Indoor INS UWB-based human localization with missing data utilizing predictive UFIR filtering

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 U...

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Bibliographic Details
Published in:IEEE/CAA journal of automatica sinica 2019-07, Vol.6 (4), p.952-960
Main Authors: Xu, Yuan, Ahn, Choon Ki, Shmaliy, Yuriy S., Chen, Xiyuan, Bu, Lili
Format: Article
Language:English
Subjects:
Algorithms
Data integration
Impulse response
Indoor environments
Inertial navigation
Kalman filters
Missing data
Multisensor fusion
Navigation systems
Predictions
Ultrawideband
Wideband communications
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Summary: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.
ISSN:2329-9266
2329-9274
DOI:10.1109/JAS.2019.1911570