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A Singular Value Decomposition Based Upgraded DV-Hop Localization Algorithm for Wireless Sensor Networks

机译:无线传感器网络中基于奇异值分解的升级DV-Hop定位算法

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摘要

Finding the location of unknown nodes using a computationally inexpensive range-free localization method is one of the most popular research areas in wireless sensor networks (WSNs). DV-hop localization is one of the most popular and localization methods in WSNs. In this article, the authors propose an upgraded DV-Hop based localization method that provides better location accuracy along with minimal computational complexity. In the proposed method, the second step of DV-Hop algorithm is modified by improving the effective average hop size and the third step of DV-Hop is modified to enhance the localization accuracy by minimizing the ranging errors. The said minimization of ranging errors has been achieved by using singular value decomposition-based estimation method. The authors have compared the upgraded DV-Hop localization method with original DV-Hop localization method as well as with improved versions of DV-Hop localization method. The simulation results show that the proposed method has less computational complexity and high location accuracy than the compared methods.
机译:使用计算上便宜的无范围定位方法来查找未知节点的位置是无线传感器网络(WSN)中最受欢迎的研究领域之一。 DV-hop定位是WSN中最流行的定位方法之一。在本文中,作者提出了一种基于DV-Hop的升级定位方法,该方法可提供更好的定位精度以及最小的计算复杂度。在该方法中,通过提高有效平均跳数来修改DV-Hop算法的第二步,并通过最小化测距误差来修改DV-Hop的第三步以提高定位精度。通过使用基于奇异值分解的估计方法已经实现了所述测距误差的最小化。作者将升级后的DV-Hop定位方法与原始DV-Hop定位方法以及改进版本的DV-Hop定位方法进行了比较。仿真结果表明,所提出的方法比所提方法具有较低的计算复杂度和较高的定位精度。

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