Including misalignment as a fixed parameter in the EKF helps mitigate what?

• A. Mitigate systematic attitude and position errors.
• B. Increase measurement noise.
• C. Eliminate the need for sensors.
• D. Reduce convergence time.

Answer: (A)

Modeling misalignment as a fixed parameter means you’re explicitly estimating the constant rotation between sensor frames and the vehicle frame. This lets the EKF separate true motion from the static orientation error, so the attitude readings and the resulting position estimates are not biased by that misalignment. In practice, without this fix, the misalignment behaves like a persistent bias that the filter must absorb into attitude and position estimates, leading to systematic errors. Estimating the misalignment compensates for it, improving overall navigation accuracy. The other options don’t fit: simply increasing measurement noise degrades accuracy, sensors aren’t eliminated by modeling misalignment, and while better modeling can help convergence in some cases, the primary benefit here is removing systematic attitude and position biases.