Unified Fingerprinting/Ranging Localization in Harsh Environments
Context-awareness in wireless sensor networks (WSNs) relies mainly on the position of objects and humans. The provision of this positional information becomes challenging in the harsh environmental conditions where WSNs are commonly deployed. With an antagonistic philosophy of design, fingerprinting...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2015-11-01
|
| Series: | International Journal of Distributed Sensor Networks |
| Online Access: | https://doi.org/10.1155/2015/479765 |
| _version_ | 1826826002170380288 |
|---|---|
| author | Javier Prieto Juan F. De Paz Gabriel Villarrubia Fernando De la Prieta Juan M. Corchado |
| author_facet | Javier Prieto Juan F. De Paz Gabriel Villarrubia Fernando De la Prieta Juan M. Corchado |
| author_sort | Javier Prieto |
| collection | DOAJ |
| description | Context-awareness in wireless sensor networks (WSNs) relies mainly on the position of objects and humans. The provision of this positional information becomes challenging in the harsh environmental conditions where WSNs are commonly deployed. With an antagonistic philosophy of design, fingerprinting and ranging have emerged as the key technologies underpinning wireless localization in harsh environments. Fingerprinting primarily focuses on accurate estimation at the expense of exhaustive calibration. Ranging mainly pursues an easy-to-deploy solution at the expense of moderate performance. In this paper, we present a resilient framework for sustained localization based on accurate fingerprinting in critical areas and light ranging in noncritical spaces. Such framework is conceived from the Bayesian perspective that facilitates the specification of recursive algorithms for real-time operation. In comparison to conventional implementations, we assessed the proposed framework in an indoor scenario with measurements gathered by commercial devices. The presented techniques noticeably outperform current approaches, enabling a flexible adaptation to the fluctuating conditions of harsh environments. |
| first_indexed | 2024-03-12T06:04:35Z |
| format | Article |
| id | doaj.art-3a6c632f687b4093886fe6c244b8041c |
| institution | Directory Open Access Journal |
| issn | 1550-1477 |
| language | English |
| last_indexed | 2025-02-16T08:05:32Z |
| publishDate | 2015-11-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Distributed Sensor Networks |
| spelling | doaj.art-3a6c632f687b4093886fe6c244b8041c2025-02-03T05:55:24ZengWileyInternational Journal of Distributed Sensor Networks1550-14772015-11-011110.1155/2015/479765479765Unified Fingerprinting/Ranging Localization in Harsh EnvironmentsJavier Prieto0Juan F. De Paz1Gabriel Villarrubia2Fernando De la Prieta3Juan M. Corchado4 BISITE Research Group, University of Salamanca, Edificio I+D+i, C/Espejo, 37008 Salamanca, Spain BISITE Research Group, University of Salamanca, Edificio I+D+i, C/Espejo, 37008 Salamanca, Spain BISITE Research Group, University of Salamanca, Edificio I+D+i, C/Espejo, 37008 Salamanca, Spain BISITE Research Group, University of Salamanca, Edificio I+D+i, C/Espejo, 37008 Salamanca, Spain Faculty of Engineering, Osaka Institute of Technology, No. 5-16-1, Omiya, Asahi-ku, Osaka 535-8585, JapanContext-awareness in wireless sensor networks (WSNs) relies mainly on the position of objects and humans. The provision of this positional information becomes challenging in the harsh environmental conditions where WSNs are commonly deployed. With an antagonistic philosophy of design, fingerprinting and ranging have emerged as the key technologies underpinning wireless localization in harsh environments. Fingerprinting primarily focuses on accurate estimation at the expense of exhaustive calibration. Ranging mainly pursues an easy-to-deploy solution at the expense of moderate performance. In this paper, we present a resilient framework for sustained localization based on accurate fingerprinting in critical areas and light ranging in noncritical spaces. Such framework is conceived from the Bayesian perspective that facilitates the specification of recursive algorithms for real-time operation. In comparison to conventional implementations, we assessed the proposed framework in an indoor scenario with measurements gathered by commercial devices. The presented techniques noticeably outperform current approaches, enabling a flexible adaptation to the fluctuating conditions of harsh environments.https://doi.org/10.1155/2015/479765 |
| spellingShingle | Javier Prieto Juan F. De Paz Gabriel Villarrubia Fernando De la Prieta Juan M. Corchado Unified Fingerprinting/Ranging Localization in Harsh Environments International Journal of Distributed Sensor Networks |
| title | Unified Fingerprinting/Ranging Localization in Harsh Environments |
| title_full | Unified Fingerprinting/Ranging Localization in Harsh Environments |
| title_fullStr | Unified Fingerprinting/Ranging Localization in Harsh Environments |
| title_full_unstemmed | Unified Fingerprinting/Ranging Localization in Harsh Environments |
| title_short | Unified Fingerprinting/Ranging Localization in Harsh Environments |
| title_sort | unified fingerprinting ranging localization in harsh environments |
| url | https://doi.org/10.1155/2015/479765 |
| work_keys_str_mv | AT javierprieto unifiedfingerprintingranginglocalizationinharshenvironments AT juanfdepaz unifiedfingerprintingranginglocalizationinharshenvironments AT gabrielvillarrubia unifiedfingerprintingranginglocalizationinharshenvironments AT fernandodelaprieta unifiedfingerprintingranginglocalizationinharshenvironments AT juanmcorchado unifiedfingerprintingranginglocalizationinharshenvironments |