2023-24-project-catalogue

###Improving Outdoor Positioning using Wi-Fi Signals

Project ID: 2228bd1063 (You will need this ID for your application)

Research Theme: Information and Communication Technologies

UCL Lead department: Civil, Environmental and Geomatic Engineering (CEGE)

Department Website

Lead Supervisor: Paul Groves

Project Summary:

Location awareness is critical for many smartphone applications and other mobile devices. Typically, these devices use primarily global navigation satellite systems (GNSS) for outdoor positioning. However, GNSS accuracy in urban areas is degraded due to buildings blocking and reflecting the signals. Wi-Fi positioning is now firmly established as an alternative, but is largely limited to indoor use. Your challenge under this PhD project will therefore be investigate the feasibility of using Wi-Fi for outdoor positioning. You will begin by assessing how the received signal strength (RSS) of Wi-Fi signals varies with position in outdoor urban environments and how it is affected by other factors such as passing people, vehicles and street furniture. You will also characterise the accuracy of distance measurements from the new Wi-Fi round-trip timing (RTT) protocols in these environments. Next, you will design, development and testing of Wi-Fi RSS and RTT positioning algorithms for outdoor use. Finally, you will integrate these new Wi-Fi positioning algorithms with GNSS positioning to get the best possible accuracy in challenging urban environments. This research can benefit many different positioning applications, including situation awareness of emergency, security and military personnel; emergency caller location; navigation, including for the visually impaired; tracking vulnerable people and valuable assets; location-based charging; and mapping environmental features. Through your research, you will develop skills in experimental work, algorithm design, software development, data analysis and effective communication. You will also participate in UCL’s flexible and extensive Doctoral Skills Development Programme. Applicants must hold or expect to obtain a 1st class or upper 2nd class bachelors or masters degree in engineering, physics, maths or computer science.