Research on purely azimuthal passive localization method in UAV formation flight

Unmanned aerial vehicle (UAV) swarms have emerged as a pivotal technological direction in both future warfare and civilian applications, owing to their inherent advantages in intelligence, cost-effectiveness, and high survivability. This study addresses the bearings-only passive localization challenge in UAV formation flight through a novel integrated model combining an Angle of Arrival (AOA) algorithm, Monte Carlo simulations, a greedy strategy, and particle swarm optimization. By establishing a polar coordinate system integrated with the sine theorem and geometric analysis, we successfully resolved the localization and formation adjustment issues in circular configurations. Experimental results demonstrate that unique and effective localization can be achieved with merely two signal-transmitting UAVs. Furthermore, the implementation of greedy strategy and particle swarm optimization enables efficient formation redistribution, supporting nine UAVs in uniform distribution with 40° intervals while maintaining angular error below 0.28°. This research provides a theoretical foundation for advancing autonomous control capabilities in UAV swarm operations.