Optimal scheduling for geosynchronous space object follow-up observations using a genetic algorithm

Abstract

Optical observations for space debris in the geosynchronous region have been performed for many years.
\nDuring this time, observation strategies, processing techniques and cataloguing approaches were successfully
\ndeveloped. Nevertheless, the importance of protecting this orbit region from space debris requires
\ncontinuous monitoring in order to support collision avoidance operations. So-called follow-up observations
\nproviding information for orbit improvement estimations are necessary to maintain high accuracy
\nof the cataloged objects. Those serve a two-fold: For one, the orbits have to be accurate enough to be
\nable to re-observe the object after a time of no observations, that is keeping it in the catalogue, secondly,
\nthe importance of protecting active space assets from space debris requires even higher accuracy
\nof the catalogue orbits. Due to limited observation resources and because a space debris object in the
\ngeostationary orbit region may only be observed for a limited period of time per the observation night
\nand telescope, efficient scheduling of follow-up observations is a key element. This paper presents an
\noptimal scheduling algorithm for a robotic optical telescope network using a genetic algorithm that has
\nbeen applied providing optimal solutions for catalogue maintenance. As optimization parameter the
\ninformation content of the orbit has been used. It is shown that information content utilizing the orbit’s
\ncovariance and the information gain in an expected update is a useful optimization measure. Finally,
\nsimulations with simulated data of space debris objects are used to study the effectivity of the scheduling
\nalgorithm.