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

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Abstract

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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Author information

Authors and Affiliations

  1. Structural Dynamics, NASA Langley Research Center, Hampton, VA, 23681, USA

    Jer-Nan Juang (Principal Scientist)

  2. Department of Aerospace and Ocean Engineering, Virginia Polytechnic Institute and State University, Blacksburg, VA, 24061, USA

    Hye-Young Kim (Post-Doctoral Research Assistant)

  3. Department of Aerospace Engineering, Texas A&M University, TX, 77843, USA

    John L. Junkins (Distinguished Professor, holder of George J. Eppright Chair, Fellow AAS)

Authors
  1. Jer-Nan Juang
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  2. Hye-Young Kim
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  3. John L. Junkins
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Juang, JN., Kim, HY. & Junkins, J.L. An Efficient and Robust Singular Value Method for Star Pattern Recognition and Attitude Determination. J of Astronaut Sci 52, 211–220 (2004). https://doi.org/10.1007/BF03546429

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  • DOI: https://doi.org/10.1007/BF03546429

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