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一种具有高速和卓越去噪能力的实时星体质心提取算法的实现。

Implementation of a real-time star centroid extraction algorithm with high speed and superior denoising ability.

作者信息

Ding Jianqun, Dai Dongkai, Tan Wenfeng, Wang Xingshu, Qin Shiqiao

出版信息

Appl Opt. 2022 Apr 10;61(11):3115-3122. doi: 10.1364/AO.450502.

DOI:10.1364/AO.450502
PMID:35471287
Abstract

Star tracker is the most precise attitude measuring device, and its advantages include a high resolution and high update rate. Star centroid extraction, which is a very time-consuming process, has great influence on the attitude update rate. This paper proposes a real-time star centroid extraction algorithm based on a field programmable gate array. First, a 1D top-hat filter is used for star segmentation, which is suitable for both uniform and nonuniform background conditions. Second, multichannel image data is reorganized together into a complete frame through image stitching, which prevents the star spots on the channel boundary from being divided into different parts. Finally, star coordinates are extracted by the center-of-mass algorithm. For an image sensor with a resolution of 2048×2048 pixels, simulation results conducted by a ModelSim simulator show that the star centroid processing time of a single frame is roughly 5.2 ms. Real night experiments demonstrate that the standard deviation of a star centroid error is within 10 pixel and the standard deviation of attitude is (2.6 2.2 12.0) arcseconds, which proves that the proposed star centroid extraction algorithm can work continuously and stably.

摘要

星敏感器是最精确的姿态测量装置,其优点包括高分辨率和高更新率。星点质心提取是一个非常耗时的过程,对姿态更新率有很大影响。本文提出了一种基于现场可编程门阵列的实时星点质心提取算法。首先,使用一维顶帽滤波器进行星点分割,该滤波器适用于均匀和非均匀背景条件。其次,通过图像拼接将多通道图像数据重新组合成一个完整的帧,这可以防止通道边界上的星点被分割成不同的部分。最后,通过质心算法提取星点坐标。对于分辨率为2048×2048像素的图像传感器,由ModelSim模拟器进行的仿真结果表明,单帧星点质心处理时间约为5.2毫秒。实际夜间实验表明,星点质心误差的标准差在10像素以内,姿态标准差为(2.6 2.2 12.0)角秒,这证明所提出的星点质心提取算法能够连续稳定地工作。

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引用本文的文献

1
A High-Accuracy Star Centroid Extraction Method Based on Kalman Filter for Multi-Exposure Imaging Star Sensors.一种基于卡尔曼滤波器的多曝光成像星敏感器高精度星质心提取方法。
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