Effectiveness Evaluation of Heterogeneous UAV Swarms Based on a Hybrid Model
This paper presents a hybrid model based on availability dependability capability(ADC)system performance evaluation and back propagation(BP)neural network prediction to realize a rapid performance evaluation of UAV swarms and cope with the diversity of UAV swarm configuration and state and the complexity of performance calculation.By analyzing the components of swarm performance,a capability index system including the general platform capability,system-level capability,and task execution capability of UAVs is established.By using the ADC method,a swarm combat performance sample set is generated,and the BP neural network is used to construct a comprehensive combat performance evaluation model of UAV parameters and capability indexes.The evaluation model is used to evaluate the comprehensive combat performance of heterogeneous UAV swarms.The results show that the evaluation error of this model can reach less than 5%,and the evaluation time based on samples is less than three hours,which verifies the effectiveness and high efficiency of this model in the evaluation of heterogeneous UAV swarm performance.At the same time,by analyzing the influence of quantity and configuration on the comprehensive performance of UAV swarms,feasible suggestions on the configuration of heterogeneous UAV swarms are obtained.
heterogeneous UAVswarm systemperformance evaluationavailability dependability capability-back propagation(ADC-BP)neural networkhybrid model
万方数据
维普
