Mobile Localization Under Non-Line-of-Sight Conditions Using Scattering Information

Abstract

A novel mobile localization algorithm under non-line-of-sight (NLoS) conditions involving at most two base stations (BS) is presented. By using such a small number of BSs, the proposed technique avoids problems related to weak mobile hearability and excessive network messaging overload. Based on a scattering model, the NLoS hybrid approximate maximum likelihood (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 a known scatterers' distribution in a maximum likelihood (ML) sense. Numerical results prove that the proposed algorithm outperforms previous methods by providing an accuracy enhancement that reaches 60%. It is also shown that the performance enhancement provided by the proposed algorithm is maximized when the adequate scatterers distribution is adopted.

Single base station positioning based on multipath parameter clustering in NLOS environment

“…However, this scheme requires 360°omnidirectional sampling of the environment near the BS. Therefore, the scattering model is often introduced in the single BS positioning system in the NLOS environment for analysis [21]. Common scattering models include the Ring of Scattering (ROS), Disk of Scattering (DOS), and Gaussian Scattering Density Model (GSDM) [22,23].…”

Single Base Station Positioning based on Multipath Parameter Clustering in NLOS Environment

“…However, this scheme requires 360 • omni-directional sampling of the environment near the base station. Therefore, the scatterer model is often introduced in the single base station localization system in the NLOS environment for analysis [21]. Common scatterer models include the Ring of Scattering (ROS), Disk of Scattering (DOS) and Gaussian Scattering Density Model (GSDM) [22,23].…”