K-Ranking RSSI Vectors Cosine Value Localization Method for Indoor Positioning-Reference-Cited by-同舟云学术

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K-Ranking RSSI Vectors Cosine Value Localization Method for Indoor Positioning

Published:2022-07-11 Issue: Volume: Page:
ISSN:
Container-title:2022 10th International Conference on Agro-geoinformatics (Agro-Geoinformatics)
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Author:

Zhang Aiguo¹,Wu Qunyong²^ORCID,Han Litao³^ORCID,Huang Yutong¹,Jin Xinping⁴

Affiliation:

1. School of Computer and Information engineering, Xiamen University of Technology,Xiamen,China

2. Fuzhou University,Spatial Data Mining and Information sharing of MOE,Fuzhou,China

3. College of Geomatics, Shandong University of Science and Technology,Qingdao,China

4. Surveying and GIS Huadong Engineering (Fujian) Corporation Limited,Fuzhou,China

Funder

Natural Science Foundation of Fujian Province

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9858936/9858951/09858987.pdf?arnumber=9858987

Reference37 articles.

1. A modified mobile location algorithm based on RSSI;zhi;Journal of Beijing University of Posts and Telecommunications,2013

2. A wireless positioning method based on deep neural network;liu;Computer Engineering,2016

3. Bayesian filtering for indoor localization and tracking in wireless sensor networks

4. A low complexity map-aided Fuzzy Decision Tree for pedestrian indoor/outdoor navi - gation using smartphone;liao;Proc IPIN,2016

5. On a problem of adaptive estimation in Gaussian white noise;lepskii;Theor Probab Appl,2006

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