基于潮运动模型预测和定位UWSN移动节点
Xiuwu Yu1,2, Dengfeng Li3, Yinhao Liu1
1School of Resource Environment and Safety Engineering, University of South China, Hengyang, 421001, China.
Scientific reports
|July 2, 2024
概括
这项研究通过使用潮运动模型提高了水下无线传感器网络定位精度. 它结合了利基基因算法优化的到达时间差异与卡尔曼波器预测,以改进移动节点本地化.
科学领域:
- 海洋工程 海洋工程
- 传感器网络 传感器网络
- 信号处理 信号处理
背景情况:
- 水下无线传感器网络 (UWSNs) 面临着由于潮和海洋流以及多路径效应的节点定位准确性方面的挑战.
- 现有的定位方法经常与动态环境因素作斗争,导致移动节点的性能不足.
研究的目的:
- 提出和评估一种新的方法,以提高UWSN中的移动节点的定位精度.
- 利用潮运动模型与高级算法集成,用于实时节点定位.
主要方法:
- 使用时差到达 (TDOA) 定位的初始节点定位,由利基基因算法优化.
- 实时节点位置更新采用卡尔曼波算法与优化的潮运动模型.
- 与传统的Chan和Taylor算法进行比较分析.
主要成果:
- 利基基因算法有效地避免了局部最佳,为TDOA本地化提供了更全面的优化.
- 与传统的Chan和Taylor算法相比,提出的方法在模拟中显示出更高的定位准确性.
- 基于卡尔曼波器的预测算法实现了适合实际应用的定位距离错误.
结论:
- 拟议的基于潮运动模型的定位方法显著提高了UWSN中移动节点的定位精度.
- 利基基因算法和卡尔曼过器的整合为动态的水下环境提供了强大的解决方案.
- 这种方法满足了准确的UWSN节点定位的实际应用要求.
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