Mon Oct 13, F. Flechtner
• Sorted by Date • Sorted by Last Name of First Author •
Causa, Flavia, Renga, Alfredo, and Grassi, Michele, 2018. Robust filter setting in GPS-based relative positioning of small-satellite LEO formations. Advances in Space Research, 62(12):3369–3382, doi:10.1016/j.asr.2018.03.020.
• from the NASA Astrophysics Data System • by the DOI System •
@ARTICLE{2018AdSpR..62.3369C,
author = {{Causa}, Flavia and {Renga}, Alfredo and {Grassi}, Michele},
title = "{Robust filter setting in GPS-based relative positioning of small-satellite LEO formations}",
journal = {Advances in Space Research},
keywords = {Formation flying, Long baseline, GPS navigation, Tuning, Double differences},
year = 2018,
month = dec,
volume = {62},
number = {12},
pages = {3369-3382},
abstract = "{Formations of small satellites are becoming more and more important to
many space applications, since they offer the possibility of
distributing the payload functionality among the different
elements of the formation, so to improve scientific return,
providing at the same time a number of advantages in terms of
overall system reliability, flexibility and modularity. However,
precise autonomous determination of the relative positions of
the formation members is required for formation acquisition and
maintenance, and scientific objective achievement. For Low-
Earth-Orbit formations, this task can be performed exploiting
GPS-based relative positioning techniques. The technique
exploited in this paper is designed for on board usage. It
processes double differenced pseudo-range and carrier phase
observables on two frequencies within a hybrid filtering scheme
to get satisfactory precision and high robustness. However,
relative positioning by GPS is affected by the capability of
correctly estimating differential ionospheric delays, and, then,
by the status of ionosphere activity. Hence, the filter includes
an ionospheric model capable of reproducing ionosphere
horizontal gradients with a minimum number of parameters, which
can be estimated on the fly. In addition, a robust tuning
approach is developed in the paper to get stable filter
performance over long period of times. Specifically, the
proposed approach combines an empirical tuning technique with a
randomized algorithm to get the best filter tuning. Filter
performance and tuning approach effectiveness are successfully
verified using freely available GPS flight data of Gravity
Recovery and Climate Experiment mission.}",
doi = {10.1016/j.asr.2018.03.020},
adsurl = {https://ui.adsabs.harvard.edu/abs/2018AdSpR..62.3369C},
adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}
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