Intelligent Target Detection Method of Unmanned Aerial Vehicle Swarms

One of the areas of use of Unmanned Aerial Vehicles (UAVs) developed for use in various missions in military and public areas is target search activities in large terrain environments.  In the event that the size of the target to be sought expands and the number increases, the use of UAVs alone is insufficient, and as a solution to this problem, UAV swarms are created. The use of UAV swarms in target detection shortens the search time and offers the opportunity to search in larger areas. In this study, it is aimed to establish a lot of UAV systems to search targets in the simulation environment and to detect the targets fleeing from the search zone. In the study, the speed and position information of the swarm UAVs were updated by using Particle Swarm Optimization, and the speeds of the UAVs in the swarm were calculated according to the position and speed values between the neighboring UAVs.  Coordinate data has been added to the functions created to determine the matrix values of the area to be scanned to achieve the goals. When the road planning of the swarm UAVs was created, the rotations of the UAVs were softened by using Dubins and Bezier Curves from start to finish in the base area.  As a result, the swarm UAVs reached a speed of up to 30 km / h within the x and y coordinates of the simulation map in the range of -800 to 1000, and the control and destruction of the target was carried out in 02.29 minutes. The simulation results contribute to reducing the target search process in multiple UAV missions.