Localization, Beacon Placement and Mapping for Range-Based Indoor Localization Systems

Precise time and location are at the core of many Cyber Physical Systems (CPS) applications, as can be seen by the impact of the Global Positioning System. Indoor<br>localization systems will enable applications ranging from navigation, asset tracking and secure device interaction to mixed reality experiences and emergency support<br>(e911). However, indoor environments are full of barriers, which attenuate and scatter signals that make it challenging to provide high coverage in a cost-effective and reliable manner at scale. In this dissertation, we will show steps towards designing scalable indoor localization systems in a systematic manner that perform effectively across unpredictable environments and are compatible with several emerging technologies. Specifically, we focus on the class of range-based beacon technologies because<br>(1) they can provide accurate ranges given line-of-sight, (2) they can instantly determine a location without requiring devices to move long distances and (3) there<br>are growing standards for range-based technologies such as 802.11mc, BLE5 and ultra-wideband. Unfortunately, installing and mapping beacons is both expensive<br>and time consuming, which continues to hinder adoption. Further, acquiring location from ranges in realistic settings can be inaccurate and slow when a low density of<br>beacons and non-line-of-sight signals are encountered. While having an abundance of beacons increases accuracy and decreases the time to acquire the initial location,<br>it also increases the cost of the system. This thesis aims to lower the barrier to adoption of range-based beacon technologies by reducing the infrastructure required<br>while maintaining high performance in terms of accuracy and time taken to acquire the location and orientation. Our approach leverages additional sources of location<br>information, like geometrical constraints from floor plans to acquire location with a reduced number of beacons, magnetic sensing to rapidly acquire orientation and visual<br>inertial odometry for setup and continuous tracking. We present techniques for location estimation and system provisioning, including beacon placement and map<br>generation, and show how these techniques apply to CPS applications like mobile augmented reality and first-responder localization.