MTSP UAV Detection Problem Based on Ant Algorithm
Zehua Yue · 2018
To study the problem of UAV detection, a multi-traveler problem (MTSP) model and a two-dimensional in-plane point circle coverage model are established. The ant algorithm and the Monk Carlo algorithm are used to solve the model according to the minimum time. First, extract the number of effective cities under the constraints of effective detection range and maneuverability of the drone. Secondly, the minimum time of flight is minimized as the objective function, and the MTSP UAV detection model based on 1936 traversal points is established. Finally, using the ant algorithm to iteratively solve, and smoothing the track by cubic B-spline interpolation to obtain a flight plan that satisfies the constraints. The shortest time to get is 7.28241h.