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Near Real Time Orbit Detemination of BILSAT-1

2009-06-13
Erdogan, Eren
Karslıoğlu, Mahmut Onur
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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
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Reduced dynamic models combined with GPSObservations on board the satellites within an extended Kalman Filtering algorithm increases the accuracy of near real time orbit determination. Gravity model as the main force and numerical integration methods are the key concepts in the GPS based reduced dynamic orbit determination. EGM 2008 Earth Gravity Model represented by U.S. National Geospatial Intelligence Agency (NGA) EGM Development Group offers a new model for the determination of gravity accelerations. Some other Earth's Gravity Models which have been generated recently from the dedicated satellite gravity field missions such as GRACE without including terrestrial observations are also evaluated in the force model for near real time orbit determination. On the other hand, numerical integration methods preferred in GPS based reduced dynamic orbit determination mostly affect the performance of the processor. In this context, another alternative to rigorous implementation of variational equation is the determination of the state transition matrix by using Markley's method which in turn contains only a simplified force model. In this study, BILSAT 1 orbit is evaluated by using EGM2008 and Grace GGM03S Earth gravity models and Markley state transition matrix. GPS based reduced dynamic orbit determination are used as the algorithm. Effect of unmodeled and unknown forces acting on satellite are approximated by first order Gauss Markov Process. Single frequency pseudorange measurements are the observations acquired from SGR 20 spaceborne GPS receiver onboard the BILSAT 1.
Reduced Dynamic Orbit Determination, Kalman filter, Markley State Transition Matrix, Spaceborn GPS Receiver, EGM2008, Gauss Markov Process
https://hdl.handle.net/11511/52545
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