空天预警研究学报2026，Vol.40Issue(4)：247-252,6.DOI:10.3969/j.issn.2097-180X.2026.04.003
一种自适应鲁棒的Sage-Husa无迹Kalman滤波算法
An adaptive robust Sage-Husa unscented Kalman filter algorithm
摘要
Abstract
Aimed at the problem of the limited accuracy of unscented Kalman filter(UKF)under inaccurate initial values and model mismatch,and the divergence of the Sage-Husa unscented Kalman filter(SH-UKF)when the state and measurement noises are estimated jointly,an adaptive robust SH-UKF(ARSH-UKF)algorithm is proposed,which incorporates four improvements:adaptive forgetting factor,bounded multiple sub-factors,a hier-archical divergence criterion with primary and auxiliary coordination,and Huber robust weight based on the actu-al residual covariance.Simulations results show that under severely mismatched initial values,both the root mean square errors(RMSE)of the synthetic position and velocity of the ARSH-UKF algorithm have been reduced com-pared with the UKF and SH-UKF algorithms,and that when the initial value is close to the true one,the accuracy is comparable to that of the UKF and SH-UKF algorithms and the ARSH-UKF algorithm has both high accuracy and strong robustness.关键词
目标跟踪/Sage-Husa无迹Kalman滤波/自适应鲁棒Key words
target tracking/Sage-Husa unscented Kalman filter(Sage-Husa UKF)/adaptive robustness分类
信息技术与安全科学引用本文复制引用
宋亚伟,叶泽浩,韩伟,颜建..一种自适应鲁棒的Sage-Husa无迹Kalman滤波算法[J].空天预警研究学报,2026,40(4):247-252,6.
