Robust Bias Mitigation for Localization in Wireless Networks

dc.contributor.advisorJabbari, Bijan
dc.contributor.authorBhagwat, Nikhil
dc.creatorBhagwat, Nikhil
dc.date2010-04-30
dc.date.accessioned2010-05-20T14:09:41Z
dc.date.availableNO_RESTRICTION
dc.date.available2010-05-20T14:09:41Z
dc.date.issued2010-05-20T14:09:41Z
dc.description.abstractLocalization of a wireless device or a sensor node has been a problem of great importance in recent years. Location services are becoming an essential part of the traditional wireless networks as well as the wireless sensor networks. Indoor localization in particular has been an issue of interest in recent studies since GPS is not suitable for indoor environments. The main issue in target node location estimation is the distance estimates affected by the non-line-of-sight (NLOS) signal measurements. In any practical setting, the NLOS errors are inevitable and need to be mitigated in order to achieve acceptable accuracy. In this work, first a theoretical analysis of effect of bias on the localization accuracy is performed. Then, a novel technique is presented which reduces the adverse effects of bias by utilizing the topological diversity provided by the unique beacon combinations from the power set of N(>3) beacons. The proposed approach consists of two complementary weighted average methods combined to provide a high level of robustness. The simulation and empirical results show that the presented technique is effective independent of the bias distribution. Thus it can be implemented on top of variety of existing localization methods in wireless networks to mitigate the adverse effects of NLOS propagation and achieve high accuracy in a practical scenario.
dc.identifier.urihttps://hdl.handle.net/1920/5829
dc.language.isoen_US
dc.subjectLocalization
dc.subjectWireless networks
dc.subjectNon-line-of -sight
dc.subjectBias mitigation
dc.subjectLocation services
dc.titleRobust Bias Mitigation for Localization in Wireless Networks
dc.typeThesis
thesis.degree.disciplineElectrical Engineering
thesis.degree.grantorGeorge Mason University
thesis.degree.levelMaster's
thesis.degree.nameMaster of Science Electrical Engineering

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