多路径辅助超宽带车辆定位在地下停车场使用光线追踪环境
Shuo Hu1, Lixin Guo1, Zhongyu Liu1
1School of Physics, Xidian University, Xi'an 710071, China.
Sensors (Basel, Switzerland)
|April 12, 2025
概括
本研究引入了一种用于地下停车场的车辆定位的新方法,使用非视线 (NLOS) 信号作为数据. 它通过将NLOS转换为视线路径来实现高精度 (高达0.14m).
科学领域:
- 机器人技术和自主系统
- 信号处理 信号处理
- 地理学工程 工程地质学
背景情况:
- 复杂的地下停车场为车辆定位带来了重大挑战,原因是非视线 (NLOS) 障碍.
- 传统方法专注于缓解NLOS,但这项研究探讨利用NLOS传播作为有价值的信息.
研究的目的:
- 开发一种创新的NLOS定位框架,用于在NLOS占主导地位的环境中精确定位车辆.
- 使用射线追踪 (RT) 将NLOS传播路径转换为等效的视线 (LOS) 路径.
- 通过整合超宽带 (UWB) 测量和强大的代算法来提高定位准确性.
主要方法:
- 使用通用源 (GS) 技术与射线追踪 (RT) 结合,将NLOS路径转换为LOS.
- 实施了在非线性系统中初始权重的新型GS过和权重策略.
- 采用强大的代重权最小方程 (W-IRLS) 方法进行最佳位置估计,减轻NLOS噪声.
- 集成超宽带 (UWB) 延迟和角度测量 (AOA,TOA,TDOA) 到四种不同的定位模式.
主要成果:
- 证明了拟议的NLOS定位框架的特殊有效性和稳定性.
- 在特定的实验和模拟场景中达到高精度定位精度,高达0.14米.
- 验证了框架在具有挑战性的NLOS重量环境中提供可靠定位的能力.
结论:
- 开发的框架成功地利用NLOS传播来实现精确的车辆定位.
- 该研究推进了NLOS定位的最新技术,为复杂的环境提供了强大的解决方案.
- 建立了高精度定位系统在具有挑战性的场景,如地下停车场的基础.
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