The purpose of this work is to develop a localization algorithm that can be used by flying UAVs to locate Wi-Fi devices on the ground. Assuming uncooperative target, we measure the RSSI on the packets that are periodically and spontaneously broadcasted by the Wi-Fi cards, and we use this information to estimate their position. GPs allowed us to reinforce the system against the noise that affects the measurements, and bayesian optimization proved an efficient way for sampling
Machine learning techniques for geolocalization of Wi-Fi devices using flying Unmanned Aerial Vehicles
Carpin, Mattia
2015/2016
Abstract
The purpose of this work is to develop a localization algorithm that can be used by flying UAVs to locate Wi-Fi devices on the ground. Assuming uncooperative target, we measure the RSSI on the packets that are periodically and spontaneously broadcasted by the Wi-Fi cards, and we use this information to estimate their position. GPs allowed us to reinforce the system against the noise that affects the measurements, and bayesian optimization proved an efficient way for samplingFile in questo prodotto:
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Utilizza questo identificativo per citare o creare un link a questo documento:
https://hdl.handle.net/20.500.12608/19856