Star Detection

Star detection involves identifying and locating stars in images, crucial for applications like spacecraft navigation and autonomous systems. Current research focuses on improving the accuracy and speed of star identification algorithms, particularly in challenging conditions like high noise levels or limited field of view, employing techniques such as convolutional neural networks (CNNs) and optimized search algorithms like Branch-and-Bound methods. These advancements enhance the reliability and efficiency of star trackers, impacting fields ranging from autonomous navigation in maritime and aerial vehicles to precise attitude determination in space missions. The development of faster, more robust algorithms is a key area of ongoing investigation.