I-Corps: Positioning System in GPS-denied Environments using Euclidean TOA Ranging and Linear Matrix Inequalities

由于支持具有移动的用户的大规模信息系统对可扩展数据传播和高效空间查询处理的关键需求，因此对移动的设备的精确定位有很大的需求。只有具备这些能力，才能开发可扩展的数据传播和查询评估基础设施，用于查询、索引和路由数据集，以支持新颖的移动的应用。这些需求将推动客户为这些功能付费的意愿。例如，重要客户是消防员，他们将在燃烧的建筑物中使用该技术，以使用基于消防员组和受害者的移动的设备之间的机会通信的定位方法来定位被困在建筑物中的受害者。在这份提案中，I-Corps团队引入了新的软件，用于准确确定移动的设备的位置，即使在GPS拒绝的环境中。所提出的创新定位方法不使用UWB或超声波收发器等特殊硬件。相反，拟议中的定位软件将运行在典型的智能手机和笔记本电脑上。没有位置信息的GPS拒绝目标节点机会性地与具有某些定位能力的范围内的多个移动的对等节点通信。目标节点利用目标节点和对等节点之间的数据交换，使用三种算法来改进其位置估计：欧几里德TOA（到达时间），LMI（线性矩阵不等式）和重心算法。利用欧几里德TOA方法的近似范围，然后应用LMI和重心算法来提高定位精度。

Because of the critical needs for scalable data dissemination and efficient spatial query processing for supporting large-scale information systems with mobile users, there is a great demand for accurate positioning of mobile devices. Only with these capabilities, one will be able to develop scalable data dissemination and query evaluation infrastructure for querying, indexing, and routing datasets to support novel mobile applications. These needs will drive customers' willingness to pay for these capabilities. For example, important customers are firemen who will use this technology in a burning building to locate victims trapped in the building using this positioning method that is based on opportunistic communication among the group of firemen and the victim's mobile devices. In this proposal, the I-Corps team introduces new software for accurately determining the positions of mobile devices, even in GPS-denied environments. The proposed innovative method for positioning does not use special hardware as UWB or ultrasounds transceivers. Instead, the proposed positioning software will run on typical smartphones and laptops. A GPS-denied target node with no position information communicates opportunistically with a number of in-range mobile peer nodes with some positioning capabilities. Data exchanges between the target node and peer nodes are used by the target node to refine its position estimation using three algorithms: Euclidean TOA (Time of Arrival), LMI (Linear Matrix Inequalities) and barycentric algorithms. Using the approximate ranges from the Euclidean TOA method, the LMI and barycentric algorithms are then applied to improve position accuracy.