Abstract

We present a methodology to accurately locate persons indoors by fusing Inertial Navigation (INS) techniques with active RFID technology. A foot-mounted IMU aided by the Received Signal Strengths (RSS) obtained from several active RFID tags, placed at known locations in a building, has been used. Other authors have already integrated IMUs with RFID tags in loosely-coupled Kalman Filter (KF) solutions [1], [2], [3]. They feed the KF with the residuals of inertial- and RFID-calculated positions; these approaches do not exploit the benefits of Zero Velocity Updates (ZUPT). In this paper, we present a tight KF-based INS/RFID integration using the residual between the INS-predicted range-to-tag, and the range derived from a generic RSS path-loss model. Our approach also includes ZUPTs at detected foot stances, ZARU (Zero Angular-rate Update) estimation at still phases, and heading drift reduction using magnetometers. A 15-element error state Extended KF [4], [7] compensates position, velocity and attitude errors of the INS solution, as well as IMU biases. This methodology is valid for any kind of motion (forward, lateral or backwards walk, at different speeds) and does not require an specific off-line calibration, neither for the user gait, nor for the location-dependent RSS fading in the building. The integrated INS+RFID methodology eliminates the typical drift of IMU-alone solutions (approximately 1% of the total travelled distance), accounting for typical positioning errors along the walking path (no matter its length) of approximately 1.5 meters.

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