摘要
针对量测噪声中可能出现成片连续野值的情况,利用Bayes定理,得到了判别成片连续野值的后验概率公式,并提出了对上述野值不敏感的鲁棒Kalman滤波。仿真实例表明:较之一般的Kalman滤波,文中提出的方法能够较为满意地处理量测噪声中具有成片连续野值的恶劣情形。
Owing to the fact that continuous outliers may occur in noise measurement, a posteriori probability formula used to discriminate continuous outliers, using Bayes theorem, is derived and the robust Kalman filtering insensitive to the above outliers is presented. To confirm effectiveness of the procedure mentioned above, the state estimation of free-falling body motion is demonstrated by simulation, which gives very satisfactory robustness to continuous outliers.
出处
《清华大学学报(自然科学版)》
EI
CAS
CSCD
北大核心
1994年第1期54-61,共8页
Journal of Tsinghua University(Science and Technology)
关键词
鲁棒性
野值剔除
卡尔漫滤波
Kalman filtering
robustness
outlier rejection
Bayes formula