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在分析主星识别算法和三角形识别算法不足的基础上,提出了一种改进的主星星图识别算法。该算法在构造导航星表时,通过旋转角距的方式构造匹配向量、引入相近模式向量,同时将旋转角距向量的模、主星的邻域伴星数目及主星的最小角距作为相近模式向量的限制条件,用来减少匹配次数,提高检索效率;在星图识别过程中,首先利用向量叉乘法进行主星识别,在不成功的情况下采用三角形算法做进一步识别。仿真结果表明:该算法兼具主星识别算法和三角形算法的优点,当存在2 pixel的位置噪声时,识别成功率达到97.24%,平均识别时间仅为6.47 ms。
Based on the analysis of the main star recognition algorithm and the triangle recognition algorithm, this paper proposes an improved algorithm of the main star image recognition. The algorithm constructs a matching vector by rotating the angular distance and introduces a similar mode vector when constructing the navigation star list. At the same time, the model of the rotating angular distance vector, the number of companion stars in the vicinity of the main star and the minimum angular distance of the main star are taken as the approximate mode vectors In order to reduce the number of matches and improve the retrieval efficiency, we first use the vector-fork multiplication method to identify the principal stars and use the triangle algorithm to further identify the unsuccessful cases. The simulation results show that the proposed algorithm has the advantages of both principal recognition algorithm and triangular algorithm. When there is 2-pixel position noise, the recognition success rate reaches 97.24% and the average recognition time is only 6.47 ms.