In this paper, The global market for unmanned aerial vehicles (UAV) is showing explosive growth. Moreover, UAVs are being actively used in various areas including the agriculture and service industries. For military purposes, UAVs perform diverse missions such as surveillance, reconnaissance and attacks. To successfully accomplish these missions, a UAV needs to travel to a designated point without being detected by opponents while keeping off the presence of high and obstructive geographic features and SAM sites. In these situations, the difficulty level of the mission drastically increases, which results in higher accident and failure rates.
Many research institutes have presented various algorithms and simulation results regarding the determination of the UAV’s flight path in order to improve the success rate of missions.
However, most UAV flight path selection algorithms developed in existing studies selected a flight path in a two-dimensional space, which is hardly applicable to real UAV missions. Moreover, other studies on three-dimensional flight paths selected a path in a two-dimensional plane and then applied vertical information or examined either circling flight or ascending flight by applying paths at a constant flight altitude. Thus, these methods can hardly be regarded as selecting a flight path in a three-dimensional space. Consequently, a composite method to determine an efficient path for each flight mode (circling or ascending) is required.
This study proposes an algorithm that identifies optimal paths for a UAV’s real flight modes of circling, descending, and ascending by comprehensively analyzing three-dimensional risk factors such as geographic features (mountains, valleys, etc.) and SAM sites. Finally, the effectiveness of the proposed algorithm is verified through simulation results.