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Open AccessArticle
Adaptive Cubature Kalman Filter for Inertial/Geomagnetic Integrated Navigation System Based on Long Short-Term Memory Network
by
Tianhao Liu
Tianhao Liu 1,
Tianshang Zhao
Tianshang Zhao 2,
Huijun Zhao
Huijun Zhao 2
and
Chenguang Wang
Chenguang Wang 2,3,*
1
State Key Laboratory of Satellite Navigation System and Equipment Technology, The 54th Research Institute of CETC, Shijiazhuang 050081, China
2
State Key Laboratory of Dynamic Measurement Technology, North University of China, Taiyuan 030051, China
3
School of Information and Communication Engineering, North University of China, Taiyuan 030051, China
*
Author to whom correspondence should be addressed.
Appl. Sci. 2024, 14(13), 5905; https://doi.org/10.3390/app14135905 (registering DOI)
Submission received: 10 May 2024
/
Revised: 1 July 2024
/
Accepted: 1 July 2024
/
Published: 5 July 2024
Abstract
Inertial navigation systems experience error accumulation over time, leading to the use of integrated navigation as a classical solution to mitigate inertial drift. This provides a novel approach to navigation and positioning by using the combined advantages of inertial and geomagnetic navigation systems. However, inertial/geomagnetic navigation is affected by significant magnetic interference in practical scenarios, resulting in reduced navigation accuracy. This research introduces a new neural network-assisted integrated inertial–geomagnetic navigation method (IM-NN), and utilizes the adaptive cubature Kalman filter to integrate attitude information from geomagnetism and inertial sensors. A model was created utilizing a Long Short-Term Memory Network (LSTM) to represent the relationship between specific force, angular velocity, and integrated navigation attitude information. The dynamics were estimated based on current and previous Inertial Measurement Unit (IMU) data using IM-NN. This study demonstrated that the method effectively corrected inertial accumulation errors and mitigated geomagnetic disruption, resulting in a more accurate and dependable navigation solution in environments with geomagnetic rejection compared to conventional single inertial navigation methods.
Share and Cite
MDPI and ACS Style
Liu, T.; Zhao, T.; Zhao, H.; Wang, C.
Adaptive Cubature Kalman Filter for Inertial/Geomagnetic Integrated Navigation System Based on Long Short-Term Memory Network. Appl. Sci. 2024, 14, 5905.
https://doi.org/10.3390/app14135905
AMA Style
Liu T, Zhao T, Zhao H, Wang C.
Adaptive Cubature Kalman Filter for Inertial/Geomagnetic Integrated Navigation System Based on Long Short-Term Memory Network. Applied Sciences. 2024; 14(13):5905.
https://doi.org/10.3390/app14135905
Chicago/Turabian Style
Liu, Tianhao, Tianshang Zhao, Huijun Zhao, and Chenguang Wang.
2024. "Adaptive Cubature Kalman Filter for Inertial/Geomagnetic Integrated Navigation System Based on Long Short-Term Memory Network" Applied Sciences 14, no. 13: 5905.
https://doi.org/10.3390/app14135905
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