Research on Optimization of Smoke Screen Bullet Drop Strategy for Unmanned Aerial Vehicles Based on Simulated Annealing Algorithm

Abstract

: This article focuses on the use of drones to deploy smoke bombs in complex scenarios to deal with incoming missiles, aiming to design an optimal deployment strategy to maximize the effective shielding time of targets. This article first considers fixed parameters such as drone flight speed, direction, smoke bomb deployment, and detonation time. On this basis, precise motion trajectory models for missiles, drones, and smoke bombs were established. Secondly, the geometric judgment criteria for "line of sight obstruction" and the consideration of the 20 second effective time of the smoke screen have been added. At the same time, a complete numerical integration model for the duration of occlusion was established. By numerical solution, the effective masking time under this strategy is determined to be 1.4190s. Then, the flight speed, direction, deployment time, and detonation delay of the drone are used as decision variables to establish a parameterized dynamic trajectory model related to the decision variables, and constraints such as the range of drone flight speed are considered. Finally, the simulated annealing algorithm was used to solve the problem, and the maximum effective shielding time obtained was 4.7500 seconds. With the independent deployment and detonation time of three smoke bombs under a single flight strategy as the core decision variables, a dynamic system was established to describe the spatiotemporal trajectories of the three smoke clouds. Secondly, the ideas of "deployment interval not less than 1 second" and "maximizing the sum of shielding time" were added, ultimately establishing a complete multi-dimensional constraint optimization model.