一种基于星体特征值的全天星图识别法

为了解决全天三角形星图识别法运行时间较长的问题,提高星敏感器测量飞行器姿态的实时性,提出了一种基于星体特征值的全天星图识别法。该算法根据星敏感器捕获星体的原理,分析了星体附近区域的特征信息,采用星体特征值作为星体的匹配因素,并建立了基于星体特征值的全天星图识别法模型。仿真过程选择标准天文星表来提供星体数据,并从中抽取13332颗星体构成候选星表,来对算法进行仿真。仿真结果显示:与传统的全天三角形星图识别法相比,该算法具有更短的运行时间和更高的星图识别率。

An all -sky star map pattern recognition algorithm based on star eigenvalues

In order to solve the problem of long execution time in all-sky triangle star map pattern recognition algorithm,and to reduce the time spent on calculating the attitude of space vehicles by star sensor,an all-sky star map pattern recognition algorithm based on star eigenvalues is proposed.Based on the principle of star sensor capturing stars,the eigenvalue information of regions nearby the stars is analyzed,the novel algorithm takes the eigenvalues of the captured stars as the navigation factors and the model of all-sky star map pattern recognition algorithm based on star eigenvalues is built.The standard celestial star catalog is selected to provide star datum in the course of simulation,13332 stars are abstracted to build the candidate star datum from star catalog and simulate the novel algorithm.The simulation results show that the star eigenvalues algorithm has shorter execution time and higher recognition ratio than the traditional all-sky triangle star map pattern recognition algorithm.