Performance analysis of data fusion for ground target tracking using GSM networks

The Global System for Mobile Communications (GSM) networks can provide position information. However, a GSM positioning system based on current specifications faces many difficulties to yield accurate position estimate for ground target tracking. Data fusion solutions which integrate two or more types of measurements have been proposed to provide estimation with better accuracy, reliability and coverage. The performance of Mobile Station (MS) positioning has been broadly discussed, but the performance analysis of ground target tracking, i.e., dynamic position estimation, is rare. This paper focuses on the performance analysis for a data fusion approach of integrating two different types of measurements from GSM networks using posterior Cramér-Rao lower bound (PCRLB). The simulation results verify that the data fusion approach greatly improves the estimation accuracy and is more robust to noisy measurements as compared to the approaches using single kind of measurements.