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

机译:加权质心定位算法中带有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,准确的位置信息对于精确跟踪目标很重要。为了满足硬件安装成本和定位精度要求,介绍了一种被认为是有前途的定位算法的加权质心定位(WCL)算法。在我们以前的研究中,我们提出了一种使用距离边界的基于测试节点的WCL算法,以提高拐角和侧面区域的定位精度。所提出的算法通过平均与分布图中的锚节点数量完全匹配的测试节点位置来平均估计目标位置。但是,由于接收信号强度在实际信道条件下具有较大的可变性,因此锚节点的数量不能完全匹配,并且定位精度可能会降低。因此,本文提出了一种相交阈值来补偿定位精度。仿真结果表明,所提出的基于测试节点的WCL算法在整个区域中提供了比常规WCL算法更高的位置信息,同时减少了物理锚节点的数量。此外,我们表明在考虑小规模衰落信道条件时,通过使用相交阈值可以提高定位精度。

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