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针对单一传感器测量精度低、可靠性差和不能判断测量点间情况等局限性,提出了一种基于Kalman滤波和相关分析的分段多传感器测量方法。该方法很好地结合了Kalman递归滤波数据融合和相关分析的优势,避免了Kalman滤波在数学模型和噪声统计特性方面的缺点和局限性,提高了数据测量的精度和可靠性,并可以对测量点间异常信息进行判断。从开发的动态载荷轨道特征参数测量装置的数据处理可以看出,这种算法是有效的,效果也是十分明显的。
Aiming at the limitations of single sensor, such as low accuracy, poor reliability and inability to judge the location of measurement points, a piecewise multi-sensor measurement method based on Kalman filter and correlation analysis is proposed. This method well combines the advantages of Kalman recursive filtering data fusion and correlation analysis, avoids the disadvantages and limitations of Kalman filtering in the aspects of mathematical model and noise statistics, improves the accuracy and reliability of data measurement, Abnormal information between points to judge. It can be seen from the data processing of the developed dynamic load orbit feature parameter measuring device that the algorithm is effective and the effect is very obvious.