In order to implement an observing strategy,image degradation that occurs during optical observation of space debris is ineluctable and has distinct characteristics. Image restoration is presented as a way to remove the influence of degradation in CCD images of space debris,based on assumed PSF models with the same FWHM as images of the object. In the process of image restoration,the maximum entropy method is adopted. The results of reduction using observed raw CCD images indicate that the precision in estimating positions of objects is improved and the effects of degradation are reduced. Improving the astrometry of space debris using image restoration is effective and feasible.
An optical survey is the main technique for detecting space debris. Due to the specific characteristics of observation, the pointing errors and tracking errors of the telescope as well as image degradation may be significant, which make it difficult for astrometric calibration. Here we present an improved method that corrects the pointing and tracking errors, and measures the image position precisely. The pipeline is tested on a number of CCD images obtained from a 1-m telescope administered by Xinjiang Astronomical Observatory while observing a GPS satellite. The results show that the position measurement error of the background stars is around 0.1 pixel, while the time cost for a single frame is about 7.5 s; hence the reliability and accuracy of our method are demonstrated. In addition, our method shows a versatile and feasible way to perform space debris observation utilizing non-dedicated telescopes, which means more sensors could be involved and the ability to perform surveys could be improved.
Specific challenges arise in the task of real-time automatic data reduction of optical space debris observations. Here we present an automatic technique that optimally detects and measures the sources from images of optical space debris observations. We show that highly reliable and accurate results can be obtained on most images produced by our specific sensors, and due to optimizations, the whole pipeline works fast and efficiently. Tests demonstrate that the technique performs better than SExtractor from the point of view of fast and accurate detection, therefore it is well suited for data reduction of optical space debris observations.
