Indoor location tracking using inertial navigation sensors and radio beacons

  • Authors:

  • Pedro Coronel;Simeon Furrer;Wolfgang Schott;Beat Weiss

  • Affiliations:

  • Communication Technology Laboratory, Swiss Federal Institute of Technology (ETH), Zurich, Switzerland and IBM Research GmbH, Zurich Research Laboratory, Zurich, Switzerland;Broadcom Corporation, Sunnyvale, CA and IBM Research GmbH, Zurich Research Laboratory, Zurich, Switzerland;IBM Research GmbH, Zurich Research Laboratory, Zurich, Switzerland;IBM Research GmbH, Zurich Research Laboratory, Zurich, Switzerland

  • Venue:
  • IOT'08 Proceedings of the 1st international conference on The internet of things
  • Year:
  • 2008

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Abstract

We consider the problem of real-time sensing and tracking the location of a moving cart in an indoor environment. To this end, we propose to combine position information obtained from an inertial navigation system (INS) and a short-range wireless reference system that can be embedded into a future "network of things". The data produced by the INS lead to accurate short-term position estimates, but due to the drifts inherent to the system, these estimates perform loosely after some time. To solve this problem, we also generate estimates with a wireless reference system. These radio-based estimates can be used as accurate long-term position estimates because their accuracy improves over time as the channel fading can be averaged out. We use a data fusion algorithm based on Kalman filtering with forward/backward smoothing to optimally combine the short- and long-term position estimates. We have implemented this localization system in a real-time testbed. The measurement results, which we obtained using the proposed method, show considerable improvements in accuracy of the location estimates.