Signal analysis for WiFi positioning system
Wi-Fi localization is important to determine the predicted location of the network device. In this project, localization techniques were studied and implemented to perform signal analysis. Simulation of RSSI values based on a given location and simulation of an exact location based on a given set of...
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sg-ntu-dr.10356-528022023-03-03T20:41:02Z Signal analysis for WiFi positioning system Foo, Mabel Mei Ling. Chang Kuiyu School of Computer Engineering Emerging Research Lab DRNTU::Engineering::Computer science and engineering::Computing methodologies::Simulation and modeling Wi-Fi localization is important to determine the predicted location of the network device. In this project, localization techniques were studied and implemented to perform signal analysis. Simulation of RSSI values based on a given location and simulation of an exact location based on a given set of RSSI values are performed. These results are visualized in a graphical user interface and analyzed in detailed. The implementation of the simulation is based on the k-Nearest Neighbor algorithm and the Wi-Fi triangulation localization method. Euclidean distance was used as the proximity measure for the nearest neightbor algorithm. Bachelor of Engineering (Computer Science) 2013-05-27T07:44:21Z 2013-05-27T07:44:21Z 2013 2013 Final Year Project (FYP) http://hdl.handle.net/10356/52802 en Nanyang Technological University 31 p. application/pdf |
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DRNTU::Engineering::Computer science and engineering::Computing methodologies::Simulation and modeling Foo, Mabel Mei Ling. Signal analysis for WiFi positioning system |
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Wi-Fi localization is important to determine the predicted location of the network device. In this project, localization techniques were studied and implemented to perform signal analysis. Simulation of RSSI values based on a given location and simulation of an exact location based on a given set of RSSI values are performed. These results are visualized in a graphical user interface and analyzed in detailed. The implementation of the simulation is based on the k-Nearest Neighbor algorithm and the Wi-Fi triangulation localization method. Euclidean distance was used as the proximity measure for the nearest neightbor algorithm. |
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Chang Kuiyu |
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Chang Kuiyu Foo, Mabel Mei Ling. |
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Final Year Project |
author |
Foo, Mabel Mei Ling. |
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Foo, Mabel Mei Ling. |
title |
Signal analysis for WiFi positioning system |
title_short |
Signal analysis for WiFi positioning system |
title_full |
Signal analysis for WiFi positioning system |
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Signal analysis for WiFi positioning system |
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Signal analysis for WiFi positioning system |
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signal analysis for wifi positioning system |
publishDate |
2013 |
url |
http://hdl.handle.net/10356/52802 |
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1759857044770258944 |