Statistical analysis of navigation performance through thousands of randomized mission simulations
Monte Carlo simulation runs hundreds of missions with randomized sensor errors to characterize statistical navigation performance. This reveals mean errors, variance, worst-case scenarios, and reliability metrics. Configure sensor parameters and run large-scale simulations to understand system robustness and predict real-world performance distributions.
Monte Carlo simulation is essential for understanding real-world navigation performance where sensor characteristics vary, environmental conditions change, and random errors accumulate differently in each mission. By running thousands of simulations with randomized parameters, we can: