  We present a comparison study of state-of-the-art classical optimisation
methods to a D-Wave 2000Q quantum annealer for the planning of Earth
observation missions. The problem is to acquire high value images while obeying
the attitude manoeuvring constraint of the satellite. In order to investigate
close to real-world problems, we created benchmark problems by simulating
realistic scenarios. Our results show that a tuned quantum annealing approach
can run faster than a classical exact solver for some of the problem instances.
Moreover, we find that the solution quality of the quantum annealer is
comparable to the heuristic method used operationally for small problem
instances, but degrades rapidly due to the limited precision of the quantum
annealer.
