ODCC: A Dynamic Star Spots Extraction Method for Star Sensors

In this article, we consider the problem of extracting star spots for traditional star sensors under highly dynamic conditions. Under this setting, it is difficult to effectively extract star spots with a low signal-to-noise ratio (SNR), resulting in a failure to estimate the attitude of star sensors. We propose a method named optimal directional connected component (ODCC) for this task. According to the dynamic characteristics of star sensors, we propose an image enhancement method that can adaptively estimate the directions of star spots and integrate the star image so that the SNR of the star spots is increased. This aids in searching for spots with a low SNR. According to the imaging characteristics of a star, we model the imaging region of a star as a rectangle and then creatively cast the problem of extracting spots into a problem of estimating the endpoints of the rectangle. A maximum likelihood estimation method based on the Gaussian mixture model is proposed to determine the region of the star spot. Experiments demonstrate the extraction capability and accuracy of the method. In conclusion, this method has a promising application value for improving the dynamic performance of traditional star sensors.