As GPS signals are of low power, the receiving end is always highly susceptible to interference, both unintentional and deliberate. As such there is a need to develop practical ways of detecting and localizing interference sources. This paper evaluates different methods of localization, and also demonstrates a novel method of both practical and cheap localization.

Global Navigation Satellite Systems (GNSS) have found wide adoption in various applications, be they military, civilian or commercial. The susceptibility of GNSS to radio-frequency interference can, thus, be very disruptive, even for emergency services, therefore threatening people's lives. An early prototype of a system providing relatively cheap widescale GNSS jamming detection, called J911, is explored in this thesis. J911 is smartphone-based crowdsourcing of GNSS observations, most interesting of which are carrier-to-noise-density ratio (<img src="http://www.diva-portal.org/cgi-bin/mimetex.cgi?%5Cfrac%7BC%7D%7BN_0%7D" />) and Automatic Gain Control (AGC) voltage. To implement the prototype, an Android application to provide the measurements, a backend to parse and store the measurements, and a frontend to visualize the measurements were developed. In real-world use, the thesis argues, the J911 system would best be implemented over existing Enhanced 9-1-1 (E911) infrastructure, becoming a standardized part of the Public Switched Telephone Network (PSTN). The Android application, running on a smartphone, would periodically construct messages to be sent to the backend over an Internet connection. The messages would include: current location from all location providers available in Android OS, observed satellites from all supported constellations, the satellites' <img src="http://www.diva-portal.org/cgi-bin/mimetex.cgi?%5Cfrac%7BC%7D%7BN_0%7D" />, and a timestamp. Once a message is received on the backend, the data would be extracted and stored in a database. The frontend would query the database and produce a map with the collected datapoints overlaid on top of it, whose color indicates received signal strength at that point. When a jammer gets close enough to a few smartphones, they will all be jammed, which is easily observed on the map. On top of that, if enough samples are gathered, a Power Difference of Arrival localization algorithm can be used to localize the jammer. The smartphones that the system was planned to be tested with did not support AGC level readings, therefore in order to obtain AGC levels over time, a few SiGe GN3S Samplers, which are radio-frequency frontends, were used. In eastern Idaho, United States, over three nights in July 2017, an exercise, named 2017 DHS JamX, was performed with the help of the US Department of Homeland Security. Sadly, the approval for the publication of the test results did not come in time to be included in this thesis.