No abstract

No abstract

This letter deals with a hybrid time-of-arrival/angle-of-arrival (TOA/AOA) approximate maximum likelihood (AML) wireless location algorithm. Thanks to the use of both TOA/AOA measurements, the proposed technique can rely on two base stations (BS) only and achieves better performance compared to the original approximate maximum likelihood (AML) method. The use of two BSs is an important advantage in wireless cellular communication systems because it avoids hearability problems and reduces network signaling burden. Simulation results show that, for certain scenarios, the proposed hybrid TOA/AOA AML with two BSs can outperform the AML with up to six BSs.

No 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.