A fast star identification algorithm using feature vector
Stars in a star map can be regarded as a point pattern, and we can utilize the matching of point pattern to recognize star pattern. First, the inth Radius-Weighted-Mean Points (RWMPs) are proposed which are invariant to translation, rotation and scaling. And then, a RWMP-based feature vector is constructed which is still invariant to translation and rotation. The candidate referenced star images and their corresponding attitudes are obtained by computing the Euclidean distance between the viewed star image and each of the star images in the pattern database. A verification process is introduced to confirm the identification results. The simulation results indicates that the average identification rate of the proposed algorithm can be enhanced 8.9％ as compared to the Radial and Cyclic Feature algorithm (RCF algorithm) and 3.5％ as compared to the grid algorithm at the same star position noise level from 0 to 3 pixels, and moreover, the identification time of the proposed algorithm is reduced to 1/6 and 1/5 respectively.
star sensor star identification feature vector feature extraction
Qi-Shen LI Chang-Ming ZHU Jun GUAN
School of Information Engineering,Nanchang Hangkong University,Nanchang 330063,China
国际会议
The Third International Conference on Modelling and Simulation(第三届国际建模、计算、仿真、优化及其应用学术会议 ICMS 2010)
无锡
英文
400-403
2010-06-04（万方平台首次上网日期，不代表论文的发表时间）