Mobile positioning in a Gaussian scattering channel model

This paper presents a novel mobile localization algorithm under non-line-of-sight (NLoS) conditions in a Gaussian scattering channel model involving two base stations (BS) at most. By using such a small number of BSs, the proposed technique avoids problems relative to weak mobile hearability, network overload and linear BSs layout. Based on the known scattering distribution, the Gaussian NLoS hybrid approximate maximum likelihood (G-NLoS HAML) approach presented herein estimates the distances between the mobile station (MS) and the scatterers through the measured hybrid time-of-arrival/angle-of-arrival (ToA/AoA) statistics. Then, it matches the calculated distances to the Gaussian scatterers´ distribution in a maximum likelihood (ML) sense. Numerical results prove that the proposed algorithm gives better performance compared to previous approaches.