%0 Conference Paper %1 topp2022flowbased %A Topp, Thomas %A Hobiger, Thomas %B Proceedings of the 35th International Technical Meeting of the Satellite Division of the Institute of Navigation (ION GNSS+ 2022) %D 2022 %K %P 2492-2502 %T Flow-Based Programming for Real-Time Multi-Sensor Data Fusion %X Flow-based programming (FBP) splits software functionality into modules which are triggered by data elements flowing from one module to the next. Thus, modules, which are not directly dependent on data from each other, can run independently and applications can be parallelized on a basic level what is a major improvement for the performance of multi-sensor data fusion algorithms. This paper discusses the flow-based software INSTINCT, which is a solid framework for implementing PNT algorithms and helps to reduce development times by making algorithms reusable. It provides an intuitive graphical user interface (GUI) that makes it usable in research and teaching. Inside the software, a variety of file formats and sensors for IMU und GNSS data processing are implemented. The realization of an INS/GNSS loosely-coupled Kalman filter flow is discussed and the results are compared to a flow representing a single point positioning (SPP) solution. Finally, a performance study of the algorithm on a 4th generation Intel CPU is presented, demonstrating that real-time capabilities can be ensured even on older systems. %@ 978-0-936406-32-9

@inproceedings{topp2022flowbased, abstract = {Flow-based programming (FBP) splits software functionality into modules which are triggered by data elements flowing from one module to the next. Thus, modules, which are not directly dependent on data from each other, can run independently and applications can be parallelized on a basic level what is a major improvement for the performance of multi-sensor data fusion algorithms. This paper discusses the flow-based software INSTINCT, which is a solid framework for implementing PNT algorithms and helps to reduce development times by making algorithms reusable. It provides an intuitive graphical user interface (GUI) that makes it usable in research and teaching. Inside the software, a variety of file formats and sensors for IMU und GNSS data processing are implemented. The realization of an INS/GNSS loosely-coupled Kalman filter flow is discussed and the results are compared to a flow representing a single point positioning (SPP) solution. Finally, a performance study of the algorithm on a 4th generation Intel CPU is presented, demonstrating that real-time capabilities can be ensured even on older systems.}, added-at = {2022-10-24T12:51:22.000+0200}, author = {Topp, Thomas and Hobiger, Thomas}, biburl = {https://puma.ub.uni-stuttgart.de/bibtex/22ddf6dae767ecf0790b57c0b59cb78f3/topp}, booktitle = {Proceedings of the 35th International Technical Meeting of the Satellite Division of the Institute of Navigation (ION GNSS+ 2022)}, eventdate = {September 19–23, 2022}, eventtitle = {ION GNSS+ 2022}, interhash = {f58569a9abc7d99cfac69b2944e63bb5}, intrahash = {2ddf6dae767ecf0790b57c0b59cb78f3}, isbn = {978-0-936406-32-9}, issn = {2331-5954}, keywords = {}, organization = {Institute of Navigation, Inc. (ION)}, pages = {2492-2502}, timestamp = {2022-10-24T10:51:22.000+0200}, title = {Flow-Based Programming for Real-Time Multi-Sensor Data Fusion}, year = 2022 }