Optimal data fusion for pedestrian navigation based on UWB and MEMS

被引：0
|
作者：
Renaudin, V. [1 ]
Merminod, B. [1 ]
Kasser, M. [2 ]
机构：
[1] Ecole Polytech Fed Lausanne, CH-1015 Lausanne, Switzerland
[2] Ecole Natl Sci Geograph, Champs Sur Marne, France
来源：
2008 IEEE/ION POSITION, LOCATION AND NAVIGATION SYMPOSIUM, VOLS 1-3 | 2008年
关键词：
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：
Indoor pedestrian navigation is probably a very challenging research area. In this context, an optimal data fusion filter that hybridises a large set of observations: angles of arrival (AOA), time differences of arrival (TDOA), accelerations, angular velocities and magnetic field measurements is presented. The coupling of UWB and MEMS data relies on an Extended Kalman Filter complemented with specific procedures. Geometry based algorithms and a RANSAC paradigm that mitigates the Non Line Of Sight (NLOS) UWB propagation are detailed. The benefit of the solution is evaluated and compared with the pure inertial positioning system.
引用
收藏
页码：753 / +
页数：3
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