基于区间正交小波变换的多尺度实时Kalman滤波器设计

Design of multi-scale real-time Kalman filtering based on interval orthogonal wavelet transform

针对导航系统中惯性元器件的降噪问题,设计一种基于区间正交小波变换的多尺度实时Kalman滤波算法。该算法利用区间正交小波变换抑制边界效应的能力及其滑动数据窗口内实时分解特性,建立动态系统的多尺度实时Kalman滤波框架。Allan方差分析结果表明:在陀螺信号滤波中,给定小波分解尺度,该算法在保持一定实时性的同时,可以取得较好的滤波效果,滤波后的噪声系数比标准Kalman滤波减少至少1个数量级。

To solve the practical problem of inertial components de-noising in INS,a multi-scale real-time Kalman filtering based on interval orthogonal wavelet transform was proposed.With the ability of the interval wavelet transform to restrain terrible edge effects and its real-time decomposition characteristics in a sliding data window,a multi-scale dynamic systems framework for real-time Kalman filter was established.The results show that under the condition of given wavelet decomposition scale,the algorithm,while maintaining a certain real-time,has a good performance,and variances of filter errors are reduced by at least one order of magnitude.