|Table of Contents|

WirelessTomographyPositioningMethodBasedonKPCA(PDF)

《南京师大学报（自然科学版）》[ISSN:1001-4616/CN:32-1239/N]

Issue:
2020年01期
Page:
31-39
Research Field:
·物理学·
Publishing date:

Info

Title:
WirelessTomographyPositioningMethodBasedonKPCA
Author(s):
LuJun1; KeWei1; 2; JinJie1; ChenMengling1; WangYanli1; ZuoHaoran1
(1.JiangsuKeyLaboratoryonOpto-electronicTechnology,SchoolofPhysicsScienceandTechnology,NanjingNormalUniversity,Nanjing210023,China)(2.JiangsuCenterforCollaborativeInnovationinGeographicalInformationResourceDevelopmentandApplication,Nanjing210023,China)
Keywords:
radiotomographyimaging; device-freelocalization; receivedsignalstrength; kernelprincipalcomponentanalysis
PACS:
O451
DOI:
10.3969/j.issn.1001-4616.2020.01.006
Abstract:
RadioTomographyImaging(RTI)technologyisoneofthemainmethodsofdevice-freelocalization(DFL).Itcanstillachievepositioningwithoutbeingpositionedwithanypositioningdevice,andwithawiderangeofapplicationprospects.However,sincetheReceivedSignalStrength(RSS)informationiseasilyaffectedbyenvironmentalchangesandnoise,backgroundnoiseisinevitablypresentontheRTIimage,andsometimesevenpseudotargetsappearontheimage.InordertoimprovethequalityofRTI,thispaperproposesanenhancedRTImethodbasedonKernelPrincipalComponentAnalysis(KPCA),whichusesthelearningabilityofKPCAtoextractthelinkcharacteristicinformationthatiseffectivelyaffectedbythetarget,inordertoovercometheeffectsofnoiseandimprovepositioningaccuracy.TheresultsofindoorandoutdoorexperimentsshowthattheimagingqualityandpositioningaccuracyofthismethodarebetterthantheexistingRTImethod.

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Last Update: 2020-03-15