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

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


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


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.


  • 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

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