基于帐PSO的无人机飞行器路径规划,用于在动态用户环境中的合作中继网络
Shuyue Liu1, Wenmao Zhou1, Mingwei Qin1
1School of Information Engineering, Southwest University of Science and Technology, Mianyang 621010, China.
Sensors (Basel, Switzerland)
|April 12, 2025
概括
本研究介绍了Tent-PSO,这是一个针对无人机 (UAV) 路径规划的优化算法. 它增强了动态用户的移动通信覆盖范围,提高了解决方案的准确性和网络吞吐量.
科学领域:
- 计算机科学 计算机科学
- 电气工程 电气工程
- 机器人技术 机器人技术 机器人技术
背景情况:
- 无人机为动态的地面用户提供灵活的移动通信解决方案.
- 传统的粒子群集优化 (PSO) 面临的挑战是搜索覆盖范围不均和过早的融合.
- 有效的无人机路线规划对于最大限度地提高用户覆盖率和通信质量至关重要.
研究的目的:
- 为动态用户覆盖提供改进的无人机路径规划方法.
- 在无人机通信场景中解决传统PSO的局限性.
- 提高多无人机系统的效率和有效性.
主要方法:
- 这是一种新的方法,它结合了帐混沌映射和粒子集群优化 (Tent-PSO).
- 利用帐混乱映射来优化无人机的速度和位置,以实现粒子分布的均.
- 模拟具有动态用户分布的多无人机覆盖场景.
主要成果:
- 帐-PSO在全球最佳解决方案覆盖率上表现出10%的改善.
- 与传统方法相比,吞吐量至少增加了37%.
- 提出的方法有效地处理动态用户场景.
结论:
- 帐-PSO显著提高了基于无人机的移动通信覆盖率.
- 该算法克服了PSO的局限性,提供了卓越的性能.
- 这种方法对于在动态环境中优化通信链路是有效的.
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