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Localization in Inconsistent WiFi Environments

  • Hsin-Min Cheng
  • Dezhen SongEmail author
Conference paper
Part of the Springer Proceedings in Advanced Robotics book series (SPAR, volume 10)

Abstract

As WiFi becomes more and more popular, indoor environments are often covered with access points (APs) many of which are temporarily generated by mobile devices. On the other hand, more and more infrastructural APs are equipped with beamforming capabilities which adjust radiation patterns according to client locations. These APs have large variations of signal fields. The inconsistent WiFi environments present a challenge for localization tasks when the client cannot communicate with APs. Here we report a new algorithm targeted at handling inconsistent APs. We develop a windowed majority voting and statistical hypothesis testing-based approach to remove APs with large displacements between reference and query data sets. We then refine the localization by applying maximum likelihood estimation method to the closed-form posterior location distribution over the filtered signal strength and AP sets in the time window. We determine the time window length by minimizing Shannon entropy of the posterior location distribution. We have implemented our algorithm and our method outperforms its counterparts in physical experiments. Our method achieves a mean localization error of less than 3.7 meters even when \(70\%\) of APs are inconsistent.

Notes

Acknowledgements

We would like to thank C. Chou, B. Li, S. Yeh, A. Kingery, A. Angert, Y. Sun, M. Jin, D. Wang, Y. You, M. Momin, T. Sun, and H. Li for their input and contributions to the NetBot Lab at Texas A&M University.

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Department of Computer Science and EngineeringTexas A&M UniversityCollege StationUSA

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