00000nam 2200000zi 4500 9.881300 CaOODSP 20240221113057 m o d f cr cn||||||||| 191029t20182018quca ob f000 0 eng d CaOODSP eng rda CaOODSP D68-10/083-2018E-PDF Gagnon, Eric, author. Data fusion architectures for orthogonal redundant inertial measurement units / Eric Gagnon, DRDC - Valcartier Research Centre ; Alexandre Vachon, Numérica Technologies Inc. ; Yanick Beaudoin, Université Laval. Quebec (Quebec) : Defence Research and Development Canada = Recherche et développement pour la défense Canada, 2018. ©2018 1 online resource (20 pages, 2 unnumbered pages) : colour illustrations. text txt rdacontent computer c rdamedia online resource cr rdacarrier External literature (P) ; DRDC-RDDC-2018-P083 "Can unclassified." "Sensors, MDPI, Sensors 2018, 18(6), 1910." "July 2018." Includes bibliographical references (pages 19-20). "This work looks at the exploitation of large numbers of orthogonal redundant inertial measurement units. Specifically, the paper analyses centralized and distributed architectures in the context of data fusion algorithms for those sensors. For both architectures, data fusion algorithms based on Kalman filter are developed. Some of those algorithms consider sensors location, whereas the others do not, but all estimate the sensors bias. A fault detection algorithm, based on residual analysis, is also proposed. Monte-Carlo simulations show better performance for the centralized architecture with an algorithm considering sensors location. Due to a better estimation of the sensors bias, the latter provides the most precise and accurate estimates and the best fault detection. However, it requires a much longer computational time. An analysis of the sensors bias correlation is also done. Based on the simulations, the biases correlation has a small effect on the attitude rate estimation, but a very significant one on the acceleration estimation"--Abstract. Defence R&D Canada. Defence R&D Canada. Valcartier Research Centre. External literature (P) (Defence R&D Canada) DRDC-RDDC-2018-P083. (CaOODSP)9.854437 PDF 1.84 MB https://publications.gc.ca/collections/collection_2019/rddc-drdc/D68-10-083-2018-eng.pdf