AP Optimization for Wi-Fi Indoor Positioning-Based on RSS Feature Fuzzy Mapping and Clustering
| Autor: | Zhu Liu, Xiaolong Yang, Qiaolin Pu, Wei He, Wei Nie |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Fuzzy mapping
General Computer Science Computer science RSS 010401 analytical chemistry Real-time computing General Engineering 020206 networking & telecommunications Wi-Fi indoor positioning 02 engineering and technology computer.file_format 01 natural sciences 0104 chemical sciences Positioning technology Feature (computer vision) 0202 electrical engineering electronic engineering information engineering Overhead (computing) General Materials Science multi-dimensional RSS feature lcsh:Electrical engineering. Electronics. Nuclear engineering AP optimization Cluster analysis lcsh:TK1-9971 computer fuzzy mapping and clustering |
| Zdroj: | IEEE Access, Vol 8, Pp 153599-153609 (2020) |
| ISSN: | 2169-3536 |
| Popis: | In indoor environments, Access Points (APs) are widely deployed in various locations of buildings, and thereby the AP optimization-based Wi-Fi indoor positioning technology is of great significance for achieving the satisfactory indoor Location-based Services (LBSs). However, the current Wi-Fi indoor positioning methods rarely pay attention to the diversity of Received Signal Strength (RSS) features for AP optimization, which may result in the low positioning accuracy and high positioning overhead. In order to deal with such issues, this article proposes a new concept of multi-dimensional RSS feature fuzzy mapping and clustering for AP optimization in Wi-Fi indoor positioning. Besides, the extensive experiments conducted in an actual indoor environment show that compared with the existing positioning methods, the proposed method can not only achieve higher positioning accuracy by using the optimized APs but also reduce the positioning overhead in the online phase. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|