胜, 李伟, 郭文卿. 强电磁环境下无人机的电磁防护技术[J]. 安全与电磁兼容, 2020(5): 95-99 Wang Yongsheng, Li Wei, Guo Wenqing. Protection technology of UAV in strong electromagnetic environment[J]. Safety & EMC, 2022(5): 95-99
[6]	西安交通大学, 中国电子科技集团公司第二十四研究所. 一种基于双层电介质的碳基三端仿生突触器件及其制备方法: 115642174A[P]. 2023-01-24 Xi’an Jiaotong University, China Electronics Technology Group Corporation No. 24 Research Institute. Carbon-based three-terminal bionic synaptic device based on double-layer dielectric medium and preparation method of carbon-based three-terminal bionic synaptic device: 115642174A[P]. 2023-01-24
[7]	北京纳米能源与系统研究所. 一种突触器件及神经形态器件: 115759210A[P]. 2023-03-07 Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences. Synaptic device and neuromorphic device: 115759210A[P]. 2023-03-07
[8]	浙江大学. 一种仿生物演化的脉冲电磁防护电路: 115209713A[P]. 2022-10-18 Zhejiang University. Bionic evolution pulse electromagnetic protection circuit: 115209713A[P]. 2022-10-18
[9]	张冬晓, 陈亚洲, 程二威, 等. 一种无人机数据链电磁干扰自适应新方法[J]. 北京理工大学学报, 2020, 40(8): 880-887 Zhang Dongxiao, Chen Yazhou, Cheng Erwei, et al. A new method for UAV's datalink adaptive to EMI[J]. Transactions of Beijing Institute of Technology, 2020, 40(8): 880-887
[10]	陈自力, 江涛, 范君乐. 无人机智能数据链体系结构[J]. 无线电工程, 2009, 39(4): 4-6,10 Chen Zili, Jiang Tao, Fan Junle. Architecture of UAV intelligent data link system[J]. Radio Engineering, 2009, 39(4): 4-6,10
[11]	张庆龙, 王玉明, 程二威, 等. 导航接收机跟踪环路在电磁干扰下的效应律研究[J]. 北京理工大学学报, 2021, 41(2): 207-213 Zhang Qinglong, Wang Yuming, Cheng Erwei, et al. Effect law of navigation receiver tracking loop under electromagnetic interference[J]. Transactions of Beijing Institute of Technology, 2021, 41(2): 207-213
[12]	张庆龙, 王玉明, 程二威, 等. 导航接收机跟踪环路电磁干扰的预测方法研究[J]. 电子与信息学报, 2021, 43(12): 3656-3661 Zhang Qinglong, Wang Yuming, Cheng Erwei, et al. Investigation on prediction method of electromagnetic interference in the tracking loop of navigation receiver[J]. Journal of Electronics & Information Technology, 2021, 43(12): 3656-3661
[13]	黄欣, 陈亚洲, 王玉明, 等. 核电磁脉冲对导航接收系统辐照效应研究[J]. 兵器装备工程学报, 2022, 43(2): 274-279 Huang Xin, Chen Yazhou, Wang Yuming, et al. Research on radiation effects of nuclear electromagnetic pulse on navigation receiving system[J]. Journal of Ordnance Equipment Engineering, 2022, 43(2): 274-279
[14]	谭志良, 李亚南, 宋培姣. 射频前端强电磁脉冲防护研究进展[J]. 北京理工大学学报, 2020, 40(3): 231-242 Tan Zhiliang, Li Yanan, Song Peijiao. Relevant research on electromagnetic pulse protection of RF front-end[J]. Transactions of Beijing Institute of Technology, 2020, 40(3): 231-242
[15]	马立云, 陈亚洲, 张羽瑄, 等. 无人机卫星导航系统压制干扰试验方法研究[J]. 强激光与粒子束, 2025, 37(11): 1-9 Ma Liyun, Chen Yazhou, Zhang Yuxuan, et al. Test method for dynamic multi-source suppression jamming effects on unmanned aerial vehicle satellite navigation systems[J]. High Power Laser and Particle Beams, 2025, 37(11): 1-9
[16]	于周锋, 吴凡, 宁新潮, 等. 基于无人机载的光电与SAR图像融合技术研究[J]. 应用光学, 2017, 38(2): 174-179 Yu Zhoufeng, Wu Fan, Ning Xinchao, et al. Fusion method of optical image and SAR based on UAV[J]. Journal of Applied Optics, 2017, 38(2): 174-179
[17]	Teixidó P, Gómez-Galán J A, Caballero R, et al. Secured perimeter with electromagnetic detection and tracking with drone embedded and static cameras[J]. Sensors, 2021, 21: 7379. doi: 10.3390/s21217379
[18]	北京华航无线电测量研究所. 一种基于AR技术的无人机智能侦察处理系统及方法: 108257145A[P]. 2018-07-06 Beijing Huahang Radio Measurement Research Institute. AR technology-based intelligent reconnaissance processing system and method of unmanned aerial vehicle: 108257145A[P]. 2018-07-06
[19]	Wang Yuming, Luo Shuaili, Ma Liyun, et al. RCA-GAN: an improved image denoising algorithm based on generative adversarial networks[J]. Electronics, 2023, 12: 4595. doi: 10.3390/electronics12224595
[20]	曹震, 张浴轩, 李灵蕾, 等. 神经形态器件的特性与发展[J]. 电子学报, 2023, 51(12): 3619-3642 Cao Zhen, Zhang Yuxuan, Li Linglei, et al. A comprehension survey on the characterization and development of neuromorphic devices[J]. Acta Electronica Sinica, 2023, 51(12): 3619-3642
[21]	满梦华, 蔡娜, 马贵蕾, 等. 模仿神经元网络抗扰特性的电磁防护仿生研究[J]. 装备环境工程, 2017, 14(4): 9-15 Man Menghua, Cai Na, Ma Guilei, et al. Study on electromagnetic protection bionics by mimicking the anti-interference mechanism of neural network[J]. Equipment Environmental Engineering, 2017, 14(4): 9-15
[22]	Zhang Zhao, Zhou Yang, Zhang Yang, et al. Strong electromagnetic interference and protection in UAVs[J]. Electronics, 2024, 13: 393. doi: 10.3390/electronics13020393
[23]	Little M. A nonlinear model predictive controller for a wall-rolling fully actuated UAV[D]. Kingston: University of Rhode Island, 2021: 4.
[24]	张阳, 司光亚, 王艳正. 无人机蜂群电磁作战概念仿真[J]. 系统工程与电子技术, 2020, 42(7): 1510-1518 Zhang Yang, Si Guangya, Wang Yanzheng. Simulation of unmanned aerial vehicle swarm electromagnetic operation concept[J]. Systems Engineering and Electronics, 2020, 42(7): 1510-1518