Combat Target Assignment of Multiple Space Vehicles Using a Non-dominated Sorting Kepler Optimization Algorithm

In the complex space confrontation environment, how to effectively assign space vehicles to enemy targets for combat operations has become an important research hotspot. The traditional method of target assignment takes the maximization of the operational benefit of weapons as the single goal, which simplifies the problem too much and cannot solve the problem of target assignment comprehensively. In addition, the existing intelligent algorithms often have the problem of low convergence accuracy, which is difficult to meet the real-time requirements. Aiming at the above problems, a combat target allocation method for multiple space vehicles based on Non-dominated Sorting Kepler Optimization Algorithm (NSKOA) was proposed. By integrating non-dominated sorting and crowding calculation into the traditional Kepler-based Optimization algorithm (KOA), the proposed method achieved better multi-objective optimization performance. The simulation results show that NSKOA is superior to other multi-objective optimization algorithms in the combat target allocation model. Under the same conditions, NSKOA provides superior target allocation scheme, which effectively verifies its effectiveness.