This study divides learning motivation into six vector quantities, and factor of influence relation to study divide it into three degree, 11 different factors.

本研究将学习动机分为六个向量，而影响学习因素把它分为三个向度，十一种不同的因素。

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Gauss-Newton error minimization is used to transform six-dimentional reference vector to quaternion as a part of observations for EKF, which significantly reduces the computational requirement.

用高斯-牛顿误差最小法将六维观测量转化为四元数，作为观测量的一部分，显著减少了直接使用EKF的计算量。

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Will be extracted after the six feature vector for normalized.

之后将提取出来的六个特征向量进行归一化处理。

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