大地测量与地球动力学2024，Vol.44Issue(8)：787-792,6.DOI:10.14075/j.jgg.2023.11.144
基于最大熵准则的GNSS/SINS组合导航滤波算法
GNSS/SINS Integrated Navigation Filtering Algorithm Based on Maximum Entropy Criterion
摘要
Abstract
The traditional Kalman filter(KF)of GNSS/SINS integrated navigation system is optimal under the minimum mean square error(MMSE)criterion and under the Gaussian hypothesis.Howev-er,when the measurement noise is disturbed by heavy tail pulse noise,the filtering performance of KF is seriously degraded.To solve this problem,we propose a maximum entropy Kalman filter(MCKF)for integrated navigation system.First,we establish the state equation and measurement equation of MCKF.Then,using the principle of maximum entropy,we establish a Kalman filter based on the maximum entropy criterion,and design its filter iteration flow.Finally,we simulate the GNSS/SINS integrated navigation system in the environment of mixed Gaussian noise and heavy tail pulse noise,respectively.The simulation results show that KF performs better than MCKF under mixed Gaussian noise interference,MCKF has better filtering performance than KF under the interference of heavy tail pulse noise,and MCKF is equivalent to KF when the kernel bandwidth tends to infinity.关键词
组合导航/最大熵准则/核带宽/迭代阈值/卡尔曼滤波器Key words
integrated navigation/maximum entropy criterion/kernel bandwidth/iterative threshold/Kalman filter分类
天文与地球科学引用本文复制引用
林雪原,潘新龙,王玮..基于最大熵准则的GNSS/SINS组合导航滤波算法[J].大地测量与地球动力学,2024,44(8):787-792,6.基金项目
国家自然科学基金(62076249) （62076249）
山东省自然科学基金(ZR2020MF154). National Natural Science Foundation of China,No.62076249 （ZR2020MF154）
Natural Science Foundation of Shandong Province,No.ZR2020MF154. （）
