Indoor ins/UWB-based human localization with missing data utilizing predictive ufir filtering

Yuan Xu, Choon Ki Ahn, Yuriy S. Shmaliy, Xiyuan Chen, Lili Bu

Research output: Contribution to journalArticlepeer-review

24 Citations (Scopus)


A combined algorithm for the loosely fused ultra wide band (UWB)and inertial navigation system (INS)-based measurements is designed under the indoor human navigation conditions with missing data. The scheme proposed fuses the INS- and UWB-derived positions via a data fusion filter. Since the UWB signal is prone to drift in indoor environments and its outage highly affects the integrated scheme reliability, we also consider the missing data problem in UWB measurements. To overcome this problem, the loosely-coupled INS UWB-integrated scheme is augmented with a prediction option based on the predictive unbiased finite impulse response (UFIR)fusion filter. We show experimentally that, the standard UFIR fusion filter has higher robustness than the Kalman filter. It is also shown that the predictive UFIR fusion filter is able to produce an acceptable navigation accuracy under temporary missing UWB-data.

Original languageEnglish
Article number8753752
Pages (from-to)952-960
Number of pages9
JournalIEEE/CAA Journal of Automatica Sinica
Issue number4
Publication statusPublished - 2019 Jul


  • INS/UWB model
  • Indoor human navigation
  • Prediction
  • Unbiased fir filter

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Information Systems
  • Artificial Intelligence


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