In this paper the problem of the joint statistical characterization of the NLOS bias and of the most representative features of LOS/NLOS UWB waveforms is investigated. In addition, the performance of various maximum-likelihood (ML) estimators for joint localization and NLOS bias mitigation is assessed. Our numerical results evidence that: a) the accuracy of all the considered estimators is appreciably affected by the LOS/NLOS conditions of the propagation environment; b) a statistical knowledge of multiple signal features can be exploited to mitigate the NLOS bias, so reducing the overall localization error.
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