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Erschienen in:
2019 | OriginalPaper | Buchkapitel
Rough Set Reduction Aided Cost-Efficient Indoor WLAN Localization
verfasst von : Hui Yuan, Mu Zhou, Zhian Deng, Liangbo Xie, Yong Wang, Xiaolong Yang
Erschienen in: Wireless and Satellite Systems
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Abstract
Due to the popularity of Wireless Local Area Networks (WLAN) applications, more and more access points (APs) are connected to the public network. Therefore, indoor localization technology based on public networks has a predominant development prospect. However, localization in the public network faces a lot of problems, and the excessive number of the APs in one of the most serious problems. Based on this, this paper proposes an indoor localization method based on rough set reduction. In this paper, the Received Signal Strength (RSS) signal strength from APs is used as the condition attribute of the rough set, and the optimal attribute reduction is obtained by the neighborhood rough set operation. After the rough set reduction operation, the number of APs in this paper’s data set has been reduced from 520 to 4 or 5, and the location fingerprint database has been greatly reduced. Finally, this paper applies the reduced fingerprint database for indoor localization and estimates the location of each test point.