A dual adaptive unscented Kalman filter algorithm for SINS-based integrated navigation system

LYU Xu ¹MENG Ziyang ¹LI Chunyu ¹CAI Zhenyu ²HUANG Yi ³LI Xiaoyong ³YU Xingkai⁴

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作者信息

1. Department of Precision Instrument,Tsinghua University,Beijing 100084,China
2. College of Mechanical and Power Engineering,Three Gorges University,Yichang 443002,China
3. Unit 91001 of the PLA,Beijing 100161,China
4. School of Control and Computer Engineering,North China Electric Power University,Beijing 100096,China
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Abstract

In this study,the problem of measuring noise pollu-tion distribution by the intertial-based integrated navigation sys-tem is effectively suppressed.Based on nonlinear inertial naviga-tion error modeling,a nested dual Kalman filter framework struc-ture is developed.It consists of unscented Kalman filter(UKF)master filter and Kalman filter slave filter.This method uses non-linear UKF for integrated navigation state estimation.At the same time,the exact noise measurement covariance is esti-mated by the Kalman filter dependency filter.The algorithm based on dual adaptive UKF(Dual-AUKF)has high accuracy and robustness,especially in the case of measurement information interference.Finally,vehicle-mounted and ship-mounted inte-grated navigation tests are conducted.Compared with tradi-tional UKF and the Sage-Husa adaptive UKF(SH-AUKF),this method has comparable filtering accuracy and better filtering stability.The effectiveness of the proposed algorithm is verified.

Key words

Kalman filter/dual-adaptive/integrated navigation/unscented Kalman filter(UKF)/robust

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基金项目

中国博士后科学基金(2023M741882)

国家自然科学基金(6210322262273195)

出版年

2024

系统工程与电子技术(英文版)

中国航天科工防御技术研究院中国宇航学会中国系统工程学会中国系统仿真学会

系统工程与电子技术(英文版)

CSTPCD

影响因子：0.64

ISSN：1004-4132

参考文献量24

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