A New Robust Student's t Based SINS/GPS Integrated Navigation Method

In practical strap-down inertial navigation system (SINS) and global positioning system (GPS) based integrated navigation, heavy-tailed non-Gaussian process noise may be induced by the severe maneuver, and heavy-tailed non-Gaussian measurement noise may be induced by the multipath propagation of GPS...

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Bibliographic Details
Published in2018 International Conference on Control, Automation and Information Sciences (ICCAIS) pp. 285 - 290
Main Authors Jia, Guangle, Zhang, Yonggang, Huang, Yulong, Bai, Mingming, Wang, Guoqing
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.10.2018
Subjects
Accelerometers
Automation
Covariance matrices
Global Positioning System
integrated navigation
Kalman filter
Kalman filters
Noise measurement
Strap-down inertial navigation system
Studen-t's t distribution
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Summary:In practical strap-down inertial navigation system (SINS) and global positioning system (GPS) based integrated navigation, heavy-tailed non-Gaussian process noise may be induced by the severe maneuver, and heavy-tailed non-Gaussian measurement noise may be induced by the multipath propagation of GPS signal. The performance of traditional Kalman filter based SINS/GPS integrated navigation method may degrade for such heavy-tailed non-Gaussian noises. To solve this problem, a new robust Student's t based SINS/GPS integrated navigation method is proposed, in which a new robust Student's t-based Kalman filter is employed to integrate SINS and GPS. Simulation results illustrate that the proposed integration method has higher navigation accuracy and better robustness to resist the heavy-tailed non-Gaussian noises as compared with traditional SINS/GPS integrated navigation method.
ISSN:2475-7896
DOI:10.1109/ICCAIS.2018.8570693