Faint Space Target Information Extraction Based on Small Aperture Telescope in Complex Background

Abstract

There are many problems in space debris monitoring with ground-based telescopes, such as too many stars in the same field of view, uneven background and optical distortion in the optical system. We propose a two-stage weak debris detection algorithm. In the first stage, wavelet transform is used to extract different components of three frames of images, and the median of corresponding components of the images is taken respectively to eliminate the influence of stars. In the second stage, an improved version of the faint space target extraction based on principal component analysis. The algorithm uses a smooth-detection idea to extract target information. Based on a 150 mm aperture telescope, we improved the existing method of faint space debris extraction based on principal component analysis by introducing the smooth-detection idea, and transformed the target detection problem into the separation problem of sparse matrix and low-rank matrix. We applied a certain preprocessing consisting of wavelet-based star removal and median pre-filtering to keep as little noise and other contaminants as possible. After experimental measurements by observers, the algorithm demonstrated advanced detection capabilities on multiple indicators.