An advanced algorithm for Fingerprint Localization based on Kalman Filter

被引：0
|
作者：
Wang, Xingxing [1 ]
Cong, Sian [1 ]
机构：
[1] Minzu Univ China, Coll Informat Engn, Software Engn, Beijing, Peoples R China
来源：
PROCEEDINGS OF 5TH IEEE CONFERENCE ON UBIQUITOUS POSITIONING, INDOOR NAVIGATION AND LOCATION-BASED SERVICES (UPINLBS) | 2018年
关键词：
Fingerprint Localization; received signal strength; noise filtering; Kalman Filter;
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
When it comes to Fingerprint Localization, the quality of fingerprint database is important to the accuracy of the localization results. As the received signal strength(RSS) collected in offline phase for Fingerprint Localization is usually companied with noise, it severely degrades the accuracy of the final localization results. To filter the noise, this paper proposed an advanced algorithm based on Kalman Filter (KF). The algorithm at first uses KF to filter noise of the measured RSS. Then it chooses several calibration points according to the weight of filtered data. Last the position of the user has been estimated according to the location of these calibration points. The experiment results illustrated that the algorithm proposed in this paper had improved the accuracy of location estimation efficiently.
引用
收藏
页码：123 / 127
页数：5
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