Computational and Applied Mathematics

, Volume 37, Supplement 1, pp 110–121 | Cite as

Sequential nonlinear estimation: regularized particle filter applied to the attitude estimation problem with real data

  • R. V. GarciaEmail author
  • W. R. Silva
  • P. C. P. M. Pardal
  • H. K. Kuga
  • M. C. Zanardi


The aim of this work is to analyze the robustness and computational effort of particle filter when applied to the attitude and gyro bias estimation problem. The particle filter is based on the sampling method for sequential importance, in which the basic idea is to represent the density function posteriori by a set of random samples (particles) associated with their respective weights. However, after a few interactions, degeneration of particles may occur. To avoid degeneration, the regularized version of the particle filter was applied. In such estimator, the particles with lower weight are discarded and those with greater weight give rise to new particles close to the areas of the highest probability. For analysis, the attitude dynamical model is described by quaternions, and the observation vector, composed by real data of attitude sensors that are on board the CBERS-2 (China–Brazil Earth Resource Satellite). The attitude sensors available are digital sun sensor, infrared Earth sensor, and mechanical gyros. The attitude and bias of gyro estimated by the regularized particle filter are compared with the unscented Kalman filter and the results show that for systems that do not have a high degree of nonlinearity, and under consideration of real data, the unscented Kalman filter has shown better performance than the regularized particle filter.


Attitude estimation Quaternions Regularized particle filter Real data 

Mathematics Subject Classification

60G25 60-xx 60G-xx 60G-25 


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Copyright information

© SBMAC - Sociedade Brasileira de Matemática Aplicada e Computacional 2017

Authors and Affiliations

  • R. V. Garcia
    • 1
    Email author
  • W. R. Silva
    • 2
  • P. C. P. M. Pardal
    • 1
  • H. K. Kuga
    • 2
  • M. C. Zanardi
    • 3
  1. 1.University of São Paulo (USP), EELLorenaBrazil
  2. 2.Technological Institute of AeronauticsSão José dos CamposBrazil
  3. 3.Federal University of ABCSanto AndréBrazil

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