UCAV Cluster Task Assignment Algorithm Based on Adaptive ACO Algorithm

Unmanned Combat Aerial Vehicle (UCAV) cluster air combat is the main development direction of future air combat, and task assignment is an important sub-task in UCAV cluster air combat. Efficient task assignment scheme is of great significance to improve UCAV cluster combat capability. In this paper, a new task assignment objective function of UCAV cluster is designed to solve the problem of imperfect optimization index of task assignment objective function. The weighted fusion result of threat assessment value and total flight time of UCAV is used as the objective function. In order to solve the problem of insufficient constraints of the existing task assignment model, some constraints such as task timing constraints, multi-machine cooperation constraints, target type constraints, weapon type constraints and ammunition quantity constraints are designed. Aiming at the problems of “prematurity” and “stagnation” in the classical Ant Colony Optimization (ACO) algorithm, a UCAV cluster task assignment algorithm based on adaptive ACO algorithm is proposed. The simulation results show that, Compared with the classical ACO algorithm, the UCAV cluster task assignment algorithm based on adaptive ACO algorithm has better results and better real-time performance.