摘要
针对传统到达时间差(TDOA)定位方法受噪声影响和测量精度较差造成定位误差大的问题,提出一种基于天牛须搜索(BAS)优化的TDOA三维节点定位算法(BASTDOA-3D)。通过Kalman滤波对TDOA测量的数据进行预处理,减少噪声等因素对数据的影响;将步长因子引入BAS算法,迭代计算时改变步长;利用最小适应度函数值计算未知节点的坐标位置。仿真结果表明,BASTDOA-3D算法相对于Chan算法和Taylor算法定位精度和性能明显提高。
Aiming at the problem that the traditional time difference of arrival(TDOA) positioning method is affected by noise and the poor measurement precision causes large positioning errors, a TDOA three-dimensional node positioning algorithm(BASTDOA-3 D) based on the optimization of the beetle antennae search(BAS)is proposed.The algorithm uses Kalman filtering to preprocess the data measured by TDOA to reduce the influence of noise and other factors on data.Then introduce the step size factor into the BAS algorithm, and the step size is changed during iterative calculation.Lastly, the coordinates of the unknown node can be calculated through the minimal value of fitness function.The simulation results show that the positioning precision and performance of the BASTDOA-3 D algorithm are significantly improved compared to the Chan algorithm and the Taylor algorithm.
作者
苟平章
孙梦源
刘学治
何博
GOU Pingzhang;SUN Mengyuan;LIU Xuezhi;HE Bo(College of Computer Science and Engineering,Northwest Normal University,Lanzhou,730070,China)
出处
《传感器与微系统》
CSCD
北大核心
2022年第10期141-144,共4页
Transducer and Microsystem Technologies
基金
国家自然科学基金资助项目(61561043,71961028)
全国高等院校计算机教育研究会研究项目(2019—AFCEC—079)。
关键词
无线传感器网络
到达时间差
天牛须搜索
三维节点定位
wireless sensor networks(WSNs)
time difference of arrival(TDOA)
beetle antennae search(BAS)
3D node localization