NEA Constellation Coverage Simulator
Monte Carlo simulation to determine optimal constellation size for NEA survey coverage. Adjust parameters below and run the simulation to see coverage curves and key findings.
Simulation Parameters
20 45 70
5 yr 7 yr 10 yr
0% 5% 10%
100 500 1000
Higher = more accurate, slower
NEA Distribution
300 objects
High-value reachable
Reachable
Out of reach
Coverage vs Constellation Size
Run simulation to see coverage curve
Analysis Results
Configure parameters and run simulation to see results
Simulation Methodology
This Monte Carlo simulation generates synthetic NEA populations based on known orbital distributions and applies a greedy target assignment algorithm to estimate survey coverage.
- NEAs are prioritized by mining value (high-value M/X-type asteroids first)
- Satellites are assigned targets based on lowest delta-V cost
- Annual failure rates follow Bernoulli distribution
- Delta-V requirements use simplified Hohmann transfer approximations
Results should be interpreted as relative comparisons between constellation sizes, not absolute predictions of real-world performance.
This simulator was built to investigate research question RQ-0-3: Minimum constellation size for survey coverage
View Prospecting Satellites BOM Item