dc.contributor.authorNi Yun
dc.date.accessioned2016-05-27T03:57:21Z
dc.date.available2016-05-27T03:57:21Z
dc.date.issued2016
dc.identifier.urihttp://hdl.handle.net/10356/68576
dc.description.abstractRadio tomographic imaging (RTI) is a device-free target localization algorithm that has been developed recently. It uses received signal strength changes of links in a wireless sensor network as the input to identify the target location at a specific time. We can localize the target without attaching a device to it. Compared with other device-free localization methods, RTI is relatively low cost. The objective of this project is to 1) implement radio tomographic imaging algorithms on simulated data and 2) apply a recursive Bayesian filter to infer target trajectories over time. Specifically, we have implemented the Kalman and particle filter. It is shown with computer simulations that both types are able to improve the accuracy of target trajectory estimates.en_US
dc.format.extent68 p.en_US
dc.language.isoenen_US
dc.subjectDRNTU::Engineering::Electrical and electronic engineeringen_US
dc.titleDevice-free target trackingen_US
dc.typeThesis
dc.contributor.supervisorFrancois Quitinen_US
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen_US
dc.description.degreeMaster of Science (Signal Processing)en_US


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