Nonlinear Filtering for Hybrid GPS/GSM Mobile Terminal Tracking

Carsten Fritsche,Anja Klein

doi:10.1155/2010/149065

Abstract

The Global Positioning System (GPS) has become one of the state-of-the-art location systems that offers reliable mobile terminal (MT) location estimates. However, there exist situations where GPS is not available, for example, when the MT is used indoors or when the MT is located close to high buildings. In these scenarios, a promising approach is to combine the GPS-measured values with measured values from the Global System for Mobile Communication (GSM), which is known as hybrid localization method. In this paper, three nonlinear filters, namely, an extended Kalman filter, a Rao-Blackwellized unscented Kalman filter, and a modified version of the recently proposed cubature Kalman filter, are proposed that combine pseudoranges from GPS with timing advance and received signal strengths from GSM. The three filters are compared with each other in terms of performance and computational complexity. Posterior Cramér-Rao lower bounds are evaluated in order to assess the theoretical performance. Furthermore, it is investigated how additional GPS reference time information available from GSM influences the performance of the hybrid localization method. Simulation and experimental results show that the proposed hybrid method outperforms the GSM method.

Highlights

In the past few years, there is an increased interest in wireless location systems offering reliable mobile terminal (MT) location estimates
In [12, 13], we have developed an extended Kalman filter- (EKF-) based and Rao-Blackwellized unscented Kalman filter- (RBUKF) based MT tracking algorithm that fuses timing advance (TA)- and RSSmeasured values from Global System for Mobile Communication (GSM)- and PR-measured values from Global Positioning System (GPS)
In the first simulation scenario (Scenario I), it is assumed that a car is equipped with an MT that is capable of providing PR-measured values from GPS and TA, received signal strength (RSS), and GPS reference time uncertainty-measured values from GSM

Summary

Introduction

In the past few years, there is an increased interest in wireless location systems offering reliable mobile terminal (MT) location estimates. One first collects at every time step k all the measurements from GPS and GSM and these measurements are processed jointly in the filter in order to estimate the MT location With this strategy, it is possible to obtain MT location estimates even if less than three satellites are visible to the MT. Three different suboptimal algorithms, namely, the extended Kalman filter, the Rao-Blackwellized unscented Kalman filter, and the modified cubature Kalman filter, are proposed in order to solve the underlying hybrid localization problem. These filters belong to the class of approaches where all densities in ((2), (3), and (4)) are assumed to be Gaussian. An appealing advantage of this approximation is that the functional recursion in ((2), (3), and (4)) reduces to an algebraic recursion, where only means and covariances have to be calculated

Methods

Results

Conclusion