时间调制阵列感知辅助的无人机隐蔽通信

缪晨; 秦雨萱; 马瑞谦; 林志; 马越; 章文韬; 吴文

doi:10.11999/JEIT240606

时间调制阵列感知辅助的无人机隐蔽通信

doi: 10.11999/JEIT240606

缪晨¹,
秦雨萱¹,
马瑞谦^2, ,,
林志²,
马越¹,
章文韬³,
吴文¹

1.
南京理工大学近程射频感知芯片与微系统教育部重点实验室南京 210014
2.
国防科技大学电子对抗学院合肥 230037
3.
东南大学毫米波国家重点实验室南京 210096

基金项目: 国家自然科学基金(62301254和62171464)，江苏省自然科学基金(BK20230916)，中国博士后科学基金(2023M731700)，国防科技大学自主科研创新基金 (22-ZZCX-07)，合肥综合性国家科学中心

详细信息

作者简介:
缪晨：男，副研究员，研究方向为近程探测、信号处理

秦雨萱：女，硕士生，研究方向为隐蔽通信、时间调制阵列

马瑞谦：男，讲师，研究方向为协同通信、短包通信、隐蔽通信

林志：男，副教授，研究方向为天地一体化信息网络、物理层安全、智能反射面

马越：男，副教授，研究方向为隐蔽通信、阵列信号处理

章文韬：男，博士后，研究方向为信号处理、通感一体化

吴文：男，研究员，研究方向为通感一体化、近程探测

通讯作者:
马瑞谦　mrq@nudt.edu.cn

中图分类号: TN918
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- 被引次数: 0
出版历程
- 收稿日期: 2024-07-16
- 修回日期: 2025-01-19
- 网络出版日期: 2025-01-25

Covert Communication Of UAV Aided By Time Modulated Array Perception

1.
Key Laboratory of Near-Range RF Sensing ICs & Microsystems, Ministry of Education, Nanjing University of Science and Technology, Nanjing 210094, China
2.
College of Electronic Engineering, National University of Defense Technology, Hefei 230037, China
3.
State Key Laboratory of Millimetre Waves, Southeast University, Nanjing 210096, China

Funds: The National Natural Science Foundation of China (62301254; 62171464), The Natural Science Foundation of Jiangsu Province (BK20230916), China Postdoctoral Science Foundation (2023M731700), The Research and Innovation Fund of National University of Defense Technology (22-ZZCX-07), Comprehensive National Science Center of Hefei

摘要

摘要: 随着无人机(UAV)通信技术在军民领域的广泛应用，保障UAV网络中的信息传输安全越来越受到关注。隐蔽通信提供了一种隐藏信息行为的良好手段，但目前数字波束成形等技术在带来更好隐蔽通信性能的同时，增加了体积和功耗。该文提出了一种基于时间调制平面阵列(TMPA)感知辅助的UAV短包隐蔽通信方法。首先，该文提出了基于TMPA-UAV隐蔽通信系统架构，并以此为基础提出了一种2维波达方向角(DOA)估计方法。其次，针对该场景建立了隐蔽通信模型，基于KL散度推导了隐蔽约束的闭式表达式。进一步地，该文根据估计的Willie角度对TMPA的开关序列进行优化，以最大化目标方向信号增益的同时最小化非目标方向信号增益。最后，该文以隐蔽吞吐量作为优化目标，使用一维搜索求解关于包长和发射功率优化问题的最优解。仿真表明，存在一个最优的数据包长使隐蔽吞吐量最大，所提TMPA辅助感知方案能够有效保证隐蔽传输，此外，选择合适的无人机高度可提高隐蔽通信性能。
- 时间调制阵列 /
- 隐蔽通信 /
- 无人机 /
- DOA估计 /
- 波束成形
Abstract: Objective With the widespread application of Unmanned Aerial Vehicle (UAV) communication technology in both military and civilian domains, ensuring the security of information transmission within UAV networks has garnered increasing attention.Covert communication serves as an effective approach to conceal information transmission. However, current technologies such as digital beamforming, while enhancing covert communication performance, increase system size and power consumption. A method for UAV short-packet covert communication based on Time Modulated Planar Array (TMPA) sensing is proposed. In this study, a TMPA-UAV covert communication system architecture is introduced, and a two-dimensional Direction of Arrival (DOA) estimation method is developed. A covert communication model is then established, and a closed-form expression for the covert constraint is derived using Kullback-Leibler (KL) divergence. Based on the estimated angle of Willie, the TMPA switching sequence is optimized to maximize the signal gain in the target direction while minimizing the gain in non-target directions. Covert throughput is selected as the optimization objective, and a one-dimensional search method is employed to determine the optimal data packet length and transmission power. Results and Discussions Simulations indicate that the root mean square error (RMSE) for DOA estimation in both directions approaches 0°, and the RMSE significantly decreases as the signal-to-noise ratio (SNR) increases (Figure 4). With a fixed elevation angle and azimuth angles varying between 0° and 60°, a comparison between the proposed method and the traditional DOA estimation method for time-modulated arrays demonstrates that the proposed method reduces the DOA estimation error to the order of 0.1°, significantly improving accuracy compared to conventional methods. Beamforming simulations based on the estimation results (Figure 6) show a sidelobe level (SLL) below -30 dB and a beamwidth of 5°, meeting design requirements. Covert communication simulations reveal the existence of an optimal data packet length that maximizes covert throughput (Figure 7). A stricter covert tolerance implies tighter constraints on covert communication (Figure 8), forcing Alice to use lower transmission power and shorter block lengths to communicate covertly with Bob. When the beamforming error angle is small, the system maintains a high covert throughput (Figure 9). Within a UAV flight height range of 50 m to 90 m, the covert throughput remains low; however, when the height exceeds 90 m, the throughput increases rapidly. Beyond 130 m, the UAV height has little impact on the maximum covert throughput, and performance reaches its optimal state. Therefore, controlling the UAV flight height appropriately is crucial for achieving effective communication between legitimate links. Conclusions This paper proposes a TMPA-based multi-antenna UAV sensing-assisted covert communication system for short packets. A TMPA-based DOA estimation method is introduced to determine the relative position of non-cooperative nodes. The CS algorithm is employed to optimize the beam radiation pattern, maximizing the gain at the legitimate destination node while creating nulls at the non-cooperative node's location. Furthermore, a closed-form expression for covert constraints is derived based on the KL divergence, and covert throughput is maximized through the joint optimization of packet length and transmission power. Simulations investigate the relationships between the number of array elements, covert tolerance, beam direction error angles, UAV height, and covert throughput. Results show that an optimal packet length exists to maximize covert throughput. Additionally, increasing the number of array elements and relaxing covert constraints can enhance covert throughput. Practical system design should comprehensively consider the optimization of these factors.
- Time modulated array /
- Covert communication /
- UAV /
- DOA estimation /
- Beamforming

HTML全文

图 1 时间调制阵列感知辅助隐蔽通信场景

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图 2 TMPA系统架构

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图 3 阵列位置分布

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图 4 DOA估计均方根误差

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图 5 所提方法与传统方法比较

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图 6 面向UAV隐蔽通信的TMPA波束成形优化结果

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图 7 隐蔽吞吐量随$ N $变化

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图 8 隐蔽吞吐量随$ \varepsilon $变化

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图 9 隐蔽吞吐量随误差角$ {\theta _{er}} $变化

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图 10 隐蔽吞吐量随UAV的H变化

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表 1 仿真参数表

仿真参数	值
Alice与Bob之间距离、Alice与Willie之间距离	$ {d_{\rm{ab}}} = 350 \;{\mathrm{m}}\; $, $ {d_{\rm{aw}}} = 130{\text{ }}{\mathrm{m}} $
路径损耗、传输速率	$ \alpha = 3.4 $, $ R = 0.1{\text{ }}bpcu $
单位距离d₀ = 1 m时信道功率增益、UAV与Bob之间的水平距离	$ {\beta _0} = - 80{\text{ }}{\mathrm{dB}} $, $ {R_{\rm{ab}}} = 320{\text{ }}{\mathrm{m}} $
隐蔽容忍度、噪声功率	$ \varepsilon = 0.05 $, $ {\sigma ^2} = - 80{\text{ }}{\mathrm{dB}} $

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