GNSS/INS/Visual Deeply Coupled Integration: Preliminary Investigation on Dynamic Jammed Datasets

Calogero Cristodaro, Laura Ruotsalainen, and Fabio Dovis

Peer Reviewed

Abstract:	As the Global Satellite Navigation Systems (GNSS) signals are received and processed by the GNSS receivers with an extremely low power, they are vulnerable to non-intentional and intentional interference. In particular, the intentional transmission of Radio Frequency interference, known as jamming, can completely prevent the operation of GNSS receivers. The integration of measurements from multiple sensors with complementary error characteristics offers a possible countermeasure against jamming and, therefore, it can provide a position solution that has sufficient accuracy for the applications. This paper shows how a Deeply Coupled (DC) integration of GNSS with Inertial Navigation Systems (INS) and visual sensors enhances the robustness of the navigation system in presence of jamming. In particular, the effect of DC integration for jamming mitigation is investigated for a dynamic scenario where jamming signals have been added to a pre-recorded GNSS scenario by using the record and replay approach, emulating different interference levels. The results presented in this paper show that the deep coupling of GNSS with INS and visual sensors can sustain the navigation in presence of high power jamming, although such a strong interference completely masks the GNSS signal denying the navigation of a GNSS stand-alone system. Moreover, the test procedures suitability of the record and replay approach for the jamming scenario generation and combination with real datasets are discussed and analyzed.
Published in:	Proceedings of the 31st International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2018) September 24 - 28, 2018 Hyatt Regency Miami Miami, Florida
Pages:	3088 - 3097
Cite this article:	Cristodaro, Calogero, Ruotsalainen, Laura, Dovis, Fabio, "GNSS/INS/Visual Deeply Coupled Integration: Preliminary Investigation on Dynamic Jammed Datasets," Proceedings of the 31st International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2018), Miami, Florida, September 2018, pp. 3088-3097. https://doi.org/10.33012/2018.15960
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