What are the key system-of-systems challenges in a distributed CubeSat observation architecture?
I’ve been thinking about distributed CubeSat-based observation architectures and trying to understand them from a systems engineering perspective rather than a mission-specific one.
The idea would be a loosely or tightly coordinated network of small satellites performing shared observational tasks (optical or other sensing modalities), with some level of distributed coordination and data fusion.
Not a single mission, but a system-of-systems with:
- distributed sensing nodes (CubeSats)
- coordinated observation scheduling
- inter-node communication (or ground-mediated sync)
- shared calibration strategies
- distributed data processing / fusion pipelines
- possibly near-real-time transient detection workflows
From a systems engineering standpoint, I’m trying to understand where the real limiting factors emerge when you scale coordination across multiple independent orbital nodes.
Some questions I’m particularly interested in:
- Where does coordination complexity become dominant over hardware constraints?
- How hard is cross-node calibration in practice for meaningful data fusion?
- What are the real bottlenecks: timing synchronization, bandwidth, orbital mechanics constraints, or something else?
- At what point does the system stop being “distributed instruments” and become “independent instruments with post-hoc aggregation”?
Curious how people here would break down the system-level failure modes or scaling limits.