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在无线传感器网络中基于范围的自我定位问题的优化,使用改进的子搜索算法.

Srilakshmi Aouthu1, N Dhanalakshmi2, T Seshagiri3

  • 1Electronics and Communication Engineering Department, Vasavi College of Engineering, Hyderabad, 500031, Telangana, India.

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概括

一种基于重量的新节点选择策略可以提高无线传感器网络 (WSN) 定位的准确性. 这种方法通过改进的子搜索算法来增强目标节点 (TN) 的定位,从而减少错误和成本.

关键词:
节点是一个节点.定位局部化 定位局部化定位精度 定位精度 定位精度基于范围的本地化.无线传感器网络无线传感器网络

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科学领域:

  • 无线传感器网络 (WSN) 是一种无线传感器网络.
  • 在本地化算法算法.
  • 优化技术 优化技术

背景情况:

  • 在WSNs中的自我定位使用已知的结 (AN) 位置估计目标节点 (TN) 坐标.
  • 准确的TN本地化对于位置感知应用程序至关重要,包括跟踪,医疗保健和交通监控.
  • 现有的本地化算法面临着噪音和异型网络条件的挑战.

研究的目的:

  • 提出一个基于重量的结 (AN) 选择策略,以提高WSN本地化准确性.
  • 为了减轻空间和时间变化的噪声影响,使用基于距离的AN权重.
  • 使用改进的子搜索算法计算最佳TN位置坐标.

主要方法:

  • 一个基于重量的AN选择策略,只使用四个支持GPS的AN.
  • 根据距离TN的距离,为AN分配权重,以减少噪音.
  • 采用一个改进的子搜索算法,用于全球最佳坐标计算在异型WSNs.

主要成果:

  • 拟议的CERBLA算法实现了99.24%的定位精度,距离测量误差为1.18米.
  • 与现有算法 (例如DCK-GWO,WOA-QT,ECS-NL) 相比,定位精度得到了显著提高.
  • 观察到优异的性能,特别是少于十个AN,这表明了成本效益.

结论:

  • 拟议的基于重量的AN选择策略和改进的子搜索算法有效地提高了WSN本地化准确性.
  • CERBLA算法为WSN本地化提供了一个强大而准确的解决方案,超过了几种最先进的方法.
  • 这种方法特别适合于WSN中具有成本效益的室内定位应用.