| 基于抗差卡尔曼滤波的GM(1,1)模型在变形预计中的应用 |
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| 引用本文： | 冉典.基于抗差卡尔曼滤波的GM(1,1)模型在变形预计中的应用[J].测绘与空间地理信息,2014(8):84-86. |
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| 作者姓名： | 冉典 |
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| 作者单位： | 安徽理工大学测绘学院,安徽淮南232001 |
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| 基金项目： | 安徽高校省级自然科学研究重点项目（KJ2010A104）资助 |
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| 摘 要： | 针对传统灰色模型建模过程中易受观测数据随机噪声干扰的影响,利用抗差卡尔曼滤波理论能够有效地估计含有噪声的观测值的优点,构建了基于抗差卡尔曼滤波的GM(1,1)模型。结合实例,验证了该模型在一定程度上可以提高变形监测预测精度,更好地反映观测对象的变形趋势。
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| 关 键 词： | 抗差估计 卡尔曼滤波 GM( )模型 变形预计 |
Application of Gray Model in Deformation Monitoring Based on Robust Estimate of Kalman Filter Method |
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| RAN Dian.Application of Gray Model in Deformation Monitoring Based on Robust Estimate of Kalman Filter Method[J].Geomatics & Spatial Information Technology,2014(8):84-86. |
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| Authors: | RAN Dian |
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| Institution: | RAN Dian ( College of Anhui University of Surveying and Mapping, Huainan 232001, China) |
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| Abstract: | In this paper , the problem which traditional gray model is vulnerable to be influenced by random disturbance of observation data during the model is built , was solved by building the GM （1,1） model based on robust estimate of Kalman filter , taking advan-tage of robust estimate of Kalman filter can effectively estimate observation value which contains random noise .According to the related case, proved that the GM（1,1） model based on robust estimate of Kalman filter could enhance the forecast precision of deformation monitoring and reflect the deformation tendency better . |
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| Keywords: | robust estimation Kalman filter GM（ 1 1 ） deformation forecast |
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