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一种基于多条件约束的无人机高精度合作定位方法.
Haiqiao Liu1, Wen Jiang2, Qing Long2
1The School of Electrical and Information, Hunan Institute of Engineering, Xiangtan 411104, China.
Sensors (Basel, Switzerland)
|March 14, 2026
概括
本研究介绍了一种新的空中-地面合作定位方法,用于无人机 (UAV) 克服全球导航卫星系统 (GNSS) 在具有挑战性的环境中的错误. 整合地面参考站显著提高了无人机群定位精度和稳定性.
科学领域:
- 机器人技术和自主系统
- 导航和控制 导航和控制
- 地理空间智能是什么?
背景情况:
- 全球导航卫星系统 (GNSS) 在信号拒绝环境中面临重大本地化错误.
- 多个无人机 (UAV) 的合作定位精度对群体的几何配置敏感.
- 现有的方法在复杂的操作场景中难以获得稳定性和精度.
研究的目的:
- 开发一个高精度和强大的合作本地化方法,用于无人机群.
- 优化无人机群数量和几何配置,以改善本地化.
- 通过整合地面参考基础设施来提高本地化性能.
主要方法:
- 通过最小化精度的几何稀释 (GDoP) 来优化无人机群数量和几何配置.
- 引入地面辅助参考站 (GARS) 或无人地面车辆 (UGV) 进行空地合作系统.
- 利用到达时间差 (TDoA) 约束来提高准确性和稳定性.
主要成果:
- 纯粹基于空气的几何优化改进了水平覆盖,但显示了Z轴误差 (3.0-5.0 m).
- 与边缘部署的地面站合作的空地合作计划将位置精度稀释 (PDoP) 降至0.75.
- 拟议的空地系统有效地抑制了错误分歧,并优于纯粹的基于空气的方法.
结论:
- 空地合作本地化显著提高无人机群的定位准确性和稳定性.
- 优化几何配置和整合地面参考对于可靠的导航至关重要.
- 拟议的方法为先进的无人机操作提供了实质性的理论和实践价值.
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