A Hybrid Wi-Fi Fingerprint-Based Localization Scheme Achieved by Combining Fisher Score and Stacked Sparse Autoencoder Algorithms
Joint Authors
Wang, Zhongyuan
Wang, Zijian
Fan, Li
Yu, Zhihao
Source
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-14, 14 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-04-14
Country of Publication
Egypt
No. of Pages
14
Main Subjects
Telecommunications Engineering
Abstract EN
Along with the advancement of wireless technology, indoor localization technology based on Wi-Fi has received considerable attention from academia and industry.
The fingerprint-based method is the mainstream approach for Wi-Fi indoor localization and can be easily implemented without additional hardware.
However, signal fluctuations constitute a critical issue pertaining to the extraction of robust features to achieve the required localization performance.
This study presents a fingerprint feature extraction method commonly referred to as the Fisher score–stacked sparse autoencoder (Fisher–SSAE) method.
Some features with low Fisher scores were eliminated, and the representative features were then extracted by the SSAE.
Furthermore, this study establishes a hybrid localization model constructed with the use of the global model and the submodel to avoid significant coordinate localization errors attributed to subregional localization errors.
Combined with three accessible fingerprint-based positioning methods, namely, the support vector regression, random forest regression, and the multiplayer perceptron classification, the experimental results demonstrate that the proposed methods improve the localization accuracy and response time compared to other feature extraction methods and the single localization model.
Compared with some state-of-the-art methods, the proposed methods have better localization performances when large number of features are used.
American Psychological Association (APA)
Wang, Zhongyuan& Wang, Zijian& Fan, Li& Yu, Zhihao. 2020. A Hybrid Wi-Fi Fingerprint-Based Localization Scheme Achieved by Combining Fisher Score and Stacked Sparse Autoencoder Algorithms. Mobile Information Systems،Vol. 2020, no. 2020, pp.1-14.
https://search.emarefa.net/detail/BIM-1192416
Modern Language Association (MLA)
Wang, Zhongyuan…[et al.]. A Hybrid Wi-Fi Fingerprint-Based Localization Scheme Achieved by Combining Fisher Score and Stacked Sparse Autoencoder Algorithms. Mobile Information Systems No. 2020 (2020), pp.1-14.
https://search.emarefa.net/detail/BIM-1192416
American Medical Association (AMA)
Wang, Zhongyuan& Wang, Zijian& Fan, Li& Yu, Zhihao. A Hybrid Wi-Fi Fingerprint-Based Localization Scheme Achieved by Combining Fisher Score and Stacked Sparse Autoencoder Algorithms. Mobile Information Systems. 2020. Vol. 2020, no. 2020, pp.1-14.
https://search.emarefa.net/detail/BIM-1192416
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1192416