Accuracy improvement in sensor localization system utilizing heterogeneous wireless technologies

Accuracy improvement in sensor localization system utilizing heterogeneous wireless technologies
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DOI:
10.23919/icmu.2017.8330074
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发表时间:
2017-10
期刊:
2017 Tenth International Conference on Mobile Computing and Ubiquitous Network (ICMU)
影响因子:
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通讯作者:
Takahiro Yamamoto;S. Ishida;Kousaku Izumi;S. Tagashira;Akira Fukuda
Takahiro Yamamoto;S. Ishida;Kousaku Izumi;S. Tagashira;Akira Fukuda
中科院分区:
其他
文献类型:
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作者:
Takahiro Yamamoto;S. Ishida;Kousaku Izumi;S. Tagashira;Akira Fukuda

文献摘要

相似文献

由于 GPS(全球定位系统)在室内环境中不可用,传感器定位是构建大规模室内传感器网络时的大问题之一。我们正在开发 ZigLoc,这是一种使用 WiFi AP(接入点)作为参考的传感器定位系统,不需要额外的基础设施 [1,2]。在 ZigLoc 中,传感器节点使用 ZigBee (IEEE 802.15.4) 模块测量 WiFi AP 信号的 RSS(接收信号强度)。然后使用为 WiFi 定位系统收集的指纹来估计传感器节点的位置。然而,由于 ZigBee 和 WiFi 模块产生的 RSS 偏移,ZigLoc 的精度较低。 RSS偏移主要是由信道带宽差异引起的。在本文中,我们提出了一种差分指纹方法来提高定位精度。我们的主要想法是我们关注 WiFi AP 之间的 RSS 差异。当我们使用 ZigBee 或 WiFi 模块测量 RSS 时,AP 之间的 RSS 差异应该相同。差分指纹仅依靠RSS差异进行指纹相似度计算。我们在实际环境中进行了实验评估。实验评估表明,使用差分指纹识别方法,ZigLoc 准确度提高了约 26%。
Sensor localization is one of the big problems when building large scale indoor sensor networks because GPS (Global Positioning System) is unavailable in indoor environments. We are developing ZigLoc, a sensor localization system using WiFi APs (access points) as references, which requires no additional infrastructure [1,2]. In ZigLoc, a sensor node measures RSS (received signal strength) of WiFi AP signals using a ZigBee (IEEE 802.15.4) module. Location of a sensor node is then estimated using fingerprints collected for a WiFi localization system. However, ZigLoc exhibits low accuracy due to the RSS offset derived by ZigBee and WiFi modules. The RSS offset is mainly caused by the channel bandwidth difference. In this paper, we present a differential fingerprinting method to improve localization accuracy. Our key idea is that we focus on RSS difference between WiFi APs. RSS difference between APs should be the same when we measure RSS using either ZigBee or WiFi modules. Differential fingerprinting only relies on RSS difference in fingerprint similarity calculation. We conducted experimental evaluations in a practical environment. The experimental evaluations reveal that ZigLoc accuracy was improved by approximately 26 % using the differential fingerprinting method.