Analyzing the Unscented Kalman Filter Robustness for Orbit Determination through Global Positioning System Signals

Authors

  • Paula C. P. M. Pardal Federal University of São Paulo - Office of Science and Technology (ICT-UNIFESP)
  • Helio Koiti Kuga National Institute for Space Research - Space Mechanics and Control Division (INPE-DMC)
  • Rodolpho Vilhena de Moraes Federal University of São Paulo - Office of Science and Technology (ICT-UNIFESP)

Keywords:

Orbit determination, Nonlinear Kalman filter, GPS measurements, Real time

Abstract

http://dx.doi.org/10.5028/jatm.v5i4.252

The nonlinear unscented Kalman filter (UKF) is evaluated for the satellite orbit determination problem, using Global Positioning System (GPS) measurements. The assessment is based on the robustness of the filter. The main subjects for the evaluation are convergence speed and dynamical model complexity. Such assessment is based on comparing the UKF results with the extended Kalman filter (EKF) results for the solution of the same problem. Based on the analysis of such criteria, the advantages and drawbacks of the implementations are presented. In this orbit determination problem, the focus is to analyze UKF convergence behavior using different sampling rates for the GPS signals, where scattering of measurements will be taken into account. A second aim is to evaluate how the dynamical model complexity affects the performance of the estimators in such adverse situation. After solving the real-time satellite orbit determination problem using actual GPS measurements, through EKF and UKF algorithms, the results obtained are compared in computational terms such as complexity, convergence, and accuracy.

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Published

2013-11-23

Issue

Section

Original Papers