基于位置和传感器信息的行人导航位置跟踪系统研究

M. Fujii, Ryo Ogawara, Hiroyuki Hatano, Yu Watanabe
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引用次数: 2

摘要

最近,我们可以使用移动终端在多个地点使用各种网络连接。利用位置信息为移动终端扩展业务。对于这些服务,我们需要估计移动设备的位置。众所周知,我们可以使用GPS来获得终端的绝对位置。另一方面,我们可以利用内置传感器的传统汽车导航系统所采用的航位推算方法来获得终端的相对运动。最新的移动终端,如智能手机,都配备了一些传感器来捕捉终端的行为。本文提出了一种将GPS的绝对位置信息与传感器的相对运动信息相结合的定位估计方法。结合绝对位置和相对运动信息,采用卡尔曼滤波算法,通过现场实验对所提方法的估计精度进行了评价。现场实验结果表明,利用传感器信息的方法优于不使用传感器信息的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A study on position tracking system for pedestrian navigation using location and sensor information
Recently, we can use various network connections at several location using mobile terminals. Services by using location information expand for the mobile terminals. For these services, we need to estimate the location of the moving mobile devices. It is well-known that we can use the GPS in order to obtain the absolute position of the terminal. On the other hand, we can employ dead-reckoning methods adopted by the conventional car navigation system using builtin sensors to obtain the relative movement of the terminal. The latest mobile terminals such as smart phone are equipped with some sensors to capture the behavior of the terminal. In this paper, we propose a new location estimation method which combines the absolute position information by the GPS with the relative movement information by the sensors. We evaluate the proposed method in terms of the estimation accuracy by field experiments when we adopt the Kalman filter algorithm by combining the absolute location and the relative movement information. From the results of our field experiments, we show that the proposed method using the sensor information outperforms the conventional one without it.
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