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Onboard orbit determination using GPS measurements for low Earth orbit satellites

Zhou, Ning (2005) Onboard orbit determination using GPS measurements for low Earth orbit satellites. .

Abstract

Recent advances in spaceborne GPS technology have shown significant advantages in many aspects over conventional technologies. For instance, spaceborne GPS can realize autonomous orbit determination with significant savings in spacecraft life cycle, in power, and in mass. At present, the onboard orbit determination in real time or near-real time can typically achieve 3D orbital accuracy of metres to tens metres with Kalman filtering process, but 21st century space engineering requires onboard orbit accuracy of better than 5 metres, and even sub-metre for some space applications. The research focuses on the development of GPS-based autonomous orbit determination techniques for spacecraft. Contributions are made to the field of GPS-based orbit determination in the following five areas:

Techniques to simplify the orbital dynamical models for onboard processing have been developed in order to reduce the computional burden while retaining full model accuracy. The Earth gravity acceleration approximation method was established to replace the traditional recursive acceleration computations. Results have demonstrated that with the computation burden for a 55× spherical harmonic gravity model, we achieve the accuracy of a 7070× model. Efforts were made for the simplification of solar & lunar ephemerides, atmosphere density model and orbit integration. All these techniques together enable a more accurate orbit integrator to operate onboard.

Efficient algorithms for onboard GPS measurement outlier detection and measurement improvement have been developed. In addition, a closed-form single point position method was implemented to provide an initial orbit solution without any a priori information.

The third important contribution was made to the development of sliding-window short-arc orbit filtering techniques for onboard processing. With respect to the existing Kalman recursive filtering, the short-arc method is more stable because more measurements are used. On the other hand, the short-arc method requires less accurate orbit dynamical model information compared to the long-arc method, thus it is suitable for onboard processing. Our results have demonstrated that by using the 1 ~ 2 revolutions of LEO code GPS data we can achieve an orbit accuracy of 1 ~ 2 metres. Sliding-window techniques provide sub-metre level orbit determination solutions with 5~20 minutes delay.

A software platform for the GPS orbit determination studies has been established. Methods of orbit determination in near-real time have been developed and tested. The software system includes orbit dynamical modelling, GPS data processing, orbit filtering and result analysis modules, providing an effective technical basis for further studies.

Furthermore a ground-based near-real time orbit determination system has been established for FedSat, Australia's first satellite in 30 years. The system generates 10-metre level orbit solution with half-day latency on an operational basis. This system has supported the scientific missions of FedSat such as Ka-band tracking and GPS atmosphere studies within the Cooperative Research Centre for Satellite System (CRCSS) community. Though it is different from the onboard orbit determination, it provides important test-bed for the techniques described in previous section.

This thesis focuses on the onboard orbit determination techniques that were discussed in Chapter 2 through Chapter 6. The proposed onboard orbit determination algorithms were successfully validated using real onboard GPS data collected from Topex/Poseidon, CHAMP and SAC-C satellites.

Impact and interest:

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ID Code: 16076
Item Type: QUT Thesis (PhD)
Supervisor: Feng, Yanming& Enderle, Werner
Keywords: GPS measurements, Low Earth Orbit Satellites, GPS technology, onboard orbit determination, orbital dynamical models, onboard processing
Divisions: Past > QUT Faculties & Divisions > Faculty of Built Environment and Engineering
Department: Faculty of Built Environment and Engineering
Institution: Queensland University of Technology
Deposited On: 03 Dec 2008 13:56
Last Modified: 29 Oct 2011 05:42

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