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A Kalman Filter-Based Algorithm for Measuring the Parameters of Moving Objects

机译:基于卡尔曼滤波器的运动物体参数测量算法

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One of the most complex problems in measuring equipment is related to the provision of the required dynamic accuracy of measuring systems determining the parameters of moving objects. The present paper views an algorithm for improving the dynamic accuracy of such measuring systems. It is based on the Kalman method. The algorithm aims to eliminate the influence of a number of interference sources, each of which is of secondary significance. However, their total effect can cause considerable distortion of the measurement signal. The algorithm model is designed for gyro-free measuring systems. It is based on one of the most widely used elements in the dynamic systems, namely the physical pendulum, due to which measuring systems of high dynamic accuracy and low cost can be developed. The presented experimental results confirm the effectiveness of the proposed algorithm with respect to the dynamic accuracy of measuring systems of this type.
机译:测量设备中最复杂的问题之一与提供确定运动物体参数的测量系统所需的动态精度有关。本文介绍了一种用于提高此类测量系统动态精度的算法。它基于卡尔曼方法。该算法旨在消除多个干扰源的影响,每个干扰源具有次要意义。但是,它们的总作用会引起测量信号的明显失真。该算法模型是为无陀螺仪测量系统设计的。它基于动态系统中使用最广泛的元素之一,即物理摆,因此可以开发出高动态精度和低成本的测量系统。提出的实验结果证实了该算法相对于这种类型的测量系统的动态精度的有效性。

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