Bootstrapping M-estimators for reducing errors due to non-line-of-sight (NLOS) propagation

Mobile positioning is made difficult by nonsymmetric contamination of measured time-of-arrival (TOA) data caused by non-line-of-sight (NLOS) propagation. In this letter, a robust NLOS error mitigation algorithm based on Bootstrapping M-estimation is proposed without prior NLOS error distribution. A simulation comparison is performed in different channel environments between the proposed algorithm and two additional ones (least-square and Huber estimator). The proposed algorithm clearly outperforms the other two.

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