UFIR Filtering for GPS-Based Tracking over WSNs with Delayed and Missing Data

In smart cities, vehicles tracking is organized to increase safety by localizing cars using the Global Positioning System (GPS). The GPS-based system provides accurate tracking but is also required to be reliable and robust. As a main estimator, we propose using the unbiased finite impulse response...

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Bibliographic Details
Published in:Journal of electrical and computer engineering 2018-01, Vol.2018 (2018), p.1-9
Main Authors: Uribe-Murcia, Karen, Andrade-Lucio, Jose A., Shmaliy, Yuriy S.
Format: Article
Language:English
Subjects:
Algorithms
Automobiles
Filtration
Global positioning systems
GPS
H infinity
Impulse response
Kalman filters
Microelectromechanical systems
Missing data
Neural networks
Noise
Remote sensors
Satellite navigation systems
Sensors
Signal processing
State space models
Tracking
Wireless sensor networks
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Summary:In smart cities, vehicles tracking is organized to increase safety by localizing cars using the Global Positioning System (GPS). The GPS-based system provides accurate tracking but is also required to be reliable and robust. As a main estimator, we propose using the unbiased finite impulse response (UFIR) filter, which meets these needs as being more robust than the Kalman filter (KF). The UFIR filter is developed for vehicle tracking in discrete-time state-space over wireless sensor networks (WSNs) with time-stamped data discretely delayed on k-step-lags and missing data. The state-space model is represented in a way such that the UFIR filter, KF, and H∞ filter can be used universally. Applications are given for measurement data, which are cooperatively transferred from a vehicle to a central station through several nodes with k-step-lags. Better tracking performance of the UFIR filter is shown experimentally.
ISSN:2090-0147
2090-0155
DOI:10.1155/2018/7456010