Viability Assessment Report on TTRDP GMTI Constallation Study
Bibliographic record
Abstract
Driven by the potential military utility of a satellite constellation providing wide-area space based surveillance, the Trilateral Technology Research and Development Program (TTRDP) envisaged a framework that supports constellation concept design, assessment modeling and system feasibility studies. The concept design's "study and evolve" approach was institutionalized by formulating various teams, each oriented towards distinct research activity, to cooperatively feed on each others inferences. The performance assessment activity kicked-off with an initial set of constellation design parameters with 36 satellites distributed in 12 orbital planes inclined at 850. The outcome of iterative research and assessment activities revealed that 27 satellites distributed in nine orbital planes at 63.40 inclination produces equally acceptable results over most of the globe. This report is the result of an effort to deduce the viability of various design trade-offs that the two sets of satellite orbital parameters and constellation patterns can render on the Measure of Performance (MOP). Simulation Laboratory (SimLab), a simulator built in-house at DRDC Ottawa, and Satellite Tool Kit (STK), a Commercial Off-The-Shelf (COTS) tool, were used as performance modelling and assessment tools to obtain the MOP and statistically evaluate the two constellation patterns. The assessment presented in this report quantifies the MOP based on coverage, detection and tracking analysis, which SimLab exercised on a representative Area of Interest (AOI) and STK on a global scale. With most of the satellite and sensor's parameters being held constant, a comparative performance validation was conducted against both constellation patterns.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.003 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".