Satcom systems toolkit (opensatcom)
- Python
- NumPy
- SciPy
- pandas
- Plotly
Problem
Satellite link design lives in a budget: antenna gain, transmit power, free-space spreading, atmospheric loss, receiver noise, and the modem all trade against each other, and a clear-sky design can fail in rain or at a low elevation angle. Doing that bookkeeping in spreadsheets makes trade studies slow and hard to reproduce.
Approach
opensatcom turns the link budget into a typed, sweepable pipeline. A snapshot engine maps two terminals, antennas, an RF chain, and a propagation stack to EIRP, G/T, C/N0, Eb/N0, and margin in one call. Propagation composes free-space loss with simplified, ITU-R-inspired models (P.676 gases, P.618 rain, scintillation). A DVB-S2 modem layer with 28 ModCods and adaptive coding turns C/N0 into throughput. On top sit a multibeam payload model (interference and SINR maps), mission simulation (single-satellite, handover, and network traffic tiers), and a trade-study layer (design of experiments, batch runs, and Pareto extraction), with a CLI and HTML reports.
Result
The toolkit makes early satcom system design fast and reproducible: sweep elevation, frequency, rain rate, or antenna size and read the margin and estimated throughput that result, then extract the Pareto front across competing objectives. The write-up walks the link budget from EIRP to bits, with the atmospheric attenuation, the elevation sweep, and the DVB-S2 staircase generated from the package; the code is on GitHub.