北京测绘2024，Vol.38Issue(5)：661-666,6.DOI:10.19580/j.cnki.1007-3000.2024.05.003
超高层建筑动态变形分数阶Kalman滤波提取模型
A fractional-order Kalman filter extraction model for dynamic deformation of super-high buildings
摘要
Abstract
Global navigation satellite system(GNSS)has been widely used in dynamic deformation monitoring of super-high buildings because of its advantages of direct measurement of three-dimensional(3D)coordinates without access to view.When GNSS is used to monitor buildings,the monitoring data usually contains a lot of noise.In order to extract the characteristics of deformation information more accurately,this paper used a fractional-order Kalman filter(FKF)to process the data.Through the analysis of simulation experiment data and actual case data,the correlation coefficient,root mean square error,and other evaluation parameters were compared with the Kalman filter(KF)results,so as to verify the feasibility of the method.The results show that FKF is more effective than the KF model in extracting deformation information of super-high buildings.关键词
超高层建筑/卡尔曼滤波(KF)/分数阶卡尔曼滤波(FKF)/变形监测Key words
super-high building/Kalman filter(KF)/fractional-order Kalman filter(FKF)/deformation monitoring分类
天文与地球科学引用本文复制引用
王凯,马晓东,蒋韬,余永明,王坚,赵鑫垚..超高层建筑动态变形分数阶Kalman滤波提取模型[J].北京测绘,2024,38(5):661-666,6.基金项目
国家自然科学基金(42274029) （42274029）
