INSTINCT: a flow-based open-source PNT framework for satellite navigation and sensor fusion

INS toolkit for integrated navigation concepts and training (INSTINCT) is an open-source positioning, navigation and timing (PNT) framework for global navigation satellite system (GNSS) navigation and sensor fusion written in C++. It uses flow-based programming to encapsulate functionality, enforce...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:GPS solutions Ročník 29; číslo 4; s. 171
Hlavní autoři: Topp, Thomas, Maier, Marcel, Hobiger, Thomas, Becker, Doris
Médium: Journal Article
Jazyk:angličtina
Vydáno: Berlin/Heidelberg Springer Berlin Heidelberg 01.10.2025
Springer Nature B.V
Témata:
ISSN:1080-5370, 1521-1886
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Popis
Shrnutí:INS toolkit for integrated navigation concepts and training (INSTINCT) is an open-source positioning, navigation and timing (PNT) framework for global navigation satellite system (GNSS) navigation and sensor fusion written in C++. It uses flow-based programming to encapsulate functionality, enforce clean interfaces and promote reusability. Not only multi-constellation, multi-frequency single point positioning (SPP) and real-time kinematic positioning (RTK) algorithms are available, but also inertial navigation system (INS)/GNSS sensor fusion. Moreover, innovative concepts like multi inertial measurement unit (IMU) arrays and factor graph optimization are featured. Furthermore, most file formats common in the PNT field can be read with the software and converted between them. Also, simulation of trajectories and IMU data with different error models is possible. A graphical user interface allows the user to directly set parameters and analyze results in plots, which enables rapid prototyping and testing. A developer can easily extend the functionality with own algorithms and sensor interfaces building upon the existing modules. In order to evaluate the performance of the algorithms two experiments were performed. Analysis of a static dataset shows that the position accuracy of the RTK algorithm of INSTINCT is comparable to RTKLIB. Additionally, a dynamic dataset was generated using a Spirent GNSS simulator and INSTINCT’s IMU simulation capabilities. In-depth assessment confirms the high accuracy of the results and demonstrates that the INS/GNSS loosely coupled Kalman filter can compensate for GNSS outages.
Bibliografie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:1080-5370
1521-1886
DOI:10.1007/s10291-025-01927-4