改进的5TH-CKF及其在初始对准中的应用

Wei Wang, Xiyuan Chen
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引用次数: 1

摘要

大不对准角的初始对准模型是强非线性的,这就要求非线性滤波的精度必须很高。为了充分利用这一创新,本文对五阶Cubature Kalman滤波器(CKF)的误差协方差矩阵进行了自适应缩放。比例因子可以通过计算当前实际创新与过滤后创新的矩阵秩之比得到。大偏差的仿真实验表明,改进算法比传统算法具有更高的精度和更短的收敛时间。
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Improved 5TH-CKF and its application in initial alignment
The initial alignment model of large misalignment angle is strong nonlinear, which means that the precision of nonlinear filter must be high. In order to make full use of the innovation, the error covariance matrix of fifth-order Cubature Kalman Filter (CKF) is scaled adaptively in this paper. The scaling factor can be obtained by calculating the ratio between matrix ranks of the current actual innovation and filtered innovation. The simulation experiments of large misalignment show that the improved algorithm has the higher accuracy and shorter convergence time than the traditional algorithm.
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