文章基本信息

标题：Two Modified Unscented Kalman Filter and Acceleration Information in Unmanned Surface Vehicle Estimation
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作者：Yulong Ma
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2015
卷号：48
期号：28
页码：1450-1455
DOI：10.1016/j.ifacol.2015.12.337
语种：English
出版社：Elsevier
摘要：AbstractThe stability problem is one of the existing problems of unscented Kalman filter (UKF), which due to the nonlinearity and complexity of system. The precision will be decreased or even UKF will be halted when the algorithm can't ensure the state covariance to be positive semidefinite. Based on decomposition of state covariance, the paper first reviews two modified UKFs which can enhance the state covariance to be positive semidefinite, then describes a method which combines the modified UKFs with acceleration measurement together to unmanned surface vehicle (USV) state estimation which main advantage lies in binding UKF with acceleration to simplify the system estimation model, so that it becomes an online estimation algorithm with higher precision and lower calculation complexity.
关键词：Keywordsdiagonal similar decompositionacceleration, singular value decompositionpositive semidefinite