Abstract
Radio Frequency Interference (RFI), either intentional or unintentional in nature, can have significant impact on the performance of systems utilizing GNSS receivers. It can therefore be beneficial for a commercial autonomous system to have the capability to detect the presence of RFI, and determine the source's position, speed and course over ground to potentially maneuver away from the affected region. Typical approaches involve deployment of complex infrastructure to measure different signal parameters making them cost-ineffective. Several low cost receivers have been proven a better alternative as they are capable to output the parameters required by the localization system. In this paper, a Carrier-to-Noise density ratio (\mathbf{C}/\mathbf{N}_{0}) model, describing the variations of \mathbf{C}/\mathbf{N}_{0} measurements as a function of the distance between jammer and victim receiver is applied to a network of cooperating Unmanned Aerial Vehicles (UAVs) to enable collaborative jammer localization. Two different techniques are studied, the first one is based on the synthetic array principle allowing jammer localization by a single node. In this paper, the original method is extended to a three-dimensional case. The second approach is based on combining the measurements obtained by all cooperating nodes. Both of the techniques are verified through simulations of a dynamic jammer and dynamic cooperating UAV network scenario in a controlled lab environment. The obtained results are discussed in terms of achieved accuracy as well as various factors impacting the performance of the approaches.