【摘要】 为了提高飞行姿态的测量精度,工程上一般使用滤波算法对测量数据进行滤波降噪处理,由于建立在线性递推估计框架之上的卡尔曼滤波算法在处理非线性问题时精度不佳,且无迹卡尔曼滤波算法无法保证正交且解算量大,于是容积卡尔曼滤波算法便应运而生了。由于采用了容积采样准则,其解算量仍然较大,为此本文基于乔列斯基分解原理改进了容积卡尔曼滤波的逆矩阵运算方法,使解算精度保持不变的同时能够大幅降低解算时间,为工程应用提供了一种参考。更多还原

【Abstract】 To improve the measuring precision of flight attitude,Kalman filtering algorithm is used widely to smooth the noise in engineering application.Kalman filter performance built on the linear estimation frame is not good enough to be used in nonlinear system and its improved filter algorithm,unscented Kalman filter whose orthogonal can’t be ensured has a too huge computation burden to be used widely in aircraft,so cubature Kalman filter is raised.Because the computation burden is still huge when cubature Kalman filter used cubature sample principle,a new method is raised in this paper to solve this problem.Cholesky decomposition was introduced into the inverse matrix calculating course,so the total computation burden is reduced significantly and the calculating accuracy isn’t impacted,which can be served as an engineering reference.更多还原