网络中心战下指挥控制决策系统研究

《网络中心战下指挥控制决策系统研究》由会员上传分享，免费在线阅读，更多相关内容在学术论文-天天文库。

1、中北大学博士学位论文网络中心战下指挥控制决策系统研究姓名：唐立军申请学位级别：博士专业：测试计量技术及仪器指导教师：王建中20080801地对C4SIR系统方案进行优选。根据网络中心战指挥控制系统的功能及特点，设计并实现了网络中心战下防空指挥控制决策仿真系统。具体对作战仿真系统的结构、设计过程及仿真建模方法等进行阐述；描述了网络中战下防空指挥控制决策系统的仿真框架及系统软件的设计原理，为构建适合信息化战场需求的网络中心战防空指挥控制决策系统提供了理论及技术依据。最后给出全文的总结和展望。关键词：网络中心战，指挥控制系统，决策，复杂武器系统，建模与仿真，动态组网，目标威胁估计，火力

2、优化分配，作战效能评估，作战效能预测，系统消费比，仿真系统AbstractNetworkcentricwarfareisnecessarytrendofinformationbattledevelopment，and弱oneimportantpartofit，commandandcontrolsystemprovidesrealtimeandreliablefightingcommanddecisionforweaponsystem，makingtheholisticfightingefficiencyofweaponsystemhaveitsfullplay．Thethesis

3、hasstudiedsomemaintheorymethodsreferredtothecommandandcontrolsystemofnetworkcentriewarfare，onthebasisofthese，asuitofthedecision—makingsimulationsystemofcommandandcontrolhasbeendesigned．Accordingtothecharactersandfunctionsofnetworkcentricwarfare，andintegratingthestructureoftacticsintemets，thed

4、ynamicrecom．binedecision-makingproblemofcommunicationnetworkinnetworkcentricwarfareisresearched．Thereinto，networkrecombinestrategyandlinkrecombinestrategyhavebeenresearchedconcretely,andviasimulationandtestingonthosetwodecision—makingmethods，validityandfeasibilityoftwodynamicrecombinestrategi

5、eshavebeenproved，whichprovideeffectivedecision-makingapproachforcommunicationnetworkofnetworkObjectthreatassessmentandfirepowerallocationaretwoimportantassistantdecision-makingproblemsoffightingofcommandandcontrolsystem．Aimingtothecharacteristicofobjectthreatassessment，anobjectthreatassessmen

6、tmodelbasedonsupportvectormachine(SVM)isputforward，andinordertomakemodelhassubjectiveandobjectivecharacteristic，fuzzysyntheticevaluationmethodisadopttoobtaintrainingandtestingdataforthismodel．Throughanumericalexampleofaerialdefenseobjectthreatassessmentandcomparingwithotherexistedmethods，ther

7、esultsshowtherationalityandsuperiorityofthemethod．Consideringthepreconditionofcounterwork‘betweenmulti—weaponandmulti-object，firepowerallocationmodelhavebeensolvedbygeneticalgorithm(GA)andparticleswarmoptimization(PSO)algorithmseparately，then