摘要
针对近似三角形内点测试法(Approximate Point-In-Triangulation Test, APIT)定位精度与覆盖率不足的问题,提出了一种基于APIT与遗传算法混合的无线传感器网络定位算法.该算法通过比较分割法优化APIT算法提高定位精度,并通过遗传算法提高定位覆盖率.通过仿真对比分析,该算法相较于APIT算法定位精度提高21.62%,定位覆盖率提高4.87%.
Regarding the low localization accuracy and coverage of the Approximate Point-In-Triangulation Test(APIT)algorithm, this study proposes a hybrid localization algorithm based on the APIT and genetic algorithms for Wireless Sensor Network(WSN). This algorithm improves localization accuracy by the APIT algorithm optimized with a comparison of segmentation methods and enhances localization coverage by the genetic algorithm. Simulation results show that in comparison with the APIT algorithm, the localization accuracy and coverage of the proposed algorithm are respectively increased by 21.62% and 4.87%.
作者
李云鹏
LI Yun-Peng(School of Information Science and Engineering,Shenyang University of Technology,Shenyang 110870,China)
出处
《计算机系统应用》
2021年第10期254-258,共5页
Computer Systems & Applications
关键词
无线传感器网络
APIT
遗传算法
定位精度
覆盖率
Wireless Sensor Network(WSN)
Approximate Point-In-Triangulation Test(APIT)
genetic algorithm
localization accuracy
coverage
