This paper proposes high-degree cubature Kalman filter for nonlinear systems with missing measurements. We derive out the explicit formulas for the prediction and update in the filtering. To fulfill the numerical computation, especially the numerical integrals, of these formulas, the fifth-degree spherical-radial cubature rule is adopted to give a high-degree cubature Kalman filtering algorithm. Through numerical example, it is shown that the fifth-degree cubature Kalman filter has better precision and stability than the extended Kalman filter, the unscented Kalman filter, and the fifth-degree unscented Kalman filter.

中文翻译：

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用于缺少测量的非线性状态估计的高阶容积卡尔曼滤波器

本文针对缺少测量的非线性系统提出了高度容积卡尔曼滤波器。我们推导出过滤中预测和更新的显式公式。为了完成这些公式的数值计算，特别是数值积分，采用五次球面-径向容积规则，给出了一个高度容积卡尔曼滤波算法。通过数值算例表明，五度容积卡尔曼滤波器比扩展卡尔曼滤波器、无迹卡尔曼滤波器和五度无迹卡尔曼滤波器具有更好的精度和稳定性。