An All-Sky Imaging Framework for Cloud-Free Line-of-Sight Assessment in Free-Space Optical Satellite Downlinks

Abstract

Free-space optical (FSO) downlinks from satellites enable high data rates but are highly sensitive to cloud-induced attenuation and blockage. We present an integrated all-sky imaging framework for optical ground stations that converts station-local sky observations into direction- and lead-time-dependent cloud-free line-of-sight (CFLOS) decision support along predicted satellite links. The framework combines geometric calibration of hemispheric imagery, two-line element (TLE)-based orbit propagation, stereographic remapping into a common processing domain, short-horizon autoregressive sky-frame prediction using a diffusion-based sequence model, cloud/no-cloud segmentation, and a corridor-based CFLOS decision rule along the projected satellite path. The contribution lies in the operational integration of these components into a unified CFLOS-oriented sensing, prediction, and evaluation chain for optical downlink support. The framework is demonstrated at the German Aerospace Center (DLR) optical ground-station site in Trauen and evaluated using a geometry-controlled reference-track protocol across image sequences acquired at 15 s, 30 s, and 45 s cadence. Under this protocol, nowcasting-based CFLOS decisions outperformed a constant-persistence baseline across all evaluated lead times. At a 90 s lead time, the method achieved an F1-score of 0.857 and a balanced accuracy of 0.865, corresponding to gains of +0.083 and +0.089 over persistence, respectively. Positive performance margins are maintained across the full evaluated range up to a 450 s lead time. These results show that all-sky image sequences can be translated into physically interpretable CFLOS decision support and provide a basis for future network-level site-selection and handover strategies.