Bayesian filters for ToF and RSS measurements for indoor positioning of a mobile object

被引：0

作者：

Galov, Aleksandr ^{[1
]}

Moschevikin, Alex ^{[1
]}

机构：

[1] Petrozavodsk State Univ, RTL Serv Ltd, Petrozavodsk, Russia

来源：

2013 INTERNATIONAL CONFERENCE ON INDOOR POSITIONING AND INDOOR NAVIGATION (IPIN) | 2013年

关键词：

Bayesian filtering; particle filter; grid-based filter; indoor positioning; NanoLOC; ToF; RSS;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The article describes three different types of Bayesian filtering methods (Kalman filter, particle filter, and grid-based filter) applied for indoor localization in NanoLOC (IEEE 802.15.4a) wireless sensors network. Received Signal Strength, Time-of-flight measurements and the building structure were used for position calculations. The comparison of the applied algorithms revealed conditions at which one algorithm is superior to others. The techniques described in this paper are not depending on the used RF technology.

引用

页数：8

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