An Efficient Hybrid RSS-AoA Localization for 3D Wireless Sensor Networks
Wireless sensor networks (WSNs) enable many applications such as intelligent control, prediction, tracking, and other communication network services, which are integrated into many technologies of the Internet-of-Things. The conventional localization frameworks may not function well in practical env...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2019-05-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/19/9/2121 |
| _version_ | 1798005990268862464 |
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| author | Thu L. N. Nguyen Tuan D. Vy Yoan Shin |
| author_facet | Thu L. N. Nguyen Tuan D. Vy Yoan Shin |
| author_sort | Thu L. N. Nguyen |
| collection | DOAJ |
| description | Wireless sensor networks (WSNs) enable many applications such as intelligent control, prediction, tracking, and other communication network services, which are integrated into many technologies of the Internet-of-Things. The conventional localization frameworks may not function well in practical environments since they were designed either for two-dimensional space only, or have high computational costs, or are sensitive to measurement errors. In order to build an accurate and efficient localization scheme, we consider in this paper a hybrid received signal strength and angle-of-arrival localization in three-dimensional WSNs, where sensors are randomly deployed with the transmit power and the path loss exponent unknown. Moreover, in order to avoid the difficulty of solving the conventional maximum-likelihood estimator due to its non-convex and highly complex natures, we derive a weighted least squares estimate to estimate jointly the location of the unknown node and the two aforementioned channel components through some suitable approximations. Simulation results confirm the effectiveness of the proposed method. |
| first_indexed | 2024-04-11T12:47:47Z |
| format | Article |
| id | doaj.art-c6acbb367a344db381ac6362aefd0235 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-11T12:47:47Z |
| publishDate | 2019-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-c6acbb367a344db381ac6362aefd02352022-12-22T04:23:18ZengMDPI AGSensors1424-82202019-05-01199212110.3390/s19092121s19092121An Efficient Hybrid RSS-AoA Localization for 3D Wireless Sensor NetworksThu L. N. Nguyen0Tuan D. Vy1Yoan Shin2School of Electronic Engineering, Soongsil University, Seoul 06978, KoreaSchool of Electronic Engineering, Soongsil University, Seoul 06978, KoreaSchool of Electronic Engineering, Soongsil University, Seoul 06978, KoreaWireless sensor networks (WSNs) enable many applications such as intelligent control, prediction, tracking, and other communication network services, which are integrated into many technologies of the Internet-of-Things. The conventional localization frameworks may not function well in practical environments since they were designed either for two-dimensional space only, or have high computational costs, or are sensitive to measurement errors. In order to build an accurate and efficient localization scheme, we consider in this paper a hybrid received signal strength and angle-of-arrival localization in three-dimensional WSNs, where sensors are randomly deployed with the transmit power and the path loss exponent unknown. Moreover, in order to avoid the difficulty of solving the conventional maximum-likelihood estimator due to its non-convex and highly complex natures, we derive a weighted least squares estimate to estimate jointly the location of the unknown node and the two aforementioned channel components through some suitable approximations. Simulation results confirm the effectiveness of the proposed method.https://www.mdpi.com/1424-8220/19/9/2121wireless sensor networkshybrid localizationreceived signal strengthangle-of-arrivalsuboptimalweighted least squares estimate |
| spellingShingle | Thu L. N. Nguyen Tuan D. Vy Yoan Shin An Efficient Hybrid RSS-AoA Localization for 3D Wireless Sensor Networks Sensors wireless sensor networks hybrid localization received signal strength angle-of-arrival suboptimal weighted least squares estimate |
| title | An Efficient Hybrid RSS-AoA Localization for 3D Wireless Sensor Networks |
| title_full | An Efficient Hybrid RSS-AoA Localization for 3D Wireless Sensor Networks |
| title_fullStr | An Efficient Hybrid RSS-AoA Localization for 3D Wireless Sensor Networks |
| title_full_unstemmed | An Efficient Hybrid RSS-AoA Localization for 3D Wireless Sensor Networks |
| title_short | An Efficient Hybrid RSS-AoA Localization for 3D Wireless Sensor Networks |
| title_sort | efficient hybrid rss aoa localization for 3d wireless sensor networks |
| topic | wireless sensor networks hybrid localization received signal strength angle-of-arrival suboptimal weighted least squares estimate |
| url | https://www.mdpi.com/1424-8220/19/9/2121 |
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