Department of Computer Science, Université de Sherbrooke, 2500 boulevard de l'Université, Sherbrooke J1K 2R1, QC, Canada.
Sensors (Basel). 2011;11(8):7606-24. doi: 10.3390/s110807606. Epub 2011 Aug 2.
Many solutions have been proposed for indoor pedestrian navigation. Some rely on pre-installed sensor networks, which offer good accuracy but are limited to areas that have been prepared for that purpose, thus requiring an expensive and possibly time-consuming process. Such methods are therefore inappropriate for navigation in emergency situations since the power supply may be disturbed. Other types of solutions track the user without requiring a prepared environment. However, they may have low accuracy. Offline tracking has been proposed to increase accuracy, however this prevents users from knowing their position in real time. This paper describes a real time indoor navigation system that does not require prepared building environments and provides tracking accuracy superior to previously described tracking methods. The system uses a combination of four techniques: foot-mounted IMU (Inertial Motion Unit), ultrasonic ranging, particle filtering and model-based navigation. The very purpose of the project is to combine these four well-known techniques in a novel way to provide better indoor tracking results for pedestrians.
已经提出了许多用于室内行人导航的解决方案。有些依赖于预先安装的传感器网络,这些网络提供了很好的准确性,但仅限于已经为此目的准备的区域,因此需要昂贵且可能耗时的过程。因此,这些方法不适合在紧急情况下进行导航,因为电源可能会受到干扰。其他类型的解决方案无需准备环境即可跟踪用户。但是,它们的精度可能较低。已经提出了离线跟踪来提高精度,但是这会阻止用户实时了解自己的位置。本文描述了一种实时室内导航系统,该系统不需要准备好的建筑物环境,并且提供的跟踪精度优于以前描述的跟踪方法。该系统使用四种技术的组合:脚部安装的惯性测量单元(IMU),超声波测距,粒子滤波和基于模型的导航。该项目的目的是将这四种众所周知的技术以新颖的方式结合起来,为行人提供更好的室内跟踪结果。