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A NLOS-robust TOA positioning filter based on a skew-t measurement noise model | IEEE Conference Publication | IEEE Xplore

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


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...Show More

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.
Date of Conference: 13-16 October 2015
Date Added to IEEE Xplore: 07 December 2015
ISBN Information:
Conference Location: Banff, AB, Canada

References

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