Bacterial foraging-based SIFT for full moon image direction estimation

Recently as a standalone configuration attitude sensor to get accurate attitude from body measurements and known reference observations for spacecraft, moon-sun attitude sensor gets more and more attention for spacecraft accurate attitude determination. But for full moon image situation, the symmetry axis estimation method does not work in moon-sun attitude sensor. A bacterial foraging optimisation-based Scale Invariant Feature Transform (SIFT) algorithm is proposed to recognise the Crisium Sea in moon image quickly for direction estimation in moonsun attitude sensor. Inspired by the foraging behaviour of bacteria, the bacterial foraging algorithm-based optimisation is applied to SIFT for searching the Crisium Sea characters in the full illuminated moon with a developed object function. The experimental results show that the proposed method is more efficient in the direction estimation than that traditional SIFT for the full moon image situation of moon-sun attitude sensor.