Research on Adaptively Robust Kalman Filtering for Dynamic Deformation Monitoring Applications

伍锡锈; 戴吾蛟; 罗飞雪

doi:10.13409/j.cnki.jdpme.2011.01.001

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Research on Adaptively Robust Kalman Filtering for Dynamic Deformation Monitoring Applications

更新时间：2025-12-11

- Research on Adaptively Robust Kalman Filtering for Dynamic Deformation Monitoring Applications
- Vol. 31, Issue 1, Pages: 102-106(2011)
- 作者机构：
- 作者简介：
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- DOI：10.13409/j.cnki.jdpme.2011.01.001
  CLC： 227
- Published：2011
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[1]伍锡锈,戴吾蛟,罗飞雪.抗差自适应Kalman滤波在动态变形监测中的应用研究[J].防灾减灾工程学报,2011,31(01):102-106.

伍锡锈, 戴吾蛟, 罗飞雪. Research on Adaptively Robust Kalman Filtering for Dynamic Deformation Monitoring Applications[J]. 2011, 31(1): 102-106.
[1]伍锡锈,戴吾蛟,罗飞雪.抗差自适应Kalman滤波在动态变形监测中的应用研究[J].防灾减灾工程学报,2011,31(01):102-106. DOI： 10.13409/j.cnki.jdpme.2011.01.001.

伍锡锈, 戴吾蛟, 罗飞雪. Research on Adaptively Robust Kalman Filtering for Dynamic Deformation Monitoring Applications[J]. 2011, 31(1): 102-106. DOI： 10.13409/j.cnki.jdpme.2011.01.001.

摘要

抗差自适应Kalman滤波算法中

抗差等价权矩阵和自适应因子的计算

要求观测信息具有多余观测量且准确可靠

但在动态变形监测应用中

通常滤波观测值仅为三维坐标且存在较强噪声和粗差的影响。为此

先对该算法中的自适应因子和抗差等价权矩阵的计算进行研究和改进

然后计算了某高速公路边坡的GPS动态监测数据。结果表明

抗差自适应Kalman滤波能够有效地抵制动态变形监测中观测值异常的影响。

Abstract

In the algorithm of adaptively robust Kalman filtering

the calculations of equivalent weight matrixes and adaptive factors are based on abundant

accurate and reliable observation information.But in the application of dynamic deformation monitoring

the monitoring point’s measurement values are simply three-dimensional coordinates

and the impact of noise and outliers is also serious in the observation.In this paper

the algorithms of equivalent weight matrixes and adaptive factors are researched and improved

and the adaptively robust filtering has been used in the GPS dynamic deformation monitoring data processing of a slope.Filtering results show that:adaptively robust Kalman filtering can significantly weaken the influence of measurement outliers in dynamic deformation monitoring.

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references

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