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.
Scientific reports
|November 13, 2025
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.
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.
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