Localization Algorithm for 3D Sensor Networks: A Recursive Data Fusion Approach
Autor: | Cesar Vargas-Rosales, Rafaela Villalpando-Hernandez, David Munoz-Rodriguez |
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Jazyk: | angličtina |
Rok vydání: | 2021 |
Předmět: |
3D sensor networks
Computer science TP1-1185 Biochemistry Article Analytical Chemistry Computer Communication Networks Position (vector) Humans Computer Simulation Electrical and Electronic Engineering Instrumentation Node (networking) Chemical technology position information fusion Sensor fusion Atomic and Molecular Physics and Optics Range (mathematics) recursive localization Routing (electronic design automation) Communications protocol Algorithm Wireless sensor network Energy harvesting Wireless Technology Algorithms |
Zdroj: | Sensors (Basel, Switzerland) Sensors Volume 21 Issue 22 Sensors, Vol 21, Iss 7626, p 7626 (2021) |
ISSN: | 1424-8220 |
Popis: | 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. |
Databáze: | OpenAIRE |
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