Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1763436 | Advances in Space Research | 2016 | 16 Pages |
•New functionalities were brought into the DSST standalone propagator’s capability.•A semi-analytical way of computing the partial derivative matrix was successfully inserted and tested.•Multiple test procedures were employed to test the performance capabilities of DSST.•DSST performed very close in accuracy to the SP method and within the requirements.•DSST outperforms SP method by 3–4 orders in magnitude of computational runtime.
Catalog maintenance for Space Situational Awareness (SSA) demands an accurate and computationally lean orbit propagation and orbit determination technique to cope with the ever increasing number of observed space objects. As an alternative to established numerical and analytical methods, we investigate the accuracy and computational load of the Draper Semi-analytical Satellite Theory (DSST). The standalone version of the DSST was enhanced with additional perturbation models to improve its recovery of short periodic motion. The accuracy of DSST is, for the first time, compared to a numerical propagator with fidelity force models for a comprehensive grid of low, medium, and high altitude orbits with varying eccentricity and different inclinations. Furthermore, the run-time of both propagators is compared as a function of propagation arc, output step size and gravity field order to assess its performance for a full range of relevant use cases. For use in orbit determination, a robust performance of DSST is demonstrated even in the case of sparse observations, which is most sensitive to mismodeled short periodic perturbations. Overall, DSST is shown to exhibit adequate accuracy at favorable computational speed for the full set of orbits that need to be considered in space surveillance. Along with the inherent benefits of a semi-analytical orbit representation, DSST provides an attractive alternative to the more common numerical orbit propagation techniques.