实时星图预处理的并行流水线算法

为提高星敏感器的星图预处理速度，减少嵌入式资源消耗，提出了一种并行流水线算法。剔除了星像点本身对背景噪声标准差（噪声水平）和均值两个特征值估计的影响，建立了是否开展滤噪的准则，确定了星图噪声的提取阈值，保证了质心定位精度。将星图缓存量降低至两行数据，用100个移位寄存器记录连通域标号，解决了嵌入式资源浪费和连通域溢出问题。仿真结果表明，50M速率输入的496×496星图流水处理完成后延迟10μs便可实时输出需要的亮星数据，使用的存储器和寄存器资源不到80kB。加入背景电平和高斯噪声后，在信噪比大于1的条件下质心精度优于1/23像素量级，验证了并行流水线的实时星图预处理算法的有效性，有助于提高星敏感器数据输出率及抗动态性能。

Abstract

To improve the preprocessing speed of star map and reduce the resource consumption of embedded system of star tracker, a parallel pipeline realtime preprocessing algorithm was presented. The two characteristics of the mean and the standard deviation of the background noise of a star map, were firstly estimated dynamically, and the influence of the star spot itself on the background noise characteristics was removed. The criterion for deciding whether the following noise filtering is conducted was established, and further the extracting threshold value which depends on the level of background noise was assigned, and meanwhile the centroiding accuracy was garanteed. In the processing algorithm, as low as two lines of pixel data were buffered, and only 100 shift registers were needed to record the connected domain label, by which the problems of resources wasting and connected domain overflow were solved. Simulation results show that the necessary data of the selected bright stars can be immediately accessed in a delay time as short as 10μs after the pipeline processing of a 496×496 star map in 50Mb/s is finished, and the needed memory and registers resource total less than 80kB. To verify the accuracy performance of the proposed algorithm, different levels of background noise were added to the processed ideal star map, and the statistic centroiding error was smaller than 1/23 pixel under the condition that the signal to noise ratio was greater than 1. Therefore the validity of the parallel pipeline algorithm of real time star map preprocessing is verified, which helps to increase the data output speed and the antidynamic performance of star tracker.

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实时星图预处理的并行流水线算法

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