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统一的概率和基于相似性的位置估计从无线电观测
Max Werner1, Markus Bullmann1, Toni Fetzer2
1Center for Artificial Intelligence (CAIRO), Technical University of Applied Sciences Wuerzburg-Schweinfurt (THWS), 97082 Wuerzburg, Germany.
Sensors (Basel, Switzerland)
|July 12, 2025
概括
这项研究引入了一种基于相似性的新型模型,用于准确的室内位置估计. 它提供了概率位置估计,改进了传统的无线电传播跟踪方法.
科学领域:
- 计算机科学 计算机科学
- 电气工程 电气工程
- 信号处理 信号处理
背景情况:
- 准确的室内定位仍然是一个挑战,现有的方法通常依赖于无线电传播的明确物理模型.
- 传统的位置估计技术通常提供点估计,限制其集成到动态系统.
研究的目的:
- 开发一种纯粹基于相似性的位置估计建模方法,独立于明确的物理假设.
- 引入概率位置估计作为连续概率密度函数,以加强整合到状态估计系统中.
主要方法:
- 一种基于内核的方法将传入的无线电传播数据与已知位置的参考记录进行比较.
- 根据相似性分配权重给参考位置,然后进行密度估计以生成连续的概率分布.
- 该方法是在基于智能手机的室内定位的颗粒过器 (PF) 系统中实施的.
主要成果:
- 与基于距离的模型相比,基于相似性的模型在现实的条件下在跟踪行人方面取得了更高的准确性.
- 该模型表现出灵活性,有效地执行无线电信号强度 (RSS) 和往返时间 (RTT) 测量.
- 概率位置估计被成功生成为连续概率密度函数.
结论:
- 拟议的基于相似性的方法为室内定位提供了强大而灵活的替代方案,优于传统方法.
- 它提供概率估计的能力提高了其在递归状态估计和现实世界跟踪应用中的实用性.
- 该模型与特定无线电传播物理学的独立性允许在不同测量类型中实现多功能应用.
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