Space Situational Awareness (SSA) requires a catalogue comprised of information for all the Earth orbiting objects. Operational satellite collisions with an object that is not in the catalogue are unacceptable. The increased demand for using space based services for a wide range of applications has significantly increased the number of known objects around the Earth. Observing, cataloguing, and maintaining all of these Earth orbiting objects is not a trivial task. Catalogue maintenance for SSA demands accurate and computationally lean orbit propagation and orbit determination techniques. These techniques are required for space resource operations, and for dealing with the large number of space objects created in past decades and anticipated in future decades. Multiple satellite theories were examined in order to establish the basis for recommending a viable alternative to the standard numerical propagator. Propagation accuracy and computational load testing methods are established, and the Draper Semi-analytical Satellite Theory (DSST) is investigated for its performance. A separate study was conducted to establish a least squares orbit determination process which uses the DSST partial derivatives. This process estimates the mean equinoctial elements and the dynamical parameters. Exhaustive simulated data test cases show that including the DSST in the orbit determination program is advantageous, specifically when processing observation data that is representative of SSA scenarios. Catalogue maintenance and its applications require an understanding of the uncertainties associated with the states of the catalogued objects. The majority of the objects in the current space debris environment are in Low Earth Orbit (LEO). Here, atmospheric drag is the major contributor to the orbit prediction errors, as it is the most uncertain force to model. A stochastic approach is developed to estimate the orbit prediction error statistics due to uncertainties in the density model. The method is tested with available real data, and the results are discussed. The uncertainty estimation method is combined with a standard covariance propagation method to showcase the applicability to the catalogue maintenance system.
«Space Situational Awareness (SSA) requires a catalogue comprised of information for all the Earth orbiting objects. Operational satellite collisions with an object that is not in the catalogue are unacceptable. The increased demand for using space based services for a wide range of applications has significantly increased the number of known objects around the Earth. Observing, cataloguing, and maintaining all of these Earth orbiting objects is not a trivial task. Catalogue maintenance for SSA d...
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