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http://hdl.handle.net/11375/24173
Title: | Design of an Ultra-Wide Band based Indoor Positioning System |
Authors: | Li, Jun |
Advisor: | Zheng, Rong |
Department: | Computing and Software |
Keywords: | Ultra-Wide Band;Indoor Positioning System;Hardware design;Two-Way Ranging |
Publication Date: | 2018 |
Abstract: | In recent years, the indoor positioning system (IPS) has attracted significant interests in both academical research and industrial development. It has seen many applications, such as hostage search and rescue, indoor navigation, and warehouse management, all of which can take advantage of precise positioning. However, in indoor environments, traditional methods, like the Global Positioning System (GPS), are usually either unreliable or incorrect because of the complicated physical characteristics of various objects reflecting and dispersing signals, such as the presence of people, walls, obstructions, and furniture. In contrast to other technologies such as WiFi and Bluetooth, which are not suitable to extract accurate timing information, UWB technology has the potential to reach center-meter level accuracy in indoor positioning. In this thesis, we developed a real-time, low-cost, IPS based on commercial-off-the-shelf UWB transceivers. Both the Two Way Ranging (TWR) and Time Difference of Arrival (TDOA) approaches have been implemented to obtain a target's location. To alleviate the effect of multipath propagation, we detect the presence of outliers by comparing the first path signal level and estimated receiving signal level. Moreover, we have designed the Printed Circuit Board (PCB) and evaluated performance by deploying the system both in a lab environment and in a two-story historical building during the 2018 Microsoft Indoor Localization Competition. The results show that we achieve a 28.9cm 95%-quantile 2D tracking error in the lab environment and a 92cm average tracking error for 3D localization on the Microsoft Indoor Localization Competition site. |
URI: | http://hdl.handle.net/11375/24173 |
Appears in Collections: | Open Access Dissertations and Theses |
Files in This Item:
File | Description | Size | Format | |
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Li_Jun_201808_Master of Science.pdf | 3.35 MB | Adobe PDF | View/Open |
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