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首页> 外文期刊>IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences >Localization of Passive RFID Tags by Using Broad-Type Multi-Sensing-Range (B-MSR) Method
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Localization of Passive RFID Tags by Using Broad-Type Multi-Sensing-Range (B-MSR) Method

机译:使用宽型多感测距离(B-MSR)方法对无源RFID标签进行定位

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摘要

The radio frequency identification (RFID) system has attracting attention as a new identification source that achieves a ubiquitous environment. Each RFID tag has a unique ID code, and is attached on an object whose information it contains. A user reads the unique ID code using RFID readers and obtains information about the object. One of the important applications of RFID technology is the indoor position estimation of RFID tags. It can be applied to navigation systems for people in complex buildings. In this paper, we propose an effective position estimation method named Broad-type Multi-Sensing-Range (B-MSR) method to improve the estimation error of the conventional methods using sensor model. A new reader antenna with two flexible antenna elements is introduced into B-MSR. The distance between two flexible antenna elements can be adjusted. Thus, two kinds of system parameters can be controlled, the distance between two antenna elements and the transmission power of the RFID reader. In this paper, four sensing ranges are settled by controlling the values of two parameters. The performance evaluation shows four characteristics of B-MSR. Firstly, it reduces the initial estimation error. Secondly, it reduces the moving distance. Thirdly, it reduces the number of different sensing points. Fourthly, it shortens the required estimation time.
机译:射频识别(RFID)系统作为一种实现无处不在的环境的新识别源已引起人们的关注。每个RFID标签都有一个唯一的ID码,并粘贴在其​​信息包含的对象上。用户使用RFID读取器读取唯一的ID码,并获取有关对象的信息。 RFID技术的重要应用之一是RFID标签的室内位置估计。它可以应用于复杂建筑物中的人的导航系统。在本文中,我们提出了一种有效的位置估计方法,称为宽型多感测范围(B-MSR)方法,以改善使用传感器模型的常规方法的估计误差。 B-MSR中引入了具有两个柔性天线元件的新型阅读器天线。可以调节两个柔性天线元件之间的距离。因此,可以控制两种系统参数,即两个天线元件之间的距离和RFID阅读器的发射功率。本文通过控制两个参数的值确定了四个感应范围。性能评估显示了B-MSR的四个特征。首先,它减少了初始估计误差。其次,它减少了移动距离。第三,它减少了不同感测点的数量。第四,它缩短了所需的估计时间。

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