An Efficient and Robust Singular Value Method for Star Pattern Recognition and Attitude Determination | Zendy

Jer-Nan Juang | Zendy; Hyeyoung Kim | Zendy; John L. Junkins | Zendy

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An Efficient and Robust Singular Value Method for Star Pattern Recognition and Attitude Determination

Author(s) -

Jer-Nan Juang,

Hyeyoung Kim,

John L. Junkins

Publication year - 2004

Publication title -

the journal of the astronautical sciences

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.698

H-Index - 46

eISSN - 2195-0571

pISSN - 0021-9142

DOI - 10.1007/bf03546429

Subject(s) - singular value decomposition , singular value , invariant (physics) , matrix (chemical analysis) , frame (networking) , transformation (genetics) , computer science , mathematics , pattern recognition (psychology) , process (computing) , value (mathematics) , artificial intelligence , algorithm , statistics , physics , eigenvalues and eigenvectors , quantum mechanics , telecommunications , biochemistry , materials science , chemistry , composite material , mathematical physics , gene , operating system

A new star pattern recognition method is developed using singular value decomposition of a measured unit column vector matrix in a measurement frame and the corresponding cataloged vector matrix in a reference frame. It is shown that singular values and right singular vectors are invariant with respect to coordinate transformation and robust under uncertainty. One advantage of singular value comparison is that a pairing process for individual measured and cataloged stars is not necessary, and the attitude estimation and pattern recognition process are not separated. An associated method for mission catalog design is introduced and simulation results are presented.

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