Localization Algorithm for 3D Sensor Networks: A Recursive Data Fusion Approach

Location-based applications for security and assisted living, such as human location tracking, pet tracking and others, have increased considerably in the last few years, enabled by the fast growth of sensor networks. Sensor location information is essential for several network protocols and applica...

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Autores principales:	Rafaela Villalpando-Hernandez, Cesar Vargas-Rosales, David Munoz-Rodriguez
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	recursive localization position information fusion 3D sensor networks Chemical technology TP1-1185
Acceso en línea:	https://doaj.org/article/47c48945fe604c549defba33cca6471a
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spelling	oai:doaj.org-article:47c48945fe604c549defba33cca6471a2021-11-25T18:58:02ZLocalization Algorithm for 3D Sensor Networks: A Recursive Data Fusion Approach10.3390/s212276261424-8220https://doaj.org/article/47c48945fe604c549defba33cca6471a2021-11-01T00:00:00Zhttps://www.mdpi.com/1424-8220/21/22/7626https://doaj.org/toc/1424-8220Location-based applications for security and assisted living, such as human location tracking, pet tracking and others, have increased considerably in the last few years, enabled by the fast growth of sensor networks. Sensor location information is essential for several network protocols and applications such as routing and energy harvesting, among others. Therefore, there is a need for developing new alternative localization algorithms suitable for rough, changing environments. In this paper, we formulate the Recursive Localization (RL) algorithm, based on the recursive coordinate data fusion using at least three anchor nodes (ANs), combined with a multiplane location estimation, suitable for 3D ad hoc environments. The novelty of the proposed algorithm is the recursive fusion technique to obtain a reliable location estimation of a node by combining noisy information from several nodes. The feasibility of the RL algorithm under several network environments was examined through analytic formulation and simulation processes. The proposed algorithm improved the location accuracy for all the scenarios analyzed. Comparing with other 3D range-based positioning algorithms, we observe that the proposed RL algorithm presents several advantages, such as a smaller number of required ANs and a better position accuracy for the worst cases analyzed. On the other hand, compared to other 3D range-free positioning algorithms, we can see an improvement by around 15.6% in terms of positioning accuracy.Rafaela Villalpando-HernandezCesar Vargas-RosalesDavid Munoz-RodriguezMDPI AGarticlerecursive localizationposition information fusion3D sensor networksChemical technologyTP1-1185ENSensors, Vol 21, Iss 7626, p 7626 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	recursive localization position information fusion 3D sensor networks Chemical technology TP1-1185
spellingShingle	recursive localization position information fusion 3D sensor networks Chemical technology TP1-1185 Rafaela Villalpando-Hernandez Cesar Vargas-Rosales David Munoz-Rodriguez Localization Algorithm for 3D Sensor Networks: A Recursive Data Fusion Approach
description	Location-based applications for security and assisted living, such as human location tracking, pet tracking and others, have increased considerably in the last few years, enabled by the fast growth of sensor networks. Sensor location information is essential for several network protocols and applications such as routing and energy harvesting, among others. Therefore, there is a need for developing new alternative localization algorithms suitable for rough, changing environments. In this paper, we formulate the Recursive Localization (RL) algorithm, based on the recursive coordinate data fusion using at least three anchor nodes (ANs), combined with a multiplane location estimation, suitable for 3D ad hoc environments. The novelty of the proposed algorithm is the recursive fusion technique to obtain a reliable location estimation of a node by combining noisy information from several nodes. The feasibility of the RL algorithm under several network environments was examined through analytic formulation and simulation processes. The proposed algorithm improved the location accuracy for all the scenarios analyzed. Comparing with other 3D range-based positioning algorithms, we observe that the proposed RL algorithm presents several advantages, such as a smaller number of required ANs and a better position accuracy for the worst cases analyzed. On the other hand, compared to other 3D range-free positioning algorithms, we can see an improvement by around 15.6% in terms of positioning accuracy.
format	article
author	Rafaela Villalpando-Hernandez Cesar Vargas-Rosales David Munoz-Rodriguez
author_facet	Rafaela Villalpando-Hernandez Cesar Vargas-Rosales David Munoz-Rodriguez
author_sort	Rafaela Villalpando-Hernandez
title	Localization Algorithm for 3D Sensor Networks: A Recursive Data Fusion Approach
title_short	Localization Algorithm for 3D Sensor Networks: A Recursive Data Fusion Approach
title_full	Localization Algorithm for 3D Sensor Networks: A Recursive Data Fusion Approach
title_fullStr	Localization Algorithm for 3D Sensor Networks: A Recursive Data Fusion Approach
title_full_unstemmed	Localization Algorithm for 3D Sensor Networks: A Recursive Data Fusion Approach
title_sort	localization algorithm for 3d sensor networks: a recursive data fusion approach
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/47c48945fe604c549defba33cca6471a
work_keys_str_mv	AT rafaelavillalpandohernandez localizationalgorithmfor3dsensornetworksarecursivedatafusionapproach AT cesarvargasrosales localizationalgorithmfor3dsensornetworksarecursivedatafusionapproach AT davidmunozrodriguez localizationalgorithmfor3dsensornetworksarecursivedatafusionapproach
_version_	1718410459994914816

Localization Algorithm for 3D Sensor Networks: A Recursive Data Fusion Approach

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