Distributed loitering synchronization is the process whereby a group of fixed-wing Unmanned Aerial Vehicles (UAVs) align with each other while they follow a circular path in the air. This process is essential to establish proper initial conditions for missions in the real world. We evaluate the performance of three synchronization algorithms using a setup of continuously moving fixed-wing drones randomly placed around a loitering circle. We consider the algorithm based on distributed consensus as a baseline. We propose two methods: the Minimum Of Shortest Arc (MOSA) algorithm that outperforms the baseline in this setup and Firefly multi-Pulse Synchronization (FPS), which is inspired by firefly synchronization. The latter method requires 10 times less communication while maintaining a performance comparable to the baseline. These algorithms were first tested in a simple simulation, then a more realistic simulation environment using Gazebo in which fixed-wing dynamics are considered. The proposed algorithms are rigorously tested in simulation through multiple trials involving a group of 10 UAVs, confirming the effectiveness of our approaches. The results were then validated in real flights using 3 fixed-wing drones.