What is the purpose of Monte Carlo simulations in navigation performance evaluation?

• A. To assess estimator performance under uncertainty by running many randomized trials and obtaining statistics like bias, RMSE, and convergence behavior
• B. To minimize energy use
• C. To calibrate the compass
• D. To run a single scenario to completion

Answer: (A)

Monte Carlo simulations in navigation performance evaluation are about understanding how an estimator or navigation system behaves when uncertainty is present. By repeatedly simulating the system with random realizations of sensor and process noise, you create many possible runs. From these runs you collect statistics on performance across trials, such as bias (systematic error), RMSE (overall accuracy), and convergence behavior as more data or iterations are used. This approach propagates uncertainty through the model, revealing the robustness and reliability of the estimator under different noise conditions and scenarios. It’s not about minimizing energy, calibrating hardware like a compass, or completing a single scenario; it’s about characterizing performance across many possible futures to gauge typical performance and variability.