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A Distance Boundary with Virtual Nodes for the Weighted Centroid Localization Algorithm

机译:对加权质心定位算法的虚拟节点的距离边界

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摘要

In wireless sensor networks, accurate location information is important for precise tracking of targets. In order to satisfy hardware installation cost and localization accuracy requirements, a weighted centroid localization (WCL) algorithm, which is considered a promising localization algorithm, was introduced. In our previous research, we proposed a test node-based WCL algorithm using a distance boundary to improve the localization accuracy in the corner and side areas. The proposed algorithm estimates the target location by averaging the test node locations that exactly match with the number of anchor nodes in the distribution map. However, since the received signal strength has large variability in real channel conditions, the number of anchor nodes is not exactly matched and the localization accuracy may deteriorate. Thus, we propose an intersection threshold to compensate for the localization accuracy in this paper. The simulation results show that the proposed test node-based WCL algorithm provides higher-precision location information than the conventional WCL algorithm in entire areas, with a reduced number of physical anchor nodes. Moreover, we show that the localization accuracy is improved by using the intersection threshold when considering small-scale fading channel conditions.
机译:在无线传感器网络中,精确的位置信息对于精确跟踪目标是重要的。为了满足硬件安装成本和本地化精度要求,介绍了一种被认为是一个有希望的定位算法的加权质心定位(WCL)算法。在我们以前的研究中,我们提出了一种基于测试节点的WCL算法,使用距离边界来提高角落和侧面区域的定位精度。所提出的算法通过对与分发图中的锚节点的数量完全匹配的测试节点位置来估计目标位置。然而,由于所接收的信号强度在真实信道条件下具有大的可变性,所以锚节点的数量不完全匹配,并且定位精度可能会恶化。因此,我们提出了一个交叉点阈值来补偿本文中的定位精度。仿真结果表明,基于测试节点的WCL算法提供比传统的WCL算法在整个区域中的高精度位置信息,具有减少的物理锚节点。此外,我们表明,在考虑小规模衰落信道条件时,通过使用交叉阈值来提高本地化精度。

著录项

  • 作者

    Kwang-Yul Kim; Yoan Shin;

  • 作者单位
  • 年度 2018
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  • 原文格式 PDF
  • 正文语种 eng
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