简介:水下多目标跟踪逻辑与决策是水下航行器多目标跟踪中需解决的技术难点.目前用于水下多目标跟踪决策的方法都假设各个决策因素相互独立,而实际上水下多目标跟踪决策的因素之间存在着相互影响.本文根据这一特点,建立了水下多目标跟踪决策的指标集和相应的ANP决策模型,提出了基于ANP的水下多目标跟踪逻辑与决策方法.该方法将水下多目标跟踪决策的指标集纳入网络层次结构模型,并通过模型解算得到优化的多目标跟踪决策,具有决策结果比现有方法更加合理、稳健的特点.仿真结果表明该方法是在多目标跟踪决策因素之间存在相互影响情况下解决水下多目标跟踪逻辑与决策问题的有效方法.
简介:Inunderwatertargetdetection,thebottomreverberationhassomeofthesamepropertiesasthetargetecho,whichhasagreatimpactontheperformance.Itisessentialtostudythedifferencebetweentargetechoandreverberation.Inthispaperbasedontheuniqueadvantageofhumanlisteningabilityonobjectsdistinction,theGammatonefilteristakenastheauditorymodel.Inaddition,time-frequencyperceptionfeaturesandauditoryspectrafeaturesareextractedforactivesonartargetechoandbottomreverberationseparation.Thefeaturesoftheexperimentaldatahavegoodconcentrationcharacteristicsinthesameclassandhavealargeamountofdifferencesbetweendifferentclasses,whichshowsthatthismethodcaneffectivelydistinguishbetweenthetargetechoandreverberation.