量测数据自校准融合方法

提出了一种量测数据自校准融合方法,给出量测数据系统误差(未知输入)的自识别自校准公式与计算步骤,能够自动对量测数据中事先无法校准的系统误差进行识别、估计、补偿和修正,从而减小系统误差的影响。建立多传感器的数据融合公式与计算步骤,进而降低偶然误差的影响。分别对线性系统和非线性系统进行了详细讨论,并进行了大量实例计算和仿真模拟验证。从两个算例计算结果可以看出:该方法的相对误差至少要比传统方法减小45%,且计算简单,便于工程应用。 

Measurement data self-calibration fusion method

A measurement data self-calibration fusion method was proposed. Self-recognition self-calibration formulas and computational procedures of the systematic error (unknown input) in measurement data were given, enabling to automatically identify, estimate, compensate and correct the systematic error, so as to reduce its influence. Formulas and computational procedures of multi-sensor data fusion were established to further reduce the influence of random errors. The linear system and the non-linear system were discussed in detail respectively, and a large number of examplifications and simulations were carried out. It can be seen in two examples that the relative error of the proposed method is at least 45% less than that of the traditional method, and the calculation is simple, and well-suited for engineering applications.