Comparative Analysis of Indoor Localization across Various Wireless Technologies

Amanpreet Singh, Matin Emam, Yaser Al Mtawa
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Abstract

This article examines the comparative effectiveness of three indoor node localization techniques—Multilateration, the Weighted Centroid algorithm, and Grid-based Received Signal Strength (RSS)—in wireless networking applications. The comparison is based on their performance against localization accuracy using RSS Indicator (RSSI) data in three experiments. The experiments utilized internally generated or real-world datasets with RSSI values for the unknown tag nodes. The datasets were obtained from various sources and evaluated in different scenarios to determine the efficiency of the three localization techniques. The results were evaluated and compared using mean error and standard deviation metrics. The findings indicate that trilateration achieves superior localization accuracy and precision in a Bluetooth Low Energy (BLE) environment compared to Wi-Fi and ZigBee. The Centroid technique showed the highest resistance to noise and outliers but is positioned biased (unlike Trilateration). Besides that, the Grid-based RSS technique is highly sensitive to noise, and theoretical RSS. These findings can greatly assist researchers and network operators in carefully selecting the most suitable localization technique for their wireless networking applications, taking into account the specific wireless technology utilized and their unique needs and limitations.
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不同无线技术的室内定位比较分析
本文研究了在无线网络应用中三种室内节点定位技术——多重定位、加权质心算法和基于网格的接收信号强度(RSS)——的比较有效性。在三个实验中,利用RSS指示器(RSSI)数据对它们的定位精度进行了比较。实验利用内部生成的或真实世界的数据集,未知标签节点的RSSI值。这些数据集来自不同的来源,并在不同的场景下进行评估,以确定三种定位技术的效率。使用平均误差和标准偏差指标对结果进行评估和比较。研究结果表明,与Wi-Fi和ZigBee相比,三边定位在低功耗蓝牙(BLE)环境下实现了更高的定位精度和精度。质心技术显示出对噪声和异常值的最高抵抗力,但定位有偏(与三边测量不同)。此外,基于网格的RSS技术对噪声和理论RSS都非常敏感。这些发现可以极大地帮助研究人员和网络运营商在考虑到所使用的特定无线技术及其独特需求和局限性的情况下,为其无线网络应用仔细选择最合适的定位技术。
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