Advanced integration of WiFi and inertial navigation systems for indoor mobile positioning
Advanced integration of WiFi and inertial navigation systems for indoor mobile positioning
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DOI：
10.1155/asp/2006/86706
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发表时间：
2006-01-01
期刊：
影响因子：
--
通讯作者：
Marx, Francois
中科院分区：
文献类型：
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作者：
Evennou, Frederic;Marx, Francois
本文提出了一种辅助航位推算导航结构和信号处理算法，通过融合行人航位推算和 WiFi 信号强度测量来实现自主移动设备的自定位。 WiFi 和惯性导航系统 (INS) 在广泛的应用中用于定位和姿态确定。在过去几年中，出现了许多低成本惯性传感器。尽管它们存在较大误差，但 WiFi 测量可用于纠正削弱基于该技术的导航的漂移。另一方面，INS传感器可以与WiFi定位系统交互，提供高精度实时导航。提出了一种基于卡尔曼滤波器和粒子滤波器的结构。它融合了来自这两种独立技术的异构信息。最后，对所提出的架构的优点进行了评估，并与纯 WiFi 和 INS 定位系统进行了比较。版权所有 (C) 2006 Hindawi 出版公司。版权所有。
This paper presents an aided dead-reckoning navigation structure and signal processing algorithms for self localization of an autonomous mobile device by fusing pedestrian dead reckoning and WiFi signal strength measurements. WiFi and inertial navigation systems ( INS) are used for positioning and attitude determination in a wide range of applications. Over the last few years, a number of low-cost inertial sensors have become available. Although they exhibit large errors, WiFi measurements can be used to correct the drift weakening the navigation based on this technology. On the other hand, INS sensors can interact with the WiFi positioning system as they provide high-accuracy real-time navigation. A structure based on a Kalman filter and a particle filter is proposed. It fuses the heterogeneous information coming from those two independent technologies. Finally, the benefits of the proposed architecture are evaluated and compared with the pure WiFi and INS positioning systems. Copyright (C) 2006 Hindawi Publishing Corporation. All rights reserved.