基于动态夹角匹配的星图识别算法

Star Identification Algorithm Based on Dynamic Angle Matching

星图识别算法是星敏感器中的关键技术,通过对观测恒星的识别实现对航天器的高精度姿态解算。现有的星图识别算法,通常需要选取最近的邻星作为起始星,从而过于依赖起始星的选取导致识别准确率不佳。因此,提出了一种基于动态夹角匹配的识别算法,使用邻星之间的夹角以及邻星与观测星之间的距离作为动态夹角特征,并借助该特征计算观测星与各个导航星之间的匹配度得分,最终将匹配度得分最高的导航星作为识别结果。仿真验证结果表明,该方法具有较高的识别率且对于噪声具有较强的鲁棒性。在对16200幅模拟星图的仿真实验中,该方法的识别率可达到99.80%,并在位置噪声、伪星以及星等噪声影响下均能保持97.00%以上的识别率。

Star identification algorithm is the key technology of star sensor. Through the identification of observed stars, the high-precision attitude calculation of spacecraft is realized. The existing star identification algorithms usually need to select the nearest neighbor star as the starting star, which results in poor recognition accuracy due to over reliance on the selection of the starting star. In this paper, a star identification algorithm based on dynamic angle matching is proposed. The angles between neighbor stars, and the distances between neighbor stars and observation star are used as the dynamic angle features. With the help of the features, the matching score between observation star and each navigation star is calculated. Finally, the navigation star with the highest matching score is taken as the recognition result. The simulation results show that the method has high recognition rate and good robustness to noise. In the simulation experiment of 16200 simulated star images, the recognition rate of this method can reach 99.80%, and it can maintain above 97.00% under the influence of position noise, false stars and magnitude noise.