基于小波变换的自适应Kalman滤波算法研究  

Self-Adaptive Kalman Filter Algorithm Research Based on Wavelet Transform

作　　者：李田科[1] 刘辉 王亮[3] 于仕财[4] 

机构地区：[1]中国人民解放军91980部队 [2]北京自动化控制设备研究所 [3]海军航空工程学院研究生管理大队 [4]海军航空工程学院电子信息工程系

出　　处：《兵工自动化》2013年第1期32-35,共4页Ordnance Industry Automation

基　　金：国家自然科学基金(61179017)

摘　　要：针对组合导航系统中Kalman滤波在实际工程应用中的不足,以惯性/卫星组合导航系统为背景,提出小波变换技术对量测噪声方差阵进行直接调控的滤波算法。介绍Kalman滤波原理,根据小波变换在时域和频域都有良好的局部化性质,检测量测噪声的变化,实时调整自适应因子,间接改变Kalman滤波器的当前观测和过去信息的比例关系。仿真结果表明:该算法对噪声干扰有较强的自适应性,能有效抑制滤波发散,提高系统的精度和鲁棒性。According to the deficiency of Kalman filtering of integrated navigation system in engineering application, based on the background of INS/BD integrated navigation, this paper puts forward the filtering algorithm which direct control noise covariance matrix with wavelet transformation technique. It introduced the theory of Kalman filtering, this method has good part characteristics in both time domain and frequency domain of wavelet transform and it adjusts the adaptive gene directly according to the variety and variance of new-information, and at the same time, it adjusts the proportion of current observation and past message indirectly. Simulation results indicates that the algorithm has good self-adaptive Kalman filtering bases on wavelet transform, it can adapt to the disturbance of system and noise model, restrain filtering failure, improve the system precision and robustness.

关 键 词：组合导航 小波变换 噪声检测 自适应Kalman滤波 

分 类 号：TJ765.4[兵器科学与技术—武器系统与运用工程]