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dc.contributor.advisorGarren, David A.
dc.contributor.advisorScrofani, James W.
dc.contributor.authorCarnes, Joseph L.
dc.dateJun-15
dc.date.accessioned2015-08-05T23:05:22Z
dc.date.available2015-08-05T23:05:22Z
dc.date.issued2015-06
dc.identifier.urihttp://hdl.handle.net/10945/45822
dc.descriptionApproved for public release; distribution is unlimiteden_US
dc.description.abstractA methodology for automatically detecting a swarm attack in the maritime domain is examined in this thesis. These techniques are based upon feeding data into the Kalman filtering algorithm, which is used in the tracking of moving targets based on simulated radar position measurements. Specifically, the expectation of a location of a given moving vessel based upon the Kalman filtering estimates is used to determine if a strong maneuver is occurring. When a given moving target’s motion lies outside of the estimated location zone, additional time is required for the estimated track to synchronize the track with the current measurements for this particular moving target. The proposed use of this algorithm is to provide an ability to monitor the maritime traffic within a given area of regard in order to determine if a high-speed maneuvering surface target swarm attack is occurring. The software for this thesis involved the development and testing of object-oriented source code in MATLAB. This work included the development of an algorithm that monitors all traffic and generates a signal spike when a threat has been initiated. A notional gun system was included in order to permit the calculation of survivability estimates when placed inside a larger Monte Carlo simulation.en_US
dc.description.urihttp://archive.org/details/determinationofh1094545822
dc.publisherMonterey, California: Naval Postgraduate Schoolen_US
dc.rightsCopyright is reserved by the copyright owner.en_US
dc.titleDetermination of high-speed multiple threat using Kalman filter analysis of maritime movementen_US
dc.typeThesisen_US
dc.contributor.secondreaderPilnick, Steven E.
dc.contributor.departmentElectrical and Computer Engineering
dc.contributor.departmentElectrical and Computer Engineeringen_US
dc.subject.authorKalman filteren_US
dc.subject.authormaritimeen_US
dc.subject.authorswarm threaten_US
dc.subject.authorHSMSTen_US
etd.thesisdegree.nameMaster of Science in Electrical Engineeringen_US
etd.thesisdegree.levelMastersen_US
etd.thesisdegree.disciplineElectrical Engineeringen_US
etd.thesisdegree.grantorNaval Postgraduate Schoolen_US


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