A NLOS-robust TOA positioning filter based on a skew-t measurement noise model
Nurminen, Henri; Ardeshiri, Tohid; Piche, Robert; Gustafsson, Fredrik (2015-10-01)
Julkaisun pysyvä osoite on
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.
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