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Performance Analysis of the New Filtering Algorithm with Kalman on Indoor Positioning System

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Hybrid Intelligent Systems (HIS 2021)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 420))

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Abstract

Location-based service (LBS) is a context-aware service, which has an awareness of its surroundings. An accurate user positioning system is required for LBS. Indoor Positioning System (IPS) is essential for LBS to determine user position in an indoor environment. The new filtering algorithm increases the accuracy of IPS, but it does not consider the fluctuation of the received signal strength index (RSSI) values, which affects the prediction results. This research describes an accuracy and performance analysis of the new filtering algorithm with Kalman filter, which is used to process the fluctuation of the test signals. The experimental result shows that the proposed method increases the positioning accuracy and computational time by as much as 0.4% and eight milliseconds, respectively than the existing method. This has made it applicable in most environments.

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Author information

Authors and Affiliations

  1. Department of Informatics, Institut Teknologi Sepuluh Nopember, Surabaya, Indonesia

    Lucas Susanto & Tohari Ahmad

Authors
  1. Lucas Susanto
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  2. Tohari Ahmad
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Editor information

Editors and Affiliations

  1. Scientific Network for Innovation and Research Excellence, Machine Intelligence Research Labs (MIR Labs), Auburn, WA, USA

    Ajith Abraham

  2. Campus Centre de Créteil, Université Paris-Est Créteil, Créteil, France

    Patrick Siarry

  3. Department of Computer Science, Università degli Studi di Milano, Milan, Milano, Italy

    Vincenzo Piuri

  4. Scientific Network for Innovation and Research Excellence, Machine Intelligence Research Labs (MIR Labs), Auburn, WA, USA

    Niketa Gandhi

  5. University of Bari, Bari, Italy

    Gabriella Casalino

  6. Division of Graduate Studies and Research, Tijuana Institute of Technology, Tijuana, Mexico

    Oscar Castillo

  7. Ontario Tech University, Oshawa, ON, Canada

    Patrick Hung

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Susanto, L., Ahmad, T. (2022). Performance Analysis of the New Filtering Algorithm with Kalman on Indoor Positioning System. In: Abraham, A., et al. Hybrid Intelligent Systems. HIS 2021. Lecture Notes in Networks and Systems, vol 420. Springer, Cham. https://doi.org/10.1007/978-3-030-96305-7_24

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