RODec 14, 2021
Review of Factor Graphs for Robust GNSS Applications
arXiv:2112.07794v2
Originality Synthesis-oriented
AI Analysis
This is an incremental review for the radio-navigation community, summarizing existing methods without new results.
The paper reviews the use of factor graphs as an alternative to Kalman Filters for GNSS positioning, highlighting their advantages in improving robustness to degraded measurements.
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.