Abstract
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.
Highlights
This work points out the nonlinear unscented Kalman filter (UKF) robustness assessment for a real-time satellite orbit determination problem, using Global Positioning System (GPS) measurements
This evaluation is based on comparing the UKF performance with the extended Kalman filter (EKF) for different sampling rates of the measurement from GPS signals
The results showed that the performance of the filters decreases as increasing the sampling intervals
Summary
This work points out the nonlinear unscented Kalman filter (UKF) robustness assessment for a real-time satellite orbit determination problem, using Global Positioning System (GPS) measurements. Pardal et al (2011) compared between the EKF and the nonlinear SPKF for a real-time satellite orbit determination problem, using GPS measurements for degraded initial conditions.
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
