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   https://doi.org/10.1109/IPIN54987.2022.9918119  

   Chen, Haige; Dhekne, Ashutosh (September 2022, 2022 IEEE 12th International Conference on Indoor Positioning and Indoor Navigation (IPIN))

   Enabling reliable indoor localization can facilitate several new applications akin to how outdoor localization systems, such as GPS, have facilitated. Currently, a few key hurdles remain that prevent indoor localization from reaching the same stature. These hurdles include complicated deployment, tight time synchronization requirements from time difference of arrival protocols, and a lack of mechanism to allow a pan-building seamless solution. This work explores ways in which these key hurdles can be overcome to enable a more pervasive use of indoor localization. We propose a novel passive ranging scheme where clients overhear ongoing two-way ranging wireless communication between a few infrastructure nodes, and compute their own relative location without transmitting any signals (preserving user privacy). Our approach of performing two-way ranging between infrastructure nodes removes a crucial timing requirement in traditional time-difference-of-arrival methods thereby relaxing the synchronization requirements imposed by previous techniques. We use ultra-wideband wireless (UWB) radios that can easily penetrate building materials so that spanning an entire floor of a large building with just a few infrastructure nodes is possible. We build working prototypes, including the necessary hardware, and demonstrate the plug-and-play nature of our proposed solution. Our evaluation in three indoor spaces shows 1–2 meter-level localization accuracy with areas as large as 2241sq.m. We expect our explorations to re-trigger interest in novel applications for indoor spaces based on fine-grained indoor location knowledge. 

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   Localization of networked nodes is an essential problem in emerging applications, including first-responder navigation, automated manufacturing lines, vehicular and drone navigation, asset tracking, Internet of Things, and 5G communication networks. In this paper, we present Locate3D, a novel system for peer-to-peer node localization and orientation estimation in large networks. Unlike traditional range-only methods, Locate3D introduces angle-of-arrival (AoA) data as an added network topology constraint. The system solves three key challenges: it uses angles to reduce the number of measurements required by 4X and jointly uses range and angle data for location estimation. We develop a spanning-tree approach for fast location updates, and to ensure the output graphs are rigid and uniquely realizable, even in occluded or weakly connected areas. Locate3D cuts down latency by up to 75% without compromising accuracy, surpassing standard range-only solutions. It has a 0.86 meter median localization error for building-scale multi-floor networks (32 nodes, 0 anchors) and 12.09 meters for large-scale networks (100,000 nodes, 15 anchors). 

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