Countering Spoofing Attacks for Unmanned Aerial Vehicles Using Multi-Constellation GNSS

Global navigation satellite system (GNSS) is an important part of unmanned aerial vehicles (UAVs), because it can provide UAVs with real-time location information for navigation and tracking. However, due to the increasing open-ness of GNSS, it has become more vulnerable to various cyber-attacks. The spoofing attack is a typical kind that can send fake information to confuse the operations of a UAV. It will cause serious consequences, for example, crash, thus the research on the methods of countering spoofing attacks is significant. This paper is concerned with a UAV suffering from a spoofing attack when flying on a path, while the extended Kalman filter (EKF) and the nonlinear model predictive control (NMPC) methods are respectively adopted for estimation and control. In order to counter malicious attackers, a multi-constellation GNSS is equipped for the UAV, which means the UAV can simultaneously receive multiple location information. After detecting the spoofed GNSS signal with the
$\chi^{2}$
detector, the data from other constellations and an inertial measurement unit (IMU) will be gathered for centralized fusion state estimation, guaranteeing high estimation performance. Finally, the software simulation on a well-known platform called Gazebo is provided to show the effectiveness of the proposed methods.