Low-Complexity Fusion Estimation Algorithms for Multisensor Dynamic Systems

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概要

• 論文の詳細を見る

• This paper focuses on fusion estimation algorithms weighted by matrices and scalars, and relationship between them is considered. We present new algorithms that address the computation of matrix weights arising from multidimensional estimation problems. The first algorithm is based on the Cholesky factorization of a cross-covariance block-matrix. This algorithm is equivalent to the standard composite fusion estimation algorithm however it is low-complexity. The second fusion algorithm is based on an approximation scheme which uses special steady-state approximation for local cross-covariances. Such approximation is useful for computing matrix weights in real-time. Subsequent analysis of the proposed fusion algorithms is presented, in which examples demonstrate the low-computational complexity of the new fusion estimation algorithms.

• （社）電子情報通信学会の論文
• 2009-11-01

著者

• SHIN Vladimir

  School of Information and Mechatronics, Gwangju Institute of Science and Technology

• Shin Vladimir

  School Of Information And Mechatronics Gwangju Institute Of Science And Technology

• LEE Seokhyoung

  School of Information and Mechatronics, Gwangju Institute of Science and Technology

• Lee Seokhyoung

  School Of Information And Mechatronics Gwangju Institute Of Science And Technology

関連論文

• MAD Robust Fusion with Non-Gaussian Channel Noise
• Low-Complexity Fusion Estimation Algorithms for Multisensor Dynamic Systems

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