Orbital Propagation

Orbital propagation focuses on accurately predicting the future positions and velocities of orbiting objects. Current research emphasizes improving the efficiency and precision of existing models like SGP4, often through the integration of differentiable programming and neural networks, creating hybrid models that combine the speed of simplified methods with the accuracy of more complex numerical techniques. This allows for faster and more precise predictions, impacting applications such as satellite tracking, space situational awareness, and spacecraft navigation. The development of differentiable propagators also facilitates the use of advanced optimization and machine learning techniques for improved orbit determination and prediction.