UAV SMOKE-SCREEN OBSCURATION EVALUATION AND STRATEGY OPTIMIZATION VIA TIME-STEPPING SIMULATION AND SIMULATED ANNEALING

Abstract

This paper develops a simulation-based framework for evaluating and optimizing UAV-deployed smoke-screen obscuration in missile engagement scenarios. First, the UAV, smoke cloud, missile, and protected target are described through a unified kinematic model, and angle and distance criteria are used to determine whether the smoke cloud effectively blocks the missile-target line. The valid time steps are accumulated to obtain the total effective obscuration duration, which provides a quantitative basis for strategy comparison. Second, the deployment problem is formulated as a constrained optimization task with UAV flight direction, flight speed, release time, and detonation delay as decision variables. A simulated annealing algorithm, combined with neighborhood search, exponential cooling, and bounded L-BFGS-B local refinement, is used to maximize the effective obscuration duration. Numerical results show that the baseline strategy provides 1.420 s of effective obscuration, while the optimized strategy increases it to 4.60 s, demonstrating the feasibility of the time-stepping simulation and optimization pipeline for smoke-screen deployment design.