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Enhance RSS-Based Indoor Localization Accuracy by Leveraging Environmental Physical Features
Joint Authors
Xiang, Peng
Ji, Peng
Zhang, Dian
Source
Wireless Communications and Mobile Computing
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-07-09
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Information Technology and Computer Science
Abstract EN
Indoor localization technologies based on Radio Signal Strength (RSS) attract many researchers’ attentions, since RSS can be easily obtained by wireless devices without additional hardware.
However, such technologies are apt to be affected by indoor environments and multipath phenomenon.
Thus, the accuracy is very difficult to improve.
In this paper, we put forward a method, which is able to leverage various other resources in localization.
Besides the traditional RSS information, the environmental physical features, e.g., the light, temperature, and humidity information, are all utilized for localization.
After building a comprehensive fingerprint map for the above information, we propose an algorithm to localize the target based on Naïve Bayesian.
Experimental results show that the successful positioning accuracy can dramatically outperform traditional pure RSS-based indoor localization method by about 39%.
Our method has the potential to improve all the radio frequency (RF) based localization approaches.
American Psychological Association (APA)
Xiang, Peng& Ji, Peng& Zhang, Dian. 2018. Enhance RSS-Based Indoor Localization Accuracy by Leveraging Environmental Physical Features. Wireless Communications and Mobile Computing،Vol. 2018, no. 2018, pp.1-8.
https://search.emarefa.net/detail/BIM-1216363
Modern Language Association (MLA)
Xiang, Peng…[et al.]. Enhance RSS-Based Indoor Localization Accuracy by Leveraging Environmental Physical Features. Wireless Communications and Mobile Computing No. 2018 (2018), pp.1-8.
https://search.emarefa.net/detail/BIM-1216363
American Medical Association (AMA)
Xiang, Peng& Ji, Peng& Zhang, Dian. Enhance RSS-Based Indoor Localization Accuracy by Leveraging Environmental Physical Features. Wireless Communications and Mobile Computing. 2018. Vol. 2018, no. 2018, pp.1-8.
https://search.emarefa.net/detail/BIM-1216363
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1216363