Space debris in low Earth orbit (LEO) below 1500 km is becoming an increasing threat to spacecrafts. To manage the threat, we are developing systems to improve the ground-based tracking and imaging of space debris and satellites. We also intend to demonstrate that it is possible to launch a high-power laser that modifies the orbits of the debris. However, atmospheric turbulence makes it necessary to use adaptive optics with such systems. When engaging with objects in LEO, the objects are available only a limited amount of time. During the observation window, the object has to be acquired and performance of all adaptive optics feedback loops optimised. We have implemented a high-level adaptive optics supervision tool to automatise time-consuming tasks related to calibration and performance monitoring. This paper describes in detail the current features of our software.
Adaptive Optics (AO) systems rely on atmospheric turbulence models in order to reduce the effect of wave-front aberrations on image quality. Due to the nature of turbulence, these models can exploit shift-invariant structures without a severe loss in generality. The resulting subset of possible state-matrices is efficiently characterised for identification using Quadratic Programming (QP). Additionally, the initial assumption of shift-invariance is relaxed in order to accommodate for the boundary effect of finite-pupils.