Indoor localization based on CSI in dynamic environments through domain adaptation

DOI Web Site 4 References Open Access
  • Yang Liuyi
    Graduate School of Engineering, Kobe University
  • Kamada Tomio
    Graduate School of Engineering, Kobe University
  • Ohta Chikara
    Graduate School of Science, Technology and Innovation Graduate School of System Informatics, Kobe University

Description

<p>As the demand for indoor localization applications continues to grow, device-free localization based on Wi-Fi Channel State Information (CSI) has become a popular research topic. Wi-Fi signals are, however, easily affected by environmental factors such as furniture changes. These factors disable the original localization system, and rebuilding it will cost a lot of time and workforce. This is a major challenge of device-free Wi-Fi localization. To address this issue, we use a transfer learning method, “Integration of Global and Local Metrics for Domain Adaptation (IGLDA),” and improve it, aiming to adapt the original localization model to the changing environment. Consequently, the localization accuracy is improved from 26.3 % to 82.2 % by only recollecting 37.5 % of data.</p>

Journal

  • IEICE Communications Express

    IEICE Communications Express 10 (8), 564-569, 2021-08-01

    The Institute of Electronics, Information and Communication Engineers

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