Better Smartphone Location Determination using Wi-Fi Outdoors

Project ID: 2531bd1623

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Research Theme: Information and Communication Technologies

Research Area(s): Pervasive and Ubiquitous Computing

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

Department Website

Lead Supervisor: Paul Groves

Project Summary:

Knowing precisely where you are is critical for smartphones and other mobile devices. Typically, these use global navigation satellite systems (GNSS) to determine their location outdoors. However, GNSS accuracy in urban areas is degraded by buildings blocking and reflecting the signals. GNSS jamming by criminals on earth and hostile states in space is also an increasing problem. Wi-Fi positioning is a firmly established alternative, but is largely limited to indoor use even though Wi-Fi signals can be detected outdoors near buildings having Wi-Fi.

Your challenge under this PhD project will be to use Wi-Fi signals to determine position outdoors. You will begin by investigating how variations in Wi-Fi signal strength can be used to infer position in outdoor urban environments and how this is affected by unpredictable factors such as passing people, vehicles and street furniture, building on earlier UCL PhD student research. You will also assess the accuracy of timing-based distance measurements . Next, you will design, develop and test Wi-Fi position determination algorithms for outdoor use, possibly using machine learning. The big challenge here is to get a reliable position solution from unreliable measurements. Finally, you will integrate these new Wi-Fi positioning algorithms with GNSS and step detection to get the best possible accuracy in challenging urban environments.

This research has many practical applications, such as navigation, including for the visually impaired; emergency caller location; tracking vulnerable people and valuable assets; situation awareness for emergency and security personnel; location-based gaming; and augmented reality.

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.