Combining RSS-based trilateration methods with radio-tomographic imaging: Exploring the capabilities of long-range RFID systems

Several approaches have been proposed for the localization of persons at their homes in assisted living applications. Most of these systems are beacon-based solutions which trilaterate with RSS signals captured by a user-attached device (the LPS approach); a technique which can be enhanced by information obtained by inertial sensor carried by the user. A completely different approach uses the concept of radio tomographic imaging (RTI) to infer the user´s position without requiring him to carry any device (the Device Free Localization or DFL approach). This paper explores how both approaches (LPS and DFL) can be combined to provide a localization solution that integrates the advantages of both methods. The sensors employed in this study use long-range active RFID technology at 433 MHz carrier frequency. An important challenge is achieving enough position accuracy with a relatively low number of RFID readers in an apartment-size area. The large wavelength (0.6 m), low measurement rate (1 Hz) and low signal to noise ratio are other challenges that our localization system has to cope with. We analyse the RSS readings of the RFID equipment and extract measurement models useful for DFL- and LPS-based localization. We also combine both approaches (DFL + LPS) in order to achieve an accurate enough localization (positioning error below 1 meter for 90% of the cases). The fusion of these estimation techniques is implemented with a particle filter which combines measurements from two sources: the tag-to-reader RSS-based ranges and the RSS-link differences with respect to an empty room reference RTI-image.