Review of Factor Graphs for Robust GNSS Applications

Aerospace Engineering; Jason Gross (1) ((1) Department of Mechanical; Laurel; Morgantown; Ryan Watson (2); Shounak Das (1); USA); USA (2) The Johns Hopkins University Applied Physics Laboratory; West Virginia University; WV 26505

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Review of Factor Graphs for Robust GNSS Applications

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arxiv 2112.07794 v2 pith:MCO5SCHM submitted 2021-12-14 cs.RO

Shounak Das (1) , Ryan Watson (2) , Jason Gross (1) ((1) Department of Mechanical , Aerospace Engineering , West Virginia University , Morgantown , WV 26505 , USA (2) The Johns Hopkins University Applied Physics Laboratory

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Laurel USA)

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keywords factorgraphsgnsspositioningreviewrobustadvantagesalternative

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Factor graphs have recently emerged as an alternative solution method for GNSS positioning. In this article, we review how factor graphs are implemented in GNSS, some of their advantages over Kalman Filters, and their importance in making positioning solutions more robust to degraded measurements. We also talk about how factor graphs can be an important tool for the field radio-navigation community.

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