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