Homogeneous Features Utilization to Address the Device Heterogeneity Problem in Fingerprint Localization
Homogeneous Features Utilization to Address the Device Heterogeneity Problem in Fingerprint Localization
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DOI：
10.1109/jsen.2013.2290736
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发表时间：
2014-04-01
影响因子：
4.3
通讯作者：
Chen, Gen-Huey
中科院分区：
文献类型：
--
作者：
Chen, Lyu-Han;Wu, Eric Hsiao-Kuang;Chen, Gen-Huey
在普适计算环境中构建上下文感知服务使得基于无线局域网的室内定位系统得以广泛发展。在指纹定位中，来自接入点 (AP) 的射频 (RF) 信号强度用位置标签进行注释，以构建 RF 指纹图。然而，由于设备异质性导致新接收到的信号强度 (RSS) 变化，这可能会导致 RSS 模式不匹配，从而危及定位精度。基于对新的单个设备的 RSS 进行额外手动校准的解决方案可以解决该问题。然而，它们对于现实世界的部署来说是费力且不切实际的。本文提出一种利用不同设备的两个同质特征的室内定位算法来解决指纹定位中的设备异构性问题。 RSS 顺序的特征以及不同设备测量的 RSS 之间的线性相关性得到了广泛的研究。实验结果表明，所提出的定位算法解决了设备异构性问题，无需对不同设备进行额外的手动校准。
Building context-aware services in pervasive computing environments have enabled the wide development of wireless local area network-based indoor positioning systems. In fingerprint localization, radio frequency (RF) signal strengths from access points (APs) are annotated with location labels to build the map of RF fingerprints. However, the newly received signal strength (RSS) variation due to device heterogeneity, which may cause RSS pattern mismatch, could jeopardize positioning accuracy. Solutions based on extra manual calibrations of RSSs for new, individual devices could address the problem. However, they are laborious and unpractical for real-world deployment. In this paper, an indoor positioning algorithm that utilizes two homogeneous features of different devices is proposed to solve the problem of device heterogeneity in fingerprint localization. The features of RSS order and linear dependency between RSSs measured by different devices are extensively investigated. The experimental results show that the proposed positioning algorithm solves the device heterogeneity problem without requiring extra manual calibration for diverse devices.