NDLI: A Novel Unscented Kalman Filter in Autonomous Optical Navigation

Content Provider	IEEE Xplore Digital Library
Author	Sui Shulin Yao Wenlong Sun Lihong Yuan Jian
Copyright Year	2007
Description	Author affiliation: Qingdao Univ. of Sci. & Technol., Qingdao (Sui Shulin; Yao Wenlong; Sun Lihong; Yuan Jian)
Abstract	Through much research on unscented Kalman filter based on scaled and square-root algorithm in autonomous navigation, it is known that these algorithms take so much time on calculation. So an improved unscented Kalman filter algorithm is proposed in the paper for autonomous navigation to solve the non-real-time difficulty. Simple scheme is adopted to predigest the choose procedure of sigma-points and weights, which reduces a mass of complex operations. From both theory and practical simulation, it is shown that much mass of calculation is reduced when the dimension of state matrix is large, and not leads to bad filtering performance.
Starting Page	462
Ending Page	466
File Size	733828
Page Count	5
File Format	PDF
ISBN	9787811240559
DOI	10.1109/CHICC.2006.4346767
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-07-26
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Optical filters Nonlinear equations Navigation Filtering Gaussian distribution Extraterrestrial measurements Covariance matrix Noise measurement Optical control UKF Autonomous optical navigation SR-UKF State estimation
Content Type	Text
Resource Type	Article

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A Novel Unscented Kalman Filter in Autonomous Optical Navigation