Advanced mobile positioning techniques using spatial and temporal cooperation

• Main Author: He, Ziming
• Published: University of Surrey 2012
• Subjects: 526.0285
• Online Access: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.580344

In the last decade, wireless network assisted positioning techniques have attracted great interests. Mobile terminals (MTs) are equipped with positioning function through employment of Global Navigation Satellite System, radio communication networks, and integrated inertial sensors. Moreover, MTs can cooperate with each other by means of either centralized data fusion or distributed data fusion. Such cooperative behaviors are referred to as the spatial cooperation, which were originally developed for wireless sensor networks. However, state-of-the-art spatial cooperation approaches were specially designed for short-range networks, and they are not suitable for applications in cellular networks. The other problem is that the spatial cooperation requires distance estimation between many MTs, which will cause significant training overhead. These research issues motivated the following major contributions: • A novel spatial cooperative positioning algorithm, namely the base station to MT angle searching, was proposed in cellular networks. The proposed algorithm was based on centralized data fusion, and it outperforms state-of-the-art approaches by at least 4 m improvement in positioning accuracy. • The Cramer-Rao lower bound (CRLB) was employed to study the relationship between the positioning accuracy and training overhead. It was found that the CRLB is minimized when 2 out of all involved MTs send training signals for the purpose of distance estimation. Moreover, we have investigated the impact of inertial sensors on mobile positioning, which allows for an MT to cooperate with itself over time. This is referred to as the temporal cooperation. Our major contribution is: • Derived a new CRLB for the inertial sensors enhanced radio positioning with the knowledge of random walk mobility model. Interestingly, it was found that the knowledge of mobility model is not needed when inertial sensor measurements are sufficiently accurate. In addition, we have developed a number of novel distance-estimation algorithms that can offer highly accurate time-of-arrival estimation using orthogonal frequency-division multiplexing (OFDM) waveforms in wireless local area networks (WLANs). These techniques are key enablers to radio positioning, which have been successfully implemented in the CCSR test-bed (WARP FPGA board).