The Global Positioning System (GPS) has become one of the state-of-the-art location systems that offers reliable mobile terminal\r\n(MT) location estimates. However, there exist situations where GPS is not available, for example, when the MT is used indoors\r\nor when the MT is located close to high buildings. In these scenarios, a promising approach is to combine the GPS-measured\r\nvalues with measured values from the Global System for Mobile Communication (GSM), which is known as hybrid localization\r\nmethod. In this paper, three nonlinear filters, namely, an extended Kalman filter, a Rao-Blackwellized unscented Kalman filter,\r\nand a modified version of the recently proposed cubature Kalman filter, are proposed that combine pseudoranges from GPS with\r\ntiming advance and received signal strengths from GSM. The three filters are compared with each other in terms of performance\r\nand computational complexity. Posterior Cram�´er-Rao lower bounds are evaluated in order to assess the theoretical performance.\r\nFurthermore, it is investigated how additional GPS reference time information available from GSM influences the performance\r\nof the hybrid localization method. Simulation and experimental results show that the proposed hybrid method outperforms the\r\nGSM method.
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