文章基本信息

标题：Quadrotor UAV state estimation based on High-Degree Cubature Kalman filter
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作者：Hamza Benzerrouk ; Alexander Nebylov ; Hassen Salhi 等
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2016
卷号：49
期号：17
页码：349-354
DOI：10.1016/j.ifacol.2016.09.060
语种：English
出版社：Elsevier
摘要：In this paper, on the basis of previous results solving INS/GNSS integration, Cubature Kalman Filter (CKF) and High Degree Cubature Kalman Filter with (GFIKF) are the references for the recent developed generalized Cubature rule based Kalman Filter (GCKF). High degree cubature rules are the kernel of the new solution for more accurate estimation with less computational complexity compared with the Gauss-Hermite Quadrature (GHQ). In this paper, state estimation of a UAV between previous and novel approaches. Instead of use particle filter as the reference filter, it is maintained that CKF is the best reference for all Gaussian approximate filters after Gauss-Hermite Kalman Filter GHKF which is not selected in this work because of its limited real-time implementation in high-dimensional state-spaces. GNSS (GPS+GLONASS) measurements are assumed available to provide heading measurement by the use of kinematic model and observe attitude angles delivered by the IMU. Gaussian approximation filters: SPKF with Cubature Kalman Filter (CKF) are compared with new high order CKF based on Spherical-radial cubature rules developed at the fifth order. Estimation accuracy of the high degree CKF is observed and discussed for different initialization parameters.
关键词：GNSSaccelerometersgyroscopesKalman filterUKFCDKFCKFGHKFHDCKF