Hybrid Location Estimation and Tracking System for Mobile Devices

Abstract

Mobile location estimation has attracted lots of attention in recent years. The location algorithms for the mobile devices can generally be categorized into the network-based and the satellite-based systems. Both types of system have their advantages and limitations under different environments (i.e. urban, suburban, or rural area). In order to provide adaptation to various scenarios for location estimation, a hybrid location scheme, which combines both the satellite-based and the network-based signals, is proposed in this paper. The proposed scheme utilizes the two-step least square method for estimating the three-dimensional position (i.e. the longitude, latitude, and altitude) of the mobile devices. The Kalman filtering technique is exploited to both eliminate the measurement noises and to track the trajectories of the mobile devices. A fusion algorithm is employed to obtain the final location estimation from both the satellite-based and the network-based systems. Numerical results demonstrate that the proposed hybrid location scheme provides accurate location estimation by adapting itself under different environments.