An enhanced autonomous counter-drone system with jamming and relative positioning capabilities

Abstract

The rise of unlawful and unauthorized operations of unmanned aerial vehicles (UAVs) has led to the need for versatile counter-drone systems. In this work, an autonomous counter-drone system is developed (denoted as RPS-JS-DNN — relative positioning and simultaneous jamming system with deep neural network learning), where a pursuer drone employs algorithms for detection, tracking, and jamming a rogue drone in real-time. The proposed system incorporates wireless interception capabilities to jam the rogue drone, together with self-positioning for the pursuer drone by employing a relative positioning system methodology based on signals of opportunity fused with inertial measurements. The performance of the proposed system depends on the switching between the jamming and self-localization modules, essentially leading to a jamming duration and positioning accuracy trade-off. The overall objective is the maximization of the jamming module’s operation time, while also increasing the performance of the self-localization module. In the proposed system, a software-defined radio (SDR) is utilized, facilitating jamming and spectrum sweeping capabilities to realize the desired GPS disturbance and self-localization, respectively. A prototype system is developed, implemented, deployed, and tested over extensive field experiments, demonstrating its effectiveness to jam a rogue drone and also achieve relative navigation in a real-world environment under various parameter settings.