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Research on Kalman Filtering Algorithm for Deformation Information Series of Similar Single-Difference Model

机译:相似单差模型变形信息序列的卡尔曼滤波算法研究

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摘要

Using similar single-difference methodology(SSDM) to solve the deformation values of the monitoring points, there is unstability of the deformation information series, at sometimes. In order to overcome this shortcoming, Kalman filtering algorithm for this series is established, and its correctness and validity are verified with the test data obtained on the movable platform in plane. The results show that Kalman filtering can improve the correctness, reliability and stability of the deformation information series.
机译:使用相似的单差方法(SSDM)求解监测点的变形值,有时会导致变形信息序列不稳定。为了克服这一缺点,建立了该系列的卡尔曼滤波算法,并通过在可移动平台上获得的测试数据验证了其正确性和有效性。结果表明,卡尔曼滤波可以提高变形信息序列的正确性,可靠性和稳定性。

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