Study on Smoke Screen Interference Shell Deployment Strategy under Different Circumstances

Abstract

This paper establishes a mathematical model based on the initial position and trajectory of enemy missiles, the positions of our real and decoy targets, the initial position of drones, the number of smoke grenades carried, deployment and detonation timing, and drone allocation. The model aims to find a global optimal solution to enhance the effective coverage duration of smoke clouds and improve drone combat effectiveness. For Problem 1, we first establish mathematical models for drone deployment of smoke interference grenades for enemy missiles M1, drones MY1, real targets, and decoy targets. Subsequently, we calculate their positions at any moment using relevant motion models. Finally, through a line-of-sight (LOS) occlusion model, real targets are abstracted into 16 test points to determine whether missile line-of-sight can be effectively occluded at any moment. The effective coverage duration is calculated by subtracting the initial and final times of effective occlusion. For Problem 2, we first define approximate ranges for four parameters: FY1's flight direction, speed, smoke interference grenade deployment point, and detonation point. We then narrow these parameter ranges using binary search and iteratively solve the objective function for these four parameters using an Evolutionary Search Genetic Algorithm (ESGA) optimized with an early termination mechanism. Genetic algorithm operations identify the maximum effective occlusion duration, with fitness analysis and patience value comparison used to determine whether early termination is necessary to avoid local optima. Finally, sensitivity analysis is conducted using differential evolution and particle swarm optimization models to verify solution accuracy after accounting for uncertain factors.