对利用智能手机传感器和空间背景的室内定位方法的审查
Jiayi Li1, Yinhao Song2, Zhiliang Ma1
1School of Civil Engineering, Tsinghua University, Beijing 100084, China.
Sensors (Basel, Switzerland)
|November 9, 2024
概括
这项研究系统地审查了基于智能手机的室内定位方法,并根据数据源对其进行分类. 它突出了研究缺口,并为推进室内定位技术提供了一个参考.
科学领域:
- 计算机科学 计算机科学
- 无处不在的计算无处不在的计算
- 信号处理 信号处理
背景情况:
- 基于位置的服务 (LBS) 正在迅速发展,增加了对有效室内本地化的需求.
- 智能手机对于室内定位至关重要,原因是集成的传感器,计算能力和用户普及率.
- 现有的审查缺乏基于智能手机的室内定位的系统分析,特别是关于传感器数据和环境环境整合.
研究的目的:
- 系统地审查和分类现有的基于智能手机的室内定位方法.
- 分析不同数据整合方法的优缺点.
- 确定研究缺口,并为未来的工作提供全面的参考.
主要方法:
- 系统的文献检索和分析.
- 基于数据源的方法分类:单传感器,多传感器融合和传感器空间上下文集成.
- 讨论关键问题和总结研究缺口.
主要成果:
- 根据数据集成,现有研究被分为三个主要类别.
- 剖析了每个类别的优点和弱点.
- 确定了基于智能手机的室内本地化的主要挑战和未来研究方向.
结论:
- 介绍了理解基于智能手机的室内定位方法的系统框架.
- 审查强调了将传感器数据与先前的环境知识相结合的重要性,以提高性能.
- 这项工作为该领域的研究人员和开发人员提供了宝贵的参考资料.
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