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Orbit Optimization for Future Satellite Gravity Field Missions: Influence of the Time Variable Gravity Field Models in a Genetic Algorithm Approach

  • Siavash Iran Pour
  • Nico Sneeuw
  • Matthias Weigelt
  • Alireza Amiri-Simkooei
Conference paper
  • 87 Downloads
Part of the International Association of Geodesy Symposia book series (IAG SYMPOSIA, volume 151)

Abstract

Many studies in the past have discussed potential orbit configurations of future satellite gravity missions. Most of those works have targeted orbit optimization of the satellite missions of the next generation in the so-called Bender formation. The studies have investigated the impact of the Keplerian orbital parameters, especially the influence of the repeat orbits and mission altitude of both satellite pairs and the inclination of the second pair in Bender formation on the satellite configurations’ gravity field recovery quality performance.

Obviously, the search space for the orbit optimization in the Bender formation is vast and, therefore, different approaches have been suggested for optimal orbit design. Among approaches, however, different assumptions about input geophysical models as well as the error models into the simulation software play a role. Our paper shows how different assumptions for input models change the orbit optimization results. For this purpose, the genetic algorithm has been utilized for orbit optimization of the Bender formation where different input models were considered. Those input models include (1) the updated ESA geophysical models, and (2) error models for the Ocean Tide (OT error) and Atmosphere-Ocean (AO error). Here, we focus on the impact of the models on relative difference of the longitude of ascending nodes between the two pairs in Bender formation. The results of the paper clearly state that our current and future knowledge about signal and error models can significantly affect the orbit optimization problem.

Keywords

Genetic algorithm Gravity field recovery Orbit optimization Time-variable gravity field 

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Siavash Iran Pour
    • 1
    • 2
  • Nico Sneeuw
    • 2
  • Matthias Weigelt
    • 3
  • Alireza Amiri-Simkooei
    • 1
    • 4
  1. 1.Department of Geomatics Engineering, Faculty of Civil Engineering and TransportationUniversity of IsfahanIsfahanIran
  2. 2.Institute of Geodesy, University of StuttgartStuttgartGermany
  3. 3.Institute of Geodesy, Leibniz University of HannoverHannoverGermany
  4. 4.Department of Control and Operations, Technical University of DelftDelftThe Netherlands

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