A novel optimal data fusion algorithm and its application for the integrated navigation system of missile

作     者：Di LIU Xiyuan CHEN Xiao LIU Di LIU;Xiyuan CHEN;Xiao LIU

作者机构：Key Laboratory of Micro-Inertial Instrument and Advanced Navigation Technology Ministry of EducationSchool of Instrument Science and EngineeringSoutheast UniversityNanjing 210096China School of Electronic and Information Engineering(Department of Physics)Qilu University of TechnologyJinan 250353China 

出 版 物：《Chinese Journal of Aeronautics》 (中国航空学报（英文版）)

年 卷 期：2022年第35卷第5期

页      面：53-68页

核心收录：

学科分类：1101[军事学-军事思想及军事历史] 08[工学] 081105[工学-导航、制导与控制] 080401[工学-精密仪器及机械] 0804[工学-仪器科学与技术] 0714[理学-统计学（可授理学、经济学学位）] 0825[工学-航空宇航科学与技术] 0811[工学-控制科学与工程] 0701[理学-数学] 

基　　金：supported by the National Natural Science Foundation of China(Nos.61873064 and 51375087) the Transformation Program of Science and Technology Achievements of Jiangsu Province(No.BA2016139) the Postgraduate Research&Practice Innovation Program of Jiangsu Province(No.KYCX18_0073) 

主　　题：Data fusion High-degree cubature Kalman filter Integrated navigation Non-Gaussian noise Process-modeling error 

摘      要：For Inertial Navigation System(INS)/Celestial Navigation System(CNS)/Global Navigation Satellite System(GNSS)integrated navigation system of the missile,the performance of data fusion algorithms based on the Cubature Kalman Filter(CKF)is seriously degraded when there are non-Gaussian noise and process-modeling errors in the system ***,a novel method is proposed,which is called Optimal Data Fusion algorithm based on the Adaptive Fading maximum Correntropy generalized high-degree CKF(AFCCKF-ODF).First,the Adaptive Fading maximum Correntropy generalized high-degree CKF(AFCCKF)is proposed and used as the local filter for the INS/GNSS and INS/CNS subsystems to improve the robustness of local state ***,the local state estimation is fused based on the minimum variance principle and highdegree cubature criterion to get the globally optimal ***,the experimental results verify that the proposed algorithm can significantly improve the robustness of the missile-borne INS/CNS/GNSS integrated navigation system to non-Gaussian noise and process modeling error and obtain the global optimal navigation information.