Radio Interferometric Tracking of Wireless Nodes Indoors

室内无线节点的无线电干涉跟踪

• 批准号: 0721604
• 负责人: Akos Ledeczi
• 金额: $ 45万
• 依托单位: Vanderbilt University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-09-01 至 2010-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0721604&HistoricalAwards=false
• 关键词: Radio; Interferometric; Tracking; Wireless; Nodes

The project aims at developing the foundations and the technology required for fine-grain indoor localization of wireless nodes using radio interferometry. Specifically, the project will develop a propagation model for radio interference signals in severe Multipath environments and an allocation strategy of frequency bands and channels to minimize RF multipath effects, maximize accuracy, and minimize measurement time. The project will also investigate how localization algorithms could work with linear combinations of distances of four nodes provided by the interferometric measurements as opposed to traditional pair-wise range estimates. The expected results of the research are a set of ranging, localization, and tracking services that achieve high precision localization even indoors and a corresponding reference implementation on an existing hardware platform. The implementation will enable extensive experimentation to gain additional insight into different reverberant environments as well as to validate the theoretical results under a range of different real-world conditions. The results can potentially enable many location-aware applications, such as accurate asset tracking in warehouses, precise localization of 802.11 nodes in WiFi networks, navigation for emergency personnel, as well as many indoor applications of wireless sensor networks.

该项目旨在开发使用无线电干涉测量法对无线节点进行精细室内定位所需的基础和技术。具体而言，该项目将开发在严重多径环境中无线电干扰信号的传播模型，以及频带和信道的分配策略，以最大限度地减少RF多径效应，最大限度地提高精度，并最大限度地减少测量时间。该项目还将研究定位算法如何与干涉测量提供的四个节点距离的线性组合一起工作，而不是传统的成对距离估计。该研究的预期结果是一组测距，定位和跟踪服务，即使在室内也能实现高精度定位，并在现有硬件平台上实现相应的参考实现。该实施将使广泛的实验，以获得更多的洞察不同的混响环境，以及验证在一系列不同的现实世界条件下的理论结果。这些结果可以潜在地实现许多位置感知应用，例如仓库中的精确资产跟踪，WiFi网络中802.11节点的精确定位，紧急人员的导航，以及无线传感器网络的许多室内应用。