Indoor/Outdoor Location of Cellular Handsets Based on Received Signal Strength
Jian Zhu
123 pages
Directed by Dr. Gregory D. Durgin
Accurate geo-location is an important emerging technology for public safety, commercial use, and military application. Especially, in the United States, the wireless Enhanced 911 (E911) rules by the Federal Communication Commission (FCC) seek to provide 911 dispatchers with additional information on wireless 911 calls.
This dissertation presents a novel technique for indoor/outdoor location of cellular handsets based on received signal strength (RSS) measurements taken by a cellular handset of the surrounding base stations. RSS location accuracy for different environments is studied as a function of base station separation distance, cell sector density, measurement density, radio propagation environment, and accuracy of measurement. The analytical and experimental results in this thesis serve as a guideline for the accuracy of RSS signature location technology under different conditions. Accurate outdoor to indoor penetration models are proposed and validated for dense urban areas by introducing pseudo-transmitters to simulate the wave-guiding effects in urban canyon environments. A set of location algorithms is developed to improve location accuracy. Furthermore, an algorithm to discriminate between indoor and outdoor users is proposed and validated. The research results demonstrate the feasibility of RSS location techniques to meet the FCCs requirements for E911 accuracy in urban and semi-urban environments. The techniques remain accurate for indoor handsets. The results also suggest that a hybridization of the handset-based GPS method and the RSS signature method may prove to be the most effective solution for locating handsets across a range of environments; including rural, suburban, dense urban, and indoor.
| Identifer | oai:union.ndltd.org:GATECH/oai:smartech.gatech.edu:1853/11489 |
| Date | 19 May 2006 |
| Creators | Zhu, Jian |
| Publisher | Georgia Institute of Technology |
| Source Sets | Georgia Tech Electronic Thesis and Dissertation Archive |
| Language | en_US |
| Detected Language | English |
| Type | Dissertation |
| Format | 13209289 bytes, application/pdf |
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