Nebula Public Library

In this project the authors looked at event-based sensing and processing for space situational awareness (SSA). Many advantages exist with the new paradigm of neuromorphic engineering, the authors investigate whether event-based optical data is suitable for the task and if processing with Spiking Neural Networks (SNN) provides advantages in terms of efficiency and efficacy. With the implementation of a novel heterogeneous LIF SNN, authors claim to surpass the state of the art in event-based SSA with a 15% increase in accuracy.

With the 'democratisation of space', and the proliferation of large non-geostationary orbit constellations, the pace at which human-made objects are being deployed into orbit demands urgent action in defining and supporting a global space traffic management plan.

The market for life‐extension services for geostationary orbit (GEO) satellites is expected to remain healthy for the foreseeable future: over the last 20 years, an average of 22 new GEO satellites were launched per year. In total, ClearSpace expects there will be 370 potential client satellites that will reach their end of life due to the limited fuel they have remaining over the 2026–2041 period. ClearSpace believes a strong market penetration rate is feasible, as more than 30% of all the potential satellites belong to just seven satellite operators.

For long-term studies, numerical simulations are at the center of predicting the space debris environment of the upcoming decades. In the scope of the study, the authors present the architecture and proof-of-concept results for a numerical simulation capable of modeling the long-term debris evolution over decades with a deterministic conjunction tracking model in contrast to typically employed Monte Carlo methods. For the simulation, an efficient propagator in modern C++ accounting for Earth’s gravitational anomalies, solar radiation pressure, and atmospheric drag was developed.