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Data Fusion-Based Descriptor Approach for Attitude Estimation under accelerated maneuvers

Aida Makni 1 Alain Kibangou 1 Hassen Fourati 1
1 NECS-POST - Systèmes Commandés en Réseau
Inria Grenoble - Rhône-Alpes, GIPSA-DA - Département Automatique
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 developped and its performance is evaluated through simulations and experimental tests in pedestrian navigation.
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Submitted on : Tuesday, February 26, 2019 - 3:24:56 PM
Last modification on : Wednesday, November 3, 2021 - 9:34:18 AM
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Aida Makni, Alain Kibangou, Hassen Fourati. Data Fusion-Based Descriptor Approach for Attitude Estimation under accelerated maneuvers. Asian Journal of Control, Asian Control Association (ACA) and Chinese Automatic Control Society (CACS) 2019, 21 (4), pp.1433-1442. ⟨10.1002/asjc.2084⟩. ⟨hal-01982463⟩



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