dc.contributor.authorYan, Yongsheng
dc.contributor.authorWang, Haiyan
dc.contributor.authorShen, Xiaohong
dc.contributor.authorHe, Ke
dc.contributor.authorZhong, Xionghu
dc.date.accessioned2015-12-14T02:05:38Z
dc.date.available2015-12-14T02:05:38Z
dc.date.issued2015
dc.identifier.citationYan, Y., Wang, H., Shen, X., He, K., & Zhong, X. (2015). TDOA-Based Source Collaborative Localization via Semidefinite Relaxation in Sensor Networks. International Journal of Distributed Sensor Networks, 2015, 248970-.en_US
dc.identifier.issn1550-1329en_US
dc.identifier.urihttp://hdl.handle.net/10220/39067
dc.description.abstractThe time delay of arrival- (TDOA-) based source localization using a wireless sensor network has been considered in this paper. The maximum likelihood estimate (MLE) is formulated by taking the correlated TDOA noise into account, which is caused by the difference with the TOA of the reference sensor. The global optimal solution is difficult to obtain due to the nonconvex nature of the ML function. We propose an alternative semidefinite programming method, which transforms the original ML problem into a convex one by relaxing nonconvex equalities into convex matrix inequalities. In addition, the source localization algorithm in the presence of sensor location errors and non-line-of-sight (NLOS) observations is developed. Our simulation results demonstrate the potential advantages of the proposed method. Furthermore, the proposed source localization algorithm by taking the NLOS TOA measurements as the constraints of the convex problem can provide a good estimate.en_US
dc.format.extent16 p.en_US
dc.language.isoenen_US
dc.relation.ispartofseriesInternational Journal of Distributed Sensor Networksen_US
dc.rights© 2015 Yongsheng Yan et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.en_US
dc.titleTDOA-Based Source Collaborative Localization via Semidefinite Relaxation in Sensor Networksen_US
dc.typeJournal Article
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen_US
dc.identifier.doihttp://dx.doi.org/10.1155/2015/248970
dc.description.versionPublished versionen_US


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