  Propagation in non-line-of-sight (NLOS) conditions is one of the major
impairments in ultrawideband (UWB) wireless localization systems based on
time-of-arrival (TOA) measurements. 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 the accuracy of all the considered estimators is appreciably
influenced by the LOS/NLOS conditions of the propagation environment and that a
statistical knowledge of multiple signal features can be exploited to mitigate
the NLOS bias, reducing the overall localization error.
