DarKnight

The number of satellites in orbit has grown dramatically over the last few years, with large constellations becoming a defining feature of the modern space industry. While these constellations enable new services and capabilities, they also introduce new challenges for ground-based astronomy. Satellite reflections create bright streaks in telescope images, increase background noise, and can interfere with scientific observations.
As satellite operators, manufacturers, and regulatory agencies place increasing emphasis on reducing the impact of spacecraft on the night sky, accurate prediction of satellite brightness has become an essential part of spacecraft design. DarKnight provides a fast and flexible solution for modelling satellite visual brightness throughout a mission, enabling engineers to assess visibility and evaluate design options before launch.
A satellite becomes visible because sunlight is reflected from its surfaces towards an observer on the ground. The apparent brightness depends on many factors, including the spacecraft geometry, surface materials, orientation, orbit, the position of the Sun, and the observer's location.
DarKnight simulates these interactions to predict the apparent visual magnitude of one or many satellites over time. It supports the analysis of individual spacecraft, multiple satellite designs, and complete constellations, allowing users to identify critical observation conditions and assess compliance with emerging "Dark and Quiet Skies" requirements.
Satellite brightness analysis plays an increasingly important role during spacecraft design. It helps engineers evaluate different material choices, optimise solar array and antenna configurations, compare attitude strategies, and understand how design decisions influence the visibility of a spacecraft from Earth.
DarKnight has been verified against published studies, real observational data, and benchmarked against ESA's DRAMA software and Lumos-Sat. The tool has also been applied to representative industrial cases covering both individual satellites and large constellations, providing confidence in its predictive capabilities.
More detailed verification results, validation methodology, and practical application examples are available through dedicated training sessions. If you are interested, contact us.

Full validation on a representative pilot case.