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Spacecraft Attitude Estimation Using Adaptive Gaussian Sum Filter

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Abstract

This paper is concerned with improving the attitude estimation accuracy by implementing an adaptive Gaussian sum filter where the a posteriori density function is approximated by a sum of Gaussian density functions. Compared to the traditional Gaussian sum filter, this adaptive approach utilizes the Fokker-Planck-Kolmogorov residual minimization to update the weights associated with different components of the Gaussian mixture model. Updating the weights provides an accurate approximation of the a posteriori density function and thus superior estimates. Simulation results show that updating the weights during the propagation stage not only provides better estimates between the observations but also provides superior estimator performance where the measurements are ambiguous.

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Author information

Authors and Affiliations

  1. Department of Mechanical & Aerospace Engineering, University at Buffalo, Buffalo, NY, 14260

    Jemin George (Graduate Student) & Puneet Singla (Assistant Professor, Member AAS)

  2. Department of Computer Science & Engineering, University at Buffalo, Buffalo, NY, 14260

    Gabriel Terejanu (Graduate Student)

Authors
  1. Jemin George
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  2. Gabriel Terejanu
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  3. Puneet Singla
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Corresponding author

Correspondence to Jemin George.

Additional information

Presented at the F. Landis Markley Astronautics Symposium, Cambridge, Maryland, June 29–July 2, 2008.

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George, J., Terejanu, G. & Singla, P. Spacecraft Attitude Estimation Using Adaptive Gaussian Sum Filter. J of Astronaut Sci 57, 31–45 (2009). https://doi.org/10.1007/BF03321492

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