An efficient constrained weighted least squares method with bias reduction for TDOA-based localization

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dc.contributor.authorZhang, Liang
dc.contributor.authorZhang, Tao
dc.contributor.authorShin, Hyo-Sang
dc.date.accessioned2021-03-31T11:17:06Z
dc.date.available2021-03-31T11:17:06Z
dc.date.issued2021-02-05
dc.description.abstractThis paper addresses the source location problem by using time-difference-of-arrival (TDOA) measurements. The two-stage weighted least squares (TWLS) algorithm has been widely used in the TDOA location. However, the estimation accuracy of the source location is poor and the bias is significant when the measurement noise is large. Owing to the nonlinear nature of the system model, we reformulate the localization problem as a constrained weighted least squares problem and derive the theoretical bias of the source location estimate from the maximum-likelihood (ML) estimation. To reduce the location bias and improve location accuracy, a novel bias-reduced method is developed based on an iterative constrained weighted least squares algorithm. The new method imposes a set of linear equality constraints instead of the quadratic constraints to suppress the bias. Numerical simulations demonstrate the significant performance improvement of the proposed method over the traditional methods. The bias is reduced significantly and the Cramér–Rao lower bound accuracy can also be achieveden_UK
dc.identifier.citationZhang L, Zhang T, Shin H-S. (2021) An efficient constrained weighted least squares method with bias reduction for TDOA-based localization. IEEE Sensors Journal, Volume 21, Issue 8, April 2021, pp. 10122-10131en_UK
dc.identifier.issn1530-437X
dc.identifier.urihttps://doi.org/10.1109/JSEN.2021.3057448
dc.identifier.urihttps://dspace.lib.cranfield.ac.uk/handle/1826/16527
dc.language.isoenen_UK
dc.publisherIEEEen_UK
dc.rightsAttribution-NonCommercial 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/*
dc.subjectmaximum-likelihood estimationen_UK
dc.subjectweighted least squaresen_UK
dc.subjectBias reductionen_UK
dc.subjectTDOAen_UK
dc.titleAn efficient constrained weighted least squares method with bias reduction for TDOA-based localizationen_UK
dc.typeArticleen_UK

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