Effective algorithms of detection of faint space objects streaks

A problem of joint detection and estimation of parameters of faint space object streaks in digital image (frame) is considered. In this work, we propose an effective two-stage algorithm for detecting a streak of a faint space object with unknown orbit and estimating its parameters. At the first stage, the sequential change detection method is used to detect abrupt changes in the statistical properties of the signal along the streak direction and thus to localize the object and preliminarily determine the beginning and end of the streak. At the second stage, the maximum likelihood ratio method is used to more precisely estimate the position of the streak. This two stage approach significantly reduces the number of hypotheses compared to the popular maximum likelihood ratio method. The developed algorithm is tested using both the simulated frames and the real data containing discrete clutter due to stars in addition to the background noise and streaks. In the case of real frames a spatiotemporal regression algorithm is used for clutter suppression. Tests show that the proposed two stage algorithm is able to detect streaks of space objects and accurately estimate their parameters with a signal-to-noise ratio for less than 1.