姜露 - 北京工商大学 - 计算机与信息工程学院

个人简介

姜露部门：北京工商大学计算机与信息工程学院电子信息系职称：讲师教育背景： 2009-2013，青岛大学获工学学士学位 2013-2019，北京理工大学获工学博士学位主要学术成果：近年来发表论文9篇，授权、受理国家发明专利2项。

研究领域

状态估计、数据融合

近期论文

查看导师新发文章（温馨提示：请注意重名现象，建议点开原文通过作者单位确认）

[1]LuJiang,LipingYan,YuanqingXia,QiaoGuo,MengyinFu,DistributedMulti-sensorDataFusioninWirelessSensorNetworksBasedonANovelEvent-triggeredStrategy,JournalofTheFranklinInstitute,DOI:10.1016/j.jfranklin.2018.04.021. [2]LuJiang,LipingYan,YuanqingXia,QiaoGuo,MengyinFu,YangLiu,KunfengLu.AsynchronousMultirateMultisensorDataFusionoverUnreliableMeasurementswithCorrelatedNoise,IEEETransactionsonAerospaceandElectronicSystems,2017,53(5):2427-2437. [3]LipingYan,LuJiang*,YuanqingXia,Event-triggeredSequentialFusionEstimationwithCorrelatedNoises,ISATransactions,DOI:10.1016/j.isatra.2019.07.029. [4]LipingYan,LuJiang,YuanqingXia,MengyinFu.StateEstimationandDataFusionforMultirateSensorNetworks.InternationalJournalofAdaptiveControlandSignalProcessing,2016,30(1):3-15. [5]LipingYan,LuJiang,JunLiu,OptimalDistributedKalmanFilteringFusionforMultirateMultisensorDynamicSystemswithCorrelatedNoiseandUnreliableMeasurements,IETSignalProcessing,2018,12(4):522-531. [6]LuJiang,LipingYan,YuanqingXia,QiaoGuo,MengyinFu,Event-triggeredMultisensorDataFusionwithCorrelatedNoise,Fusion2017,Xi’an,China,July10-July13,2017:1-8. [7]LuJiang,LipingYan,YuanqingXia,MengyinFu.OptimalDistributedFusionforStateEstimationinMultirateWirelessSensorNetworks,Proceedingsofthe34thChineseControlConference,Hangzhou,China,July28-July30,2015:4851-4856. [8]LuJiang,LipingYan,BoXiao,YuanqingXia,MengyinFu.SequentialFusionandStateEstimationforAsynchronousMultirateMultisensorDynamicSystems,Proceedingsofthe33thChineseControlConference,Nanjing,China,July28-July30,2014:291-296. [9]LipingYan,JunLiu,LuJiang,Optimalsequentialestimationformultiratedynamicsystemswithunreliablemeasurementsandcorrelatednoise,Proceedingsofthe36thChineseControlConference,Chengdu,China,July27-29,2016:4900-4905. [10]闫莉萍，姜露，夏元清，付梦印。一种多速率观测数据的状态估计和数据融合方法，授权发明专利，申请号：ZL201410659316.1 [11]闫莉萍，姜露，夏元清等。一种相关噪声环境下事件触发的多传感器融合估计方法，受理发明专利，申请号：ZL201811582146.6