Indoors Smartphone Positioning Enhancement Using Wi-Fi and Magnetometer

Authors

  • Runahi F. Qadir Department of software Engineering, College of Engineering, Koya University, Koya, Erbil, Kurdistan Region, Iraq
  • Halgurd S. Maghdid Department of Software Engineering, College of Engineering, Koya University,Koya, Erbil, Kurdistan Region, Iraq
  • Azhin T. sabir Department of Software Engineering, College of Engineering, Koya University,Koya, Erbil, Kurdistan Region, Iraq

Abstract

When smartphone holders are entering to the urbane area or indoors, the performance of GPS service will
be degraded or sometime cannot retrieve location information due to blocking the GPS signals through the
roofs or walls of the buildings. Beside this, many onboard smartphones wireless chipsets or sensors’
readings can be used as alternate technologies to provide location information including Wi-Fi, Bluetooth,
cellular, and inertial sensors. However, these technologies during positioning process will faced its own
limitations such as: none-line-of-sight signals, multipath signals, and sensor drift or accumulated error. For
these reasons, it is very difficult to provide a good positioning accuracy, when only a single technology is
utilized alone. The aforementioned limitation of positioning technologies motivated us to propose a new
positioning solution based on hybridize two different technologies measurements including received signal
strength (RSS) of the Wi-Fi access points and onboard smartphone magnetometer readings within
fingerprinting positioning technique. The hybridization of these technologies is based on taking their
advantaged and mitigating their drawbacks. In addition to that, this study also provided an improved
version of matching algorithm of the fingerprinting technique by applying the concept of boosting-dataset
records. A set of real trial experiments are conducted to prove the validity of the proposed solution. The
obtained results of the experiments show that the proposed positioning solution can provide an enough
positioning accuracy, up to 0.13 meter.

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Published

2023-09-20