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首页> 外文期刊>AEU: Archiv fur Elektronik und Ubertragungstechnik: Electronic and Communication >Novel calibration algorithm for received signal strength based indoor real-time locating systems
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Novel calibration algorithm for received signal strength based indoor real-time locating systems

机译：基于接收信号强度的室内实时定位系统的新型标定算法

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摘要

Fingerprinting is a popular technology for indoor WLAN based locating systems. Received signal strength information from different access points is used to estimate the location of mobile users. One of the drawbacks of fingerprinting algorithm is the extensive and time-consuming calibration (training) phase, during which the received signal strength measurements from nearby wireless access points are gathered at pre-defined reference spots and stored in a database to build a prior radio signal strength map of the region. In this manuscript, we present a new, precise and time efficient calibration algorithm that combines the reference data collection procedure with the path-loss prediction model. Our algorithm requires only a few samples to be measured in a given region, and thus significantly reduces the calibration time; the rest of the signal strength database is then estimated by using path-loss prediction model. We carefully evaluate the proposed algorithm through a real-world experiment. Field test results show that our new approach reduces the calibration time without harming the location accuracy of the locating system.
机译：指纹识别技术是基于室内WLAN的定位系统的流行技术。来自不同接入点的接收信号强度信息用于估计移动用户的位置。指纹识别算法的缺点之一是广泛且耗时的校准（训练）阶段，在此阶段中，来自附近无线接入点的接收信号强度测量值被收集在预定义的参考点处，并存储在数据库中以构建先前的无线电该区域的信号强度图。在此手稿中，我们提出了一种新的，精确且省时的校准算法，该算法将参考数据收集过程与路径损耗预测模型结合在一起。我们的算法只需要在给定区域内测量少量样品，从而大大减少了校准时间;然后，使用路径损耗预测模型来估算其余的信号强度数据库。我们通过实际实验仔细评估了提出的算法。现场测试结果表明，我们的新方法减少了校准时间，而不会损害定位系统的定位精度。

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