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Multitarget Tracking Using Multistatic Sensors

dc.contributor.advisorKirubarajan, T.en_US
dc.contributor.advisorI. Bruce, S. Sirouspouren_US
dc.contributor.authorSUBRAMANIAM, MAHESWARANen_US
dc.contributor.departmentElectrical and Computer Engineeringen_US
dc.date.accessioned2014-06-18T17:00:17Z
dc.date.available2014-06-18T17:00:17Z
dc.date.created2012-09-26en_US
dc.date.issued2012-10en_US
dc.description.abstract<p>In this thesis the problem of multitarget tracking in multistatic sensor networks is studied. This thesis focuses on tracking airborne targets by utilizing transmitters of opportunity in the surveillance region. Passive Coherent Location (PCL) system, which uses existing commercial signals (e.g., FM broadcast, digital TV) as the illuminators of opportunity for target tracking, is an emerging technology in air defence systems. PCL systems have many advantages over conventional radar systems such as low cost, covert operation and low vulnerability to electronic counter measures.</p> <p>One of another opportunistic signals available in the surveillance region is multipath signal. In this thesis, the multipath target return signals from distinct propagation modes that are resolvable by the receiver are exploited. When resolved multipath returns are not utilized within the tracker, i.e., discarded as clutter, potential information conveyed by the multipath detections of the same target is wasted. In this case, spurious tracks are formed using target-originated multipath measurements, but with an incorrect propagation mode assumption. Integrating multipath information into the tracker (and not discarding it) can help improve the accuracy of tracking and reduce the number of false tracks.</p> <p>In this thesis, these opportunistic measurements, i.e., commercial broadcast signals measurements in PCL tracking and resolvable multipath target return measurements in multipath assisted tracking are exploited. We give the optimal formulations for all of the above problems as well as the performance evaluations using PCRLB. Simulation results illustrate the performance of the algorithms.</p>en_US
dc.description.degreeDoctor of Philosophy (PhD)en_US
dc.identifier.otheropendissertations/7513en_US
dc.identifier.other8571en_US
dc.identifier.other3351652en_US
dc.identifier.urihttp://hdl.handle.net/11375/12645
dc.subjecttarget trackingen_US
dc.subjectmultipathen_US
dc.subjectdata associationen_US
dc.subjectmultiframe assignmenten_US
dc.subjectmultipath PCRLBen_US
dc.subjectpassive coherent locationen_US
dc.subjectbias removalen_US
dc.subjecttransmitters of opportunityen_US
dc.subjectmultipath trackingen_US
dc.subjectApplied Statisticsen_US
dc.subjectMulti-Vehicle Systems and Air Traffic Controlen_US
dc.subjectNavigation, Guidance, Control and Dynamicsen_US
dc.subjectProbabilityen_US
dc.subjectSignal Processingen_US
dc.subjectSystems and Communicationsen_US
dc.subjectApplied Statisticsen_US
dc.titleMultitarget Tracking Using Multistatic Sensorsen_US
dc.typethesisen_US

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