Fisheye camera star identification method based on circular FOV segmentation

Maritime celestial navigation is an important autonomous navigation technology at sea, and the star identification is a key step in celestial navigation. Aiming at the problems of large data, redundant identification and low speed caused by the large field of view (FOV) of the fisheye camera celestial navigation system, a fisheye camera star identification method based on circular FOV segmentation was proposed. For the star image taken by a fisheye camera, the concentric circles were drawn around the center with different radii, and the FOV was divided into several equal-area circular areas. In the process of constructing the navigation feature database, the star argument was taken as the feature to construct a hash function, and the navigation feature database was stored into several sub-databases. In the identification process, a multi-triangulation identification algorithm based on the central star was used to proceed from the center to the edge of the circular FOV. The results of marine observation experiments show that the method can achieve an identification success rate of more than 90% with the time of 2.5 s on average, and it has good real-time performance.