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Fault Tolerant Indoor Positioning Based on Federated Kalman Filter

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Abstract

In this article, multi-sensor indoor positioning, which is based on fusing tri-laterated position data of the target, is considered. A novel method, which is based on federated Kalman filtering and makes use of the fingerprint data, namely, federated Kalman filter with skipped covariance updating (FKF-SCU) is proposed. The data collected on two test beds are used in comparing the performances of the proposed algorithm and that of the regular federated filter. It is shown that the proposed algorithm provides fault tolerance and quick recovery, whenever signal reception from an access point is interrupted, as well as an improvement of 12.57% on the position accuracy.

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The collected data is provided at [31] and [32].

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Authors and Affiliations

  1. NATO Joint Forces Command, Brunssum, 6445 PA, The Netherlands

    Tarık Ayabakan

  2. Department of Computer Engineering, Kadir Has University, Istanbul, 34083, Türkiye

    Feza Kerestecioğlu

Authors
  1. Tarık Ayabakan
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  2. Feza Kerestecioğlu
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Correspondence to Tarık Ayabakan.

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Appendix

Appendix

The list of abbreviations used above are given in Table 7.

Table 7 List of Abbreviations.
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Ayabakan, T., Kerestecioğlu, F. Fault Tolerant Indoor Positioning Based on Federated Kalman Filter. J Sign Process Syst (2024). https://doi.org/10.1007/s11265-024-01913-y

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