Improved RSSI based Vehicle Localization using Base Station

Abstract

The physical position of the vehicles is vital information for the tracking operation. The vehicles localization have several benefits and support for safety, comfort, and reliability in future transportation systems. Thus the vehicular localization has investigated, where the base station (BS) will track the target vehicles. This paper mainly addresses a new localization scenario on distributing the coverage area based on the received signal strength indicator (RSSI). The RSSI measured in regular operation and consume minimum energy. However, wireless RSSI suffers from various interference in dynamic environments. For solving these issues, several methods have been proposed in the literature, including the signal intensity attenuation model (SIAM). This paper incorporates the fact that the motion of vehicles satisfies environmental constraints to improve the accuracy of RSSI-based localization by a new model, namely the gaussian signal attenuation model (GSAM) using most likely RSSIs. Numerical results demonstrate that the proposed method considerably outperforms the existing methods in terms of dynamic positioning accuracy.