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Data fusion‐based descriptor approach for attitude estimation under accelerated maneuvers
Author(s) -
Makni Aida,
Kibangou Alain Y.,
Fourati Hassen
Publication year - 2019
Publication title -
asian journal of control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.769
H-Index - 53
eISSN - 1934-6093
pISSN - 1561-8625
DOI - 10.1002/asjc.2084
Subject(s) - quaternion , gyroscope , accelerometer , control theory (sociology) , acceleration , process (computing) , kalman filter , filter (signal processing) , computer science , sensor fusion , computer vision , engineering , artificial intelligence , control engineering , simulation , mathematics , aerospace engineering , physics , geometry , control (management) , classical mechanics , operating system
Abstract This paper proposes the design of an attitude estimation algorithm for a rigid body subject to accelerated maneuvers. Unlike the current literature where the process model is usually driven by triaxial gyroscope measurements, we investigate a new formulation of the state‐space model where the process model is given by triaxial accelerometer measurements. The observation model is given by triaxial gyroscope and magnetometer measurements. The proposed model is written as a descriptor system and takes the external acceleration sensed by the accelerometer into account. Based on this model, a Quaternion Descriptor Filter (QDF) is developed and its performance is evaluated through simulations and experimental tests in pedestrian navigation.