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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Main Authors: Karen Uribe-Murcia, Yuriy S. Shmaliy, Jose A. Andrade-Lucio
Format: Article
Language:English
Published: Wiley 2018-01-01
Series:Journal of Electrical and Computer Engineering
Online Access:http://dx.doi.org/10.1155/2018/7456010
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author Karen Uribe-Murcia
Yuriy S. Shmaliy
Jose A. Andrade-Lucio
author_facet Karen Uribe-Murcia
Yuriy S. Shmaliy
Jose A. Andrade-Lucio
author_sort Karen Uribe-Murcia
collection DOAJ
description 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.
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institution Kabale University
issn 2090-0147
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spelling doaj-art-a3423ac018784a0cbc1a8e13c7f86da32025-02-03T05:52:46ZengWileyJournal of Electrical and Computer Engineering2090-01472090-01552018-01-01201810.1155/2018/74560107456010UFIR Filtering for GPS-Based Tracking over WSNs with Delayed and Missing DataKaren Uribe-Murcia0Yuriy S. Shmaliy1Jose A. Andrade-Lucio2Department of Electronics Engineering, Universidad de Guanajuato, 36885 Salamanca, GTO, MexicoDepartment of Electronics Engineering, Universidad de Guanajuato, 36885 Salamanca, GTO, MexicoDepartment of Electronics Engineering, Universidad de Guanajuato, 36885 Salamanca, GTO, MexicoIn 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.http://dx.doi.org/10.1155/2018/7456010
spellingShingle Karen Uribe-Murcia
Yuriy S. Shmaliy
Jose A. Andrade-Lucio
UFIR Filtering for GPS-Based Tracking over WSNs with Delayed and Missing Data
Journal of Electrical and Computer Engineering
title UFIR Filtering for GPS-Based Tracking over WSNs with Delayed and Missing Data
title_full UFIR Filtering for GPS-Based Tracking over WSNs with Delayed and Missing Data
title_fullStr UFIR Filtering for GPS-Based Tracking over WSNs with Delayed and Missing Data
title_full_unstemmed UFIR Filtering for GPS-Based Tracking over WSNs with Delayed and Missing Data
title_short UFIR Filtering for GPS-Based Tracking over WSNs with Delayed and Missing Data
title_sort ufir filtering for gps based tracking over wsns with delayed and missing data
url http://dx.doi.org/10.1155/2018/7456010
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