智能手机实时动力定位的十米级准确度 在复杂的城市环境中实施强大的卡尔曼波器方法和惯性导航系统输入
Amir Hossein Pourmina1, Mohamad Mahdi Alizadeh1,2, Harald Schuh2,3
1Faculty of Geodesy and Geomatics Engineering, K. N. Toosi University of Technology, Tehran 19697, Iran.
Sensors (Basel, Switzerland)
|September 28, 2024
概括
通过将全球导航卫星系统 (GNSS) 的实时动态 (RTK) 与惯性导航系统 (INS) 数据融合,智能手机定位得到了增强. 这种综合方法提高了准确性和可靠性,特别是在具有挑战性的城市环境中.
科学领域:
- 地理学工程 工程地质学
- 导航系统 导航系统
- 移动传感器 移动传感器
背景情况:
- 智能手机提供实时全球导航卫星系统 (GNSS) 数据 (伪色,多普勒,载体相).
- 通过将智能手机GNSS与参考站校正集成,可以实现实时动态定位 (RTK).
- 惯性导航系统 (INS) 数据可以补充GNSS以提高定位稳定性.
研究的目的:
- 用原始GNSS测量来评估智能手机的实时定位能力.
- 通过将GNSS RTK与INS测量相结合,提出和评估一种改进的定位方法.
- 调查在复杂的城市环境中紧密结合的RTK/INS融合框架的性能.
主要方法:
- 使用U-Blox ZED-F9RGNSS接收器作为一个基准.
- 开发了一个增强的模糊性解决算法,将LAMBDA方法与自适应值结合起来.
- 采用扩展卡尔曼波器 (EKF) 实现了紧密合 (TC) RTK/INS 融合,并实时加权.
- 利用INS数据在GNSS中断期间保持准确的定位,并检测异常的GNSS测量.
主要成果:
- RTK定位实现了十米级的精度,超过了单点定位 (SPP).
- 在Qazvin市,RTK/INS融合方法提供了约0.380米 (小米Mi 8) 和0.415米 (三星Galaxy S21 Ultra) 的定位精度.
- 融合方法证明了稳定性和精度的提高,弥合了SPP和RTK之间的差距,并在RTK信号不可靠时作为可行的替代方案.
结论:
- 整合RTK和INS测量提供了增强的实时智能手机定位,特别是在具有挑战性的城市环境中.
- 拟议的TC RTK/INS融合框架具有自适应加权,显示出可靠导航的巨大潜力.
- 环境条件极大地影响定位方法的选择,突出了融合技术的价值,以保持一致的性能.
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