基于可变遗忘因子的渐消记忆变分贝叶斯自适应滤波算法  

Fading memory variational Bayesian adaptive filter based on variable attenuating factor

作　　者：靳凯迪 柴洪洲[1] 宿楚涵 惠俊 白腾飞 JIN Kaidi;CHAI Hongzhou;SU Chuhan;HUI Jun;BAI Tengfei(Institute of Geospatial Information,Information Engineering University,Zhengzhou 450001,China)

机构地区：[1]信息工程大学地理空间信息学院,郑州450001

出　　处：《北京航空航天大学学报》2023年第11期2989-2999,共11页Journal of Beijing University of Aeronautics and Astronautics

基　　金：国家自然科学基金(42074014)。

摘　　要：针对全球卫星导航系统/捷联惯性导航系统(GNSS/SINS)组合导航中GNSS信号易受干扰,造成量测噪声突变的问题,提出一种基于可变遗忘因子的渐消记忆变分贝叶斯自适应Kalman滤波(VBAKF)算法。针对自适应滤波中突变噪声难以准确探测,构建基于初值的噪声突变检验准则;为解决自适应滤波估计突变噪声的拖尾现象,将变分贝叶斯自适应滤波的超参数传递结构转化为协方差阵修正结构,通过构造可变遗忘因子函数动态调节自适应滤波中的遗忘因子。仿真和实测数据表明:所提算法可在GNSS/SINS噪声突变时快速估计量测噪声,提高组合导航精度。The measurement noise for global navigation satellite system/strapdown inertial navigation system(GNSS/SINS)suffers from abrupt changes due to the easy interference of GNSS signals.In this paper,a novel fading memory variational Bayesian adaptive Kalman filter(VBAKF)with variable attenuating factors is proposed to estimate the abrupt measurement noise for GNSS/SINS system.The Chi-square detection method is reconstructed by initial standard deviation of GNSS noise.The hyperparameter transfer structure of VBAKF is then transformed into the error covariance matrix correction structure,and a novel variable memorial factor function is established to dynamically adjust the attenuating factor in VBAKF.Experimental results show that the proposed algorithm can adaptively estimate the abrupt measurement noise,and that the position accuracy of GNSS/SINS is improved in the presence of abrupt noise.

关 键 词：变分贝叶斯 自适应滤波 遗忘因子 渐消记忆 组合导航 

分 类 号：V249.3[航空宇航科学与技术—飞行器设计] P227.9[天文地球—大地测量学与测量工程]