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dc.contributor.advisorTitus, Harold A.
dc.contributor.authorTaskin, Dogan
dc.date1990-09
dc.date.accessioned2013-08-01T21:15:55Z
dc.date.available2013-08-01T21:15:55Z
dc.date.issued1990-09
dc.identifier.urihttp://hdl.handle.net/10945/34944
dc.description.abstractThe Kalman filter is used to provide estimates of the position and velocity of a storm based upon observation of the storm's longitude and latitude. Nonstationary noise is shown to degrade the performance of the filter and cause tracking divergence. Time varying values for the noise covariance matricies R and Q, and the addition of an external forcing function to the filter, effectively compensated for this tracking error. Results for the simulations show significant performance advantages of using an external forcing function in the system.en_US
dc.description.urihttp://archive.org/details/thepathpredictio1094534944
dc.format.extentvi, 73 p.en_US
dc.languageen_US
dc.publisherMonterey, California: Naval Postgraduate Schoolen_US
dc.rightsCopyright is reserved by the copryright owner.en_US
dc.subject.lcshElectrical engineeringen_US
dc.subject.lcshCyclonesen_US
dc.subject.lcshLatitudeen_US
dc.subject.lcshLongitudeen_US
dc.subject.lcshStormsen_US
dc.subject.lcshWeather forecastingen_US
dc.subject.lcshTropics.en_US
dc.titleThe path prediction of cyclones with Kalman filtersen_US
dc.typeThesisen_US
dc.contributor.secondreaderBurl, Jeffrey B.
dc.contributor.corporateNaval Postgraduate School (U.S.)
dc.contributor.departmentElectrical and Computer Engineering
dc.subject.authorKalman Filteren_US
dc.subject.authorpath prediction of cyclonesen_US
dc.subject.authorTurkeyen_US
dc.description.serviceLieutenant Junior Grade, Turkish Navyen_US
etd.thesisdegree.nameM.S. in Electrical Engineeringen_US
etd.thesisdegree.levelMastersen_US
etd.thesisdegree.disciplineElectrical Engineeringen_US
etd.thesisdegree.grantorNaval Postgraduate Schoolen_US
dc.description.distributionstatementApproved for public release; distribution is unlimited.


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