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A NLOS-robust TOA positioning filter based on a skew-t measurement noise model

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Details

Original languageEnglish
Title of host publication2015 International Conference on Indoor Positioning and Indoor Navigation (IPIN)
PublisherIEEE
Pages1-7
Number of pages7
ISBN (Print)978-1-4673-8402-5
DOIs
Publication statusPublished - 1 Oct 2015
Publication typeA4 Article in a conference publication
EventInternational Conference on Indoor Positioning and Indoor Navigation -
Duration: 1 Jan 1900 → …

Conference

ConferenceInternational Conference on Indoor Positioning and Indoor Navigation
Period1/01/00 → …

Abstract

A skew-t variational Bayes filter (STVBF) is applied to indoor positioning with time-of-arrival (TOA) based distance measurements and pedestrian dead reckoning (PDR). The proposed filter accommodates large positive outliers caused by occasional non-line-of-sight (NLOS) conditions by using a skew-t model of measurement errors. Real-data tests using the fusion of inertial sensors based PDR and ultra-wideband based TOA ranging show that the STVBF clearly outperforms the extended Kalman filter (EKF) in positioning accuracy with the computational complexity about three times that of the EKF.

Keywords

  • Approximation methods, Computational modeling, Distance measurement, Gaussian distribution, Measurement errors, Noise measurement, Position measurement, NLOS, TOA, UWB, indoor positioning, robust filtering, skew t, skewness, variational Bayes

Publication forum classification

Field of science, Statistics Finland

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