Bacterial foraging-based SIFT for full moon image direction estimation
by Liyong Ma; Yong Zhang
International Journal of Wireless and Mobile Computing (IJWMC), Vol. 8, No. 2, 2015

Abstract: 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 moon-sun 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.

Online publication date: Tue, 07-Apr-2015

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