舰船电子工程2025，Vol.45Issue(3)：144-147,4.DOI:10.3969/j.issn.1672-9730.2025.03.029
一种基于Huber法改进的Sage-Husa自适应算法
A Sage-Husa Adaptive Algorithm Improved by Huber Method
摘要
Abstract
Because GNSS and INS have strong complementary performance,in order to obtain the best navigation effect,the design of integrated navigation usually uses Kalman filter to process various data.When measurement anomaly occurs,it cannot solve the problems of filter divergence and real-time estimation of state measurement noise matrix of Kalman filter and Sage-Husa adaptive filter.Aiming at the above problems,an improved adaptive filter is proposed,which discriminates the innovation in real time when detecting measurement anomaly,filters the available measurement information,reconstructs the observation equation of adaptive filter by improved Huber algorithm,and then optimizes the state estimation mean square error matrix,effectively solving the problems of measurement anomaly and filter divergence in integrated navigation.Simulation proves that compared with Sage-Hu-sa adaptive filtering algorithm,the improved adaptive filtering improves the stability and reliability of the above algorithm and im-proves the performance of integrated navigation system.关键词
组合导航/Huber法/自适应滤波/鲁棒性Key words
integrated navigation/Huber method/adaptive filtering/robustness分类
信息技术与安全科学引用本文复制引用
高帅,梁凯..一种基于Huber法改进的Sage-Husa自适应算法[J].舰船电子工程,2025,45(3):144-147,4.
