Range-Only EKF-Based Relative Navigation for UAV Swarms in GPS-Denied Zones

Achieving successful collaboration among a swarm of Unmanned Aerial Vehicles (UAVs) requires an accurate relative localization system. In scenarios where GPS is intermittently lost, UAVs require an alternative navigation system to conduct autonomous missions during GPS outages. Without an alternative, UAVs must rely solely on dead reckoning navigation based on the Inertial Measurement Unit (IMU), which can lead to the accumulation of errors. This paper presents a range only aided navigation system, where an Extended Kalman Filter (EKF) combines IMU data with range data from sensors that measure the distance between nodes in the swarm. This method mitigates the growth of position, navigation, and timing (PNT) errors during periods of GPS signal loss. To demonstrate the effectiveness of this approach, a combination of software simulations and hardware experiments were conducted. These involved a swarm of six drones in various scenarios, including circular, square, and blue-angels flight trajectories. The trajectories were designed to minimize significant geometric dilution of precision (GDOP). Statistical analysis of the simulation results indicates that this approach improves the estimates compared with dead reckoning alone, thereby reducing the growth of velocity and location errors when GPS is intermittently unavailable.