Indoor Positioning Using Federated Kalman Filter

被引：0
|
作者：
Aybakan, Tarik [1 ]
Kerestecioglu, Feza [2 ]
机构：
[1] Istanbul Naval Shipyard, Underwater Syst Div, Istanbul, Turkey
[2] Kadir Has Univ, Dept Comp Engn, Istanbul, Turkey
来源：
2018 3RD INTERNATIONAL CONFERENCE ON COMPUTER SCIENCE AND ENGINEERING (UBMK) | 2018年
关键词：
federated Kalman filter; data fusion; indoor positioning;
D O I：
暂无
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
In this paper, the performance of a multi-sensor fusion technique, namely Federated Kalman Filter (FKF) is studied in the context of indoor positioning problem. Kalman filters having centralized and decentralized structures are widely used in outdoor positioning and navigation applications. Global Positioning System (GI'S) is the most commonly used system for outdoor positioning/navigation, which cannot be used indoors due to the signal loss. In this study, a decentralized structure for FKF is applied in indoor positioning problem by taking its outdoor navigation performance into consideration. Simulations are perl4med with distance measurements, which are assumed to be calculated by using Received Signal Strength (RSS). Results gathered via different simulations are evaluated as promising for future studies.
引用
收藏
页码：483 / 488
页数：6
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