低存储资源开销的多路快速星点质心提取方法

数据更新率是星敏感器的一项重要指标。随着大面阵图像探测器的应用，传统单路质心方法的处理速度已成为更新率的主要瓶颈。为此，提出一种多路快速星点质心提取方法。首先，采用基于目标行方向有效长度的边界目标信息融合技术，能够实现各种形状边界目标信息的正确融合。其次，采用动态双指针循环映射机制，能够对无效信息占用存储资源进行循环利用，大大提高了存储资源的利用效率。最后，对本文方法进行实验测试，并在相同现场可编程门阵列（FPGA）芯片上，与传统单路质心方法的性能进行对比分析。实验结果表明，本文方法处理速度约为传统单路质心方法的3.6倍，但使用的存储资源仅约为后者直接扩展的多路方法的40%，从而验证了本文方法的可行性与有效性。

Multichannel fast star centroid extraction method with low memory resource cost

The attitude update rate is one of the most important performance indexes of the star sensor. With the application of the large array image detector, the processing speed of the traditional star extraction method has become the main bottleneck of the update rate. Given that, a multichannel fast star centroid extraction method is proposed in this paper. Firstly, the information fusion technology based on the effective length of the target in the scanning direction is proposed to realize the correct information fusion of various shapes of boundary targets. Secondly, the dynamic dual-pointer cyclic mapping technology is utilized to recycle the memory resources occupied by invalid information, thus greatly improving the utilization efficiency of the memory resources. Finally, the experimental test is carried out to verify the performance of the proposed method, and the performance is compared and analyzed with that of the traditional single channel method on the same field-programmable gate array (FPGA) chip. The experimental results show that the processing speed of the proposed method is about 3.6 times as high as that of the traditional single channel method, while the memory resource used by the proposed method is merely about 40% of that used by the multichannel method which is directly extended by the traditional single channel method. Thus the feasibility and effectiveness of the proposed method are verified.