Integrated Algorithms for RFID-based multi-sensor indoor/outdoor positioning solutions

Position information is very important as people need it almost everywhere all the time. However, it is a challenging task to provide precise positions indoor/outdoor seamlessly. Outdoor positioning has been widely studied and accurate positions can usually be achieved by well developed GPS techniques but these techniques are difficult to be used indoors since GPS signal reception is limited. The alternative techniques that can be used for indoor positioning include, to name a few, Wireless Local Area Network (WLAN), bluetooth and Ultra Wideband (UWB) etc.. However, all of these have limitations. The main objectives of this paper are to investigate and develop algorithms for a low-cost and portable indoor personal positioning system using Radio Frequency Identification (RFID) and its integration with other positioning systems. An RFID system consists of three components, namely a control unit, an interrogator and a transponder that transmits data and communicates with the reader. An RFID tag can be incorporated into a product, animal or person for the purpose of identification and tracking using radio waves. In general, for RFID positioning in urban and indoor environments three different methods can be used, including cellular positioning, trilateration and location fingerprinting. In addition, the integration of RFID with other technologies is also discussed in this paper. A typical combination is to integrate RFID with relative positioning technologies such as MEMS INS to bridge the gaps between RFID tags for continuous positioning applications. Experiments are shown to demonstrate the improvements of integrating multiple sensors with RFID which can be employed successfully for personal positioning.