通信星座弹性评估权值确定方法研究
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摘要
太空环境日益复杂,通信星座的全球覆盖、超视距通信等优势使其具有极高的存在必要性;为保证通信任务的可靠性,开展通信星座弹性评估研究,为建设弹性通信星座提供参考;针对通信星座弹性意义及特点,构建通信星座弹性评估指标体系,并对权重赋值问题进行分析,确定数学模型;针对层次分析法在判断矩阵一致性差时求解特征值困难的不足,提出采用生物地理学优化算法求解权值问题;通过对BBO算法中的迁移机制、迁移算子和突变机制进行改进,实现了判断矩阵排序权值与一致性的统一;并与基本BBO算法、GA算法、GA-PSO算法、AHP算法进行比较验证,结果表明改进BBO算法在收敛速度、优化精确性以及局部寻优能力方面较优;随后,采用改进BBO算法对通信星座弹性评估指标体系权值进行分析计算,得出通信星座弹性评估指标体系权重,可为后续通信星座弹性评估提供一定帮助。
As the space environment becomes increasingly complex,the advantages of the global coverage and over-the-horizon communication of communication constellation make it extremely necessary.In order to ensure the reliability of communication tasks,the evaluation of communication constellation resilience is carried out to provide reference for building resilient communication constellation.According to the meaning and characteristics of communication constellation's resilience,an index system for evaluating communication constellation resilience is constructed,and the weight assignment problem is analyzed to determine the mathematical model.In order to solve the problem that analytic hierarchy process(AHP)is difficult to determine eigenvalues when the consistency of the matrix is poor,a Biogeography-Based Optimization Algorithm is used to solve the weight problem.By improving the migration mechanism,the migration operator and the mutation mechanism in the BBO algorithm,the unification of weights and consistency of the judgment matrix are achieved.The improved BBO algorithm is compared with the basic BBO algorithm,GA algorithm,GA-PSO algorithm,and AHP algorithm.The results show that the improved BBO algorithm is superior in convergence speed,optimization accuracy,and local search ability.Then,using the improved BBO algorithm to weight the indicator system,the communication constellation's resilience assessment weight system is obtained,which can provide some help for the subsequent resilience assessment of the satellite communication system.
As the space environment becomes increasingly complex,the advantages of the global coverage and over-the-horizon communication of communication constellation make it extremely necessary.In order to ensure the reliability of communication tasks,the evaluation of communication constellation resilience is carried out to provide reference for building resilient communication constellation.According to the meaning and characteristics of communication constellation's resilience,an index system for evaluating communication constellation resilience is constructed,and the weight assignment problem is analyzed to determine the mathematical model.In order to solve the problem that analytic hierarchy process(AHP)is difficult to determine eigenvalues when the consistency of the matrix is poor,a Biogeography-Based Optimization Algorithm is used to solve the weight problem.By improving the migration mechanism,the migration operator and the mutation mechanism in the BBO algorithm,the unification of weights and consistency of the judgment matrix are achieved.The improved BBO algorithm is compared with the basic BBO algorithm,GA algorithm,GA-PSO algorithm,and AHP algorithm.The results show that the improved BBO algorithm is superior in convergence speed,optimization accuracy,and local search ability.Then,using the improved BBO algorithm to weight the indicator system,the communication constellation's resilience assessment weight system is obtained,which can provide some help for the subsequent resilience assessment of the satellite communication system.
引文
[1]Mcleod G,Nacouzi G,Dreyer P,et al.Enhancing space resilience through non-materiel means[R/OL].http://www.rand.org/content/dam/rand/pubs/research_reports/RR1100/RR1169/RAND_RR1169.pdf.2016.[2017-03-24].
[2]Turner J S.A Methodology For Measuring resilience in a satellite-based communication Network[R].AIR Force Institute of Technology Wright-Patterson AFB OH graduate School of Engineering and Management,2014.
[3]严晓芳,饶玉柱.太空系统的适应弹性研究[J].中国电子科学研究院学报,2014,9(5):458-462.
[4]潘星,蒋卓,杨艳京.基于弹性的体系组件重要度及恢复策略[J].北京航空航天大学学报,2017(9).
[5]许相莉,胡晓峰,秦永刚.基于“四域”的卫星通信系统效能评估指标体系[J].指挥与控制学报,2015,1(2):220-222.
[6]评估理论和方法及其军事应用[M].北京:国防工业出版社,2013.
[7]Simon D.Biogeography-Based Optimization[J].IEEE Transactions on Evolutionary Computation,2008,12(6):702-713.
[8]Dan S,Ergezer M,Du D,et al.Markov models for biogeography-based optimization[J].IEEE Transactions on Systems Man&Cybernetics Part B Cybernetics A Publication of the IEEE Systems Man&Cybernetics Society,2011,41(1):299-306.
[9]罗丹,张宏立,任甜甜,等.基于混合生物地理学算法的非线性系统辨识[J].计算机仿真,2015,32(1):416-419.
[10]Dan S.Evolutionary optimization algorithms.Biologically inspired and population-based approaches to computer intelligence[J].Genetic Programming,2013.
[11]Khademi G,Mohammadi H,Dan S.Hybrid invasive weed/biogeography-based optimization[J].Engineering Applications of Artificial Intelligence,2017,64:213-231.
[12]毕晓君,王珏,李博.基于混合生物地理学优化的多目标优化算法[J].系统工程与电子技术,2014,36(1):179-186.
[13]王珏.生物地理学优化算法的研究及应用[D].哈尔滨工程大学,2013.
[14]金菊良,魏一鸣,付强,等.计算层次分析法中排序权值的加速遗传算法[J].系统工程理论与实践,2002,22(11):39-43.
[2]Turner J S.A Methodology For Measuring resilience in a satellite-based communication Network[R].AIR Force Institute of Technology Wright-Patterson AFB OH graduate School of Engineering and Management,2014.
[3]严晓芳,饶玉柱.太空系统的适应弹性研究[J].中国电子科学研究院学报,2014,9(5):458-462.
[4]潘星,蒋卓,杨艳京.基于弹性的体系组件重要度及恢复策略[J].北京航空航天大学学报,2017(9).
[5]许相莉,胡晓峰,秦永刚.基于“四域”的卫星通信系统效能评估指标体系[J].指挥与控制学报,2015,1(2):220-222.
[6]评估理论和方法及其军事应用[M].北京:国防工业出版社,2013.
[7]Simon D.Biogeography-Based Optimization[J].IEEE Transactions on Evolutionary Computation,2008,12(6):702-713.
[8]Dan S,Ergezer M,Du D,et al.Markov models for biogeography-based optimization[J].IEEE Transactions on Systems Man&Cybernetics Part B Cybernetics A Publication of the IEEE Systems Man&Cybernetics Society,2011,41(1):299-306.
[9]罗丹,张宏立,任甜甜,等.基于混合生物地理学算法的非线性系统辨识[J].计算机仿真,2015,32(1):416-419.
[10]Dan S.Evolutionary optimization algorithms.Biologically inspired and population-based approaches to computer intelligence[J].Genetic Programming,2013.
[11]Khademi G,Mohammadi H,Dan S.Hybrid invasive weed/biogeography-based optimization[J].Engineering Applications of Artificial Intelligence,2017,64:213-231.
[12]毕晓君,王珏,李博.基于混合生物地理学优化的多目标优化算法[J].系统工程与电子技术,2014,36(1):179-186.
[13]王珏.生物地理学优化算法的研究及应用[D].哈尔滨工程大学,2013.
[14]金菊良,魏一鸣,付强,等.计算层次分析法中排序权值的加速遗传算法[J].系统工程理论与实践,2002,22(11):39-43.