Abstract
The combination of GPS measurements and high-fidelity dynamic models via a Kalman filter/smoother, known as the reduced dynamic technique, allows 3D positioning of Low Earth Orbiters to the sub-decimeter level. Such accuracies can only be achieved if the GPS data are nearly continuous, post-processed and a dual-frequency receiver is utilized. The focus of this study is to quantitatively analyze the degradations in position accuracy in the presence of various limitations or constraints, which can be brought on by mission hardware limitations, for example, on micro- or nanosatellites. The constraints explored in this study are as follows: the use of single-frequency data only; real-time processing; limited dynamic modeling due to computing capabilities; and non-continuous GPS receiver operation due to power limits. The experiments are conducted with 6-h data arcs for 7 separate days using data from the CHAllenging Mini-Satellite Payload. A 3D root mean square (rms) error of 15 cm is observed in the best-case solution, in which dual-frequency data are post-processed with all available data. Various levels of accuracy degradations are observed as constraints are placed on this best-case solution. The 3D rms error of the post-processed, single-frequency solution is 68 cm and 1.3 m for the real-time, dual-frequency solution. In very challenging environments, for example, with the receiver on for only 10 min of a 90-min orbit, the 3D rms increases to 350 m.
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