Analytical Algorithm for Attitude and Heading Estimation Aided by Maneuver Classification
https://doi.org/10.17285/0869-7035.2018.27.1.072-092
Abstract
This paper presents a modified adaptive analytical algorithm for attitude and heading estimation. The analytical algorithm is based on the fusion of IMU, magnetometers and the velocity from GPS. The kinematic Euler angles are first calculated based on the output of the rate gyros, then the calculated angle errors are compensated using the output of each of the accelerometers, magnetometers, and the velocity taken from a GPS receiver, without the need to model the systematic and random errors of the used sensors; Kalman filter is not used. The algorithm will be adaptive based on the maneuver classification, the filters' parameters will be tuned depending on the maneuver intensity: No, Low, or High maneuver. The main contribution of this paper is to build an attitude and heading estimation algorithm (analytical algorithm) without using Kalman filter; this algorithm will be made adaptive based on the maneuver classification algorithm which was developed using logistic regression technique based on IMU output. Computer simulation with simulated and real flight data showed that the adaptive analytical algorithm has acceptable results compared to EKF.
About the Authors
Al Mansour
Department of Electronic & Mechanical Systems, Higher Institute for Applied Sciences and Technology (HIAST)
Russian Federation
Russian Federation
M. Chouaib
(Department of Electronic & Mechanical Systems, Higher Institute for Applied Sciences and Technology (HIAST)
Russian Federation
Russian Federation
A. Jafar
Department of Electronic & Mechanical Systems, Higher Institute for Applied Sciences and Technology (HIAST)
Russian Federation
Russian Federation
A. A. Potapov,
Kazan National Research Technical University named after A. N. Tupolev – KAI
Russian Federation
Russian Federation
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Review
For citations:
Mansour A., Chouaib M., Jafar A., Potapov, A.A. Analytical Algorithm for Attitude and Heading Estimation Aided by Maneuver Classification. Giroskopiya i Navigatsiya. 2019;27(1):72-92. (In Russ.) https://doi.org/10.17285/0869-7035.2018.27.1.072-092
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