一种抗差的形变数据插补方法A interpolation method of deformation monitoring data series
刘宁,戴吾蛟,刘斌
摘要(Abstract)：
针对传统基于空间插值和时间序列上的插值补全形变缺失数据的方法在空间点位分布稀疏、观测值连续缺失以及含有粗差的情况下插补效果不佳的问题,提出了一种基于抗差Kriged Kalman Filter的形变缺失数据插补方法。该方法是一种时空插值的算法,在空间点位分布稀疏时考虑时间上的相关性,在时间上出现连续缺失时考虑其他点位对插补点的影响,以提高插补缺失数据的精度。又将抗差估计融合到Kriged Kalman Filter中以抵抗形变数据中粗差对插补精度的影响。利用模拟数据及天津GPS地面沉降数据进行了实验分析。结果表明:由于该法考虑了监测点的时空相关性以及具有抗差性能,使得插补结果在空间点位稀疏、连续缺失或具有粗差的情况下都具有较高的插补精度。
关键词(KeyWords)： 缺失数据;插补;Kriged Kalman Filter;形变序列
基金项目(Foundation): 国家“973”项目(2013CB733303);; 中南大学教师研究基金项目(2014JSJJ003)
作者(Author): 刘宁,戴吾蛟,刘斌
DOI: 10.16251/j.cnki.1009-2307.2017.09.023
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