Closed-Loop GNSS/INS Simulation Chain with RTK-Accuracy for Sensor Fusion Algorithm Verification

Andreas Schütz, Mohamed Bochkati, Daniel Maier, Thomas Pany

Abstract: For future navigation applications like autonomous driving, air mobility or indoor navigation, GNSS only will not be sufficient to fulfill the challenging requirements these applications are demanding. Only GNSS in combination with other sensor systems can face these challenges ahead. To be able to develop such complex multi-sensor systems, it is crucial to first establish a continuous, robust and flexible procedure to test and verify algorithms and their implementation at any stage of their development. Originating from a pure software receiver, the Multi-Sensor Navigation Analysis Tool (MuSNAT) [1], developed at the Institute of Space Technology and Space Applications (ISTA) at the Universität der Bundeswehr München, has evolved into a versatile navigation platform using various advanced GNSS positioning techniques and sensors such as LiDAR and IMU. Using previously developed GNSS and INS simulation tools within the scope of this paper, we demonstrate how we at ISTA realized our closedloop testing procedure and successfully generated and married synthetic GNSS and IMU data in an RTK/INS loose-coupling scenario. We successfully show the overall quality of the simulation and sensor fusion using the coincidence of a-posteriori INS biases and the initially simulated ones, in a high precision scenario, as well as the ambiguity fixing ratio of the GNSS phase measurements.
Published in: Proceedings of the 33rd International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2020)
September 21 - 25, 2020
Pages: 2867 - 2877
Cite this article: Schütz, Andreas, Bochkati, Mohamed, Maier, Daniel, Pany, Thomas, "Closed-Loop GNSS/INS Simulation Chain with RTK-Accuracy for Sensor Fusion Algorithm Verification," Proceedings of the 33rd International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2020), , September 2020, pp. 2867-2877.
https://doi.org/10.33012/2020.17631
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