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S3SLAB multi-Satellite Simulator

                                

                                                Logo of S3 (credits: SLAB)

All research into satellite guidance, navigation, and control relies upon high-fidelity software simulations of satellite dynamics. While there exist high-fidelity software packages written in FORTRAN, C++, and Java, these packages are not suitable for rapid development and testing of novel GNC concepts, due to the lengthy write-compile-execute development cycle. However, more agile development environments that interpret scripts at runtime are unable to deliver the performance (in terms of speed and accuracy) that is often required for the most cutting-edge applications.
To solve both these issues we are developing a satellite dynamics toolkit for Matlab/Simulink that relies upon a core set of satellite dynamics libraries written in C++ and compiled to Matlab executable files. This way users can leverage the speed and performance of compiled software while being able to work in the Matlab/Simulink environment, which offers model-based capabilities, a user-friendly interface, high modularity, and is familiar to the aerospace community. Scan be accessed from Stanford's network by clicking here.
Future work will include the development of modules for orbit and attitude dynamics, GNSS and optical navigation systems, and precise orbit determination capabilities. 
High-Fidelity Simulation, Validation, and Training for Multi-Satellite Systems
                                

                                  SLAB's Hardware-in-the-Loop Testbed (credits: SLAB)

Recent Publications (2018-2019)
 
Beierle C., D'Amico S.;
Variable Magnification Optical Stimulator for Training and Validation of Spaceborne Vision-Based Navigation;
Journal of Spacecraft and Rockets (2019).DOI: 10.2514/1.A34337 Published Online

Park T., D'Amico S.;
ESA Pose Estimation Challenge 2019;
Technical Note, Stanford Space Rendezvous Lab (SLAB), July 3 (2019).

Beierle C.;
High Fidelity Validation of Vision-Based Sensors and Algorithms for Spaceborne Navigation;
Stanford University, PhD Thesis (2019).

Giralo V., D’Amico S.;
Development of the Stanford GNSS Navigation Testbed for Distributed Space Systems;
Institute of Navigation, International Technical Meeting, Reston, Virginia, January 29-February 1 (2018).

Sharma S., Beierle C., D'Amico S.;
Generative Adversarial Networks for High-Fidelity Simulation of Spacecraft Proximity Operations;
Technical Note, Stanford Space Rendezvous Lab (SLAB), April 23 (2018).