Abstract

A full-sky autonomous star map identification algorithm based on radial and cyclic features is proposed. The algorithm defines a star pattern, composed of radial angular distances and circular angles. Then, a three-step strategy is adopted to find the correspondence of the sensor pattern and the catalog pattern, including initial lookup table match, cyclic dynamic match, and validation. A number of experiments are carried out on simulated and real star images. The simulation results show that the proposed method provides improved performance, especially on robustness against up to 6 false stars. Also, the average identification time is about 45ms, and memory requirement is 16MB, having a good satisfaction to the requirements of the target system.

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