摘要
由于二维Q分类数据融合解决不了时间不同步的问题,提出了一种基于最小二乘法曲线拟合的时间对准算法。介绍了该算法的2个基本原理:最小二乘法拟合原理和时间对准原理;仿真分析该算法对2个不同采样周期的传感器进行数据融合。仿真结果表明,该算法计算速度较快,融合效率较好。
The two-dimensional classification of Q data fusion can not solve the problem of the time synchronization.Advances the algorithm of time-alignment based on the least square method of curvilinear fitting.And introduces two fundamental principles for the algorithm： the least squares fitting principle and the time alignment principle.The simulation analyses the data fusion of two sensors which have different sampling period.The result shows that the algorithm calculates faster and has better fusion efficiency.
出处
《湖南工业大学学报》
2012年第4期72-75,共4页
Journal of Hunan University of Technology
基金
国家技术创新基金资助项目(11C26214302856)
湖南省自然科学基金资助项目(11JJ4050)
湖南省教育厅科研基金资助项目(11B039
11W002
10C0620)
关键词
曲线拟合
时间对准
采样周期
数据融合
curve fitting
time-alignment
sampling period
data fusion
