面向安全传输的低能耗无人机轨迹优化算法

doi:10.19678/j.issn.1000-3428.0066761

摘要/Abstract

摘要：

无人机凭借其灵活的机动性以及高数据传输速率，被广泛应用于大范围离散节点的数据采集工作，其机载能量的有限性也使得无人机能耗优化成为当前研究热点。然而，当环境中存在窃听节点时，如何在保障多个离散数据节点数据安全传输前提下优化无人机的能量消耗具有一定的挑战性。基于此，引入中继节点和安全容量，提出面向安全传输的低能耗无人机轨迹优化算法，力求从物理层面保障数据的安全传输。对无人机与地面节点的信道模型、无人机与数据节点之间的安全容量以及无人机飞行通信能耗进行建模。将问题形式化描述为以最小化无人机能耗为目标、数据节点与无人机之间的数据安全传输为主要约束的非确定性多项式难解优化问题。为解决该问题，对问题进行子问题分解，采用自组织映射方法以及定制的粒子群算法分别对无人机访问数据节点的最优次序以及在数据节点周边悬停的最佳位置进行求解，并根据现有工作提出3种基准方案进行性能对比。仿真实验结果表明，当中继节点的能量收集电路最大输出功率变化时，所提的优化算法在降低无人机总能耗方面相比BASE_D、BASE_M、BASE_R 3种基准方案分别平均提高7.25%、8.59%、11.57%。此外，在安全容量实现率方面，所提算法的性能均优于对比方案，例如，当安全容量阈值从0.001~0.500变化时，所提算法相比基准方案BASE_M平均提高23.45%。

关键词: 无人机, 安全容量, 低能耗, 无线传能, 能量收集

Abstract:

Unmanned Aerial Vehicles(UAVs) are widely used to collect large-scale discrete node data because of their flexible maneuverability and high data transmission rates. The limited onboard energy also makes UAV energy consumption optimization a trending research hotspot.However, when eavesdropping nodes are formed in the environment, optimizing the energy consumption of drones while ensuring the secure data transmission from multiple discrete data nodes poses a significant challenges. Based on this, the introduction of relay nodes and secure capacity aims to ensure the secure transmission of data from a physical level and proposes a low-energy UAV trajectory optimization algorithm for secure transmission.The channel model between drones and ground nodes, the secure capacity between drones and data nodes, and the energy consumption of drone flight communication are established. The problem is formulated as a Non-deterministic Polynomial(NP) hard to solve the optimization problem to minimize drone energy consumption and the main constraint of secure data transmission between the data nodes and drones. The problem is decomposed into subproblems, and a self-organizing mapping method and customized particle swarm optimization algorithm are used to solve the optimal order of drone access to data nodes and the optimal position to hover around data nodes.Based on previous studies, three benchmark schemes are proposed for performance comparison. The simulation experimental results show that when the maximum output power of the energy collection circuit of the relay node changes, the proposed optimization algorithm is, on average, 7.25%, 8.59%, and 11.57% better than the BASE_D, BASE_M, BASE_R three benchmark schemes in reducing the total energy consumption of the drone. In addition, the performance of the proposed algorithm is superior to existing solutions in terms of the secure capacity implementation rate. For example, when the secure capacity threshold increases from 0.001 to 0.500, the proposed algorithm outperforms the benchmark scheme BASE_M is 23.45%.

Key words: Unmanned Aerial Vehicle(UAV), secure capacity, low energy consumption, wireless energy transmission, energy harvesting

吴嘉鑫, 孙一飞, 吴亚兰, 武继刚. 面向安全传输的低能耗无人机轨迹优化算法[J]. 计算机工程, 2024, 50(2): 59-67.

Jiaxin WU, Yifei SUN, Yalan WU, Jigang WU. Low Energy Consumption UAV Trajectory Optimization Algorithm for Secure Transmission[J]. Computer Engineering, 2024, 50(2): 59-67.

http://www.ecice06.com/CN/Y2024/V50/I2/59

图/表 11

图1 无人机安全通信网络架构

Fig.1 Architecture of UAV secure communication network

图2 无人机网络安全通信信道模型

Fig.2 Channel model of secure communication in UAV network

图3 当中继节点传输功率变化时的无人机总能耗对比

Fig.3 Comparison of total energy consumption of UAV when relay node transmission power changes

图4 当中继节点传输功率变化时的安全容量对比

Fig.4 Comparison of secure capacity when relay node transmission power changes

图5 当EH电路最大输出功率变化时的无人机总能耗对比

Fig.5 Comparison of total energy consumption of UAV when the maximum output power of EH circuit varies

图6 当EH电路最大输出功率变化时的安全容量对比

Fig.6 Comparison of secure capacity when the maximum output power of EH circuit varies

图7 当安全容量阈值变化时的无人机总能耗对比

Fig.7 Comparison of toal energy consumption of UAV when the secure capacity threshold varies

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