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In wireless positioning systems, non-line-of-sight (NLOS) is a challengingproblem. NLOS causes great ranging bias and location error, so NLOS mitigationis essential for high accuracy positioning. In this letter, we propose theWeighted-Least-Squares Robust Kalman Filter (WLS-RKF) for NLOS identificationand mitigation. WLS-RKF employs a hypothesis test based on Mahalanobis distancefor NLOS identification, and updates the corresponding Kalman filter using theWLS solution. It requires no prior knowledge about NLOS distribution or signalfeatures. We perform simulations and experiments for ultra-wideband (UWB)positioning in various scenarios. The results confirm that WLS-RKF effectivelymitigates NLOS error and achieves 5cm positioning accuracy.

NLOS Error Mitigation Using Weighted Least Squares and Kalman Filter in UWB Positioning