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A high-accuracy centroid estimation algorithm for star trackers based on micro-pace matching and filtering

机译：基于微观匹配和过滤的星跟踪器高精度质心估计算法

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摘要

The attitude determination accuracy of the star tracker is affected by many factors, among them, the centroiding accuracy of the imaging star point is one of the key factors. In this paper, a high-accuracy centroid estimation algorithm for the star tracker based on micro-pace matching and filtering is proposed. The star points are considered to be discretized sampling of the effective point spread function, in order to restore the it, it is needed to establish reference frames by micro-pace movement. Then, reference frames are interpolated, and accurate reconstruction of the star point energy distribution is obtained. In addition, Point Spread Function(PSF) correlation method is adopted to match a new star point and the reference frame to obtain the centroid displacement. Furthermore, the centroid of the new star point can be calculated. At the same time, the centroid estimation is processed by real-time Extended Kalman filter, which to some extent reduces the influence of noise, and furthermore improves the star point centroid estimation accuracy. The experiment results demonstrate that the proposed approach effectively eliminate the S-curve error of traditional centroid algorithm. The star point estimation accuracy of the proposed approach is approximate 0.0086 pixel, which is a reliable and high-accuracy result for star tracker.
机译：星形跟踪器的姿态确定准确性受到许多因素的影响，其中，成像星点的绝质精度是关键因素之一。本文提出了一种基于微观匹配和滤波的星跟踪器的高精度质心估计算法。星点被认为是分散化的有效点传播功能的采样，以便通过微步运动建立参考框架。然后，参考帧被插入，获得明星点能量分布的精确重建。另外，采用点扩展功能（PSF）相关方法匹配新的星点和参考帧以获得质心位移。此外，可以计算新星点的质心。同时，通过实时扩展卡尔曼滤波器处理质心估计，这在一定程度上降低了噪声的影响，并且还提高了星点质心估计精度。实验结果表明，所提出的方法有效地消除了传统质心算法的S曲线误差。所提出的方法的星点估计准确性是0.0086像素，这是明星跟踪器的可靠和高精度的结果。

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