Understanding how satellite geometry affects position accuracy is key here. Dilution of precision (DOP) tells you how the geometry of the satellites translates into potential position error. The term that covers the overall 3D position accuracy is positional dilution of precision. When this value is low, satellites are well spread out in the sky, giving the best possible geometry and the smallest potential error in your position fix. Horizontal DOP and vertical DOP refer to specific parts of the position—horizontal plane accuracy and altitude accuracy, respectively—so they don’t indicate the best overall 3D geometry. Geographic DOP isn’t a standard GPS metric, so it wouldn’t signal the best positional precision.

Navigation integrity today is expressed through protection levels, which give a quantitative bound on how large the true navigation error could be for a given probability. This bound is what you use to decide whether the current solution meets the required safety and performance standards. RAIM status, on the other hand, was a diagnostic that assessed satellite redundancy and consistency, but it doesn’t provide a numeric bound on the error itself. Because protection levels directly define the safe limits and are tied to the integrity requirements, they effectively replace relying on RAIM status alone as the basis for trusting the navigation solution. So, the statement that protection levels replace RAIM status best captures how integrity is assessed in modern navigation.

A quaternion represents attitude by encoding a 3D rotation into a four-parameter unit quaternion q = [q0, q1, q2, q3], where q0 is the scalar part and (q1, q2, q3) is the vector part, with the unit-norm constraint q0^2 + q1^2 + q2^2 + q3^2 = 1. This single object captures orientation without relying on a sequence of axis rotations, which is what Euler angles do. The main advantage is the absence of gimbal lock. Euler angles describe orientation as consecutive rotations about axes, and when the pitch approaches ±90 degrees, two axes align and one degree of freedom is lost. Quaternions avoid this singularity because they encode rotation in a way that does not depend on a specific sequence of axis rotations. Rotations are composed simply by quaternion multiplication. If you apply one rotation and then another, you multiply their quaternions to get the combined rotation. This makes the math stable and straightforward for iterative updates, which is especially important when you’re chaining many small rotations in real time. For attitude estimation using filters like an EKF, quaternions offer numerical robustness. They avoid the singularities that come with Euler angles, allow smooth interpolation between orientations (via operations like SLERP), and maintain a consistent parameterization of rotation. Normalization is easy to enforce to keep the unit-norm constraint, helping prevent drift from accumulating. In contrast, the idea that a quaternion is a scalar is incorrect, since a quaternion has four components. It doesn’t use Euler angles “under the hood,” though you can convert between representations if needed; it is a distinct, parallel representation for 3D rotations. And yes, quaternions can represent 3D rotations, so that last option doesn’t fit.

AIS data for destination and ETA is a useful reference, but it isn’t guaranteed to be accurate. These details can change with speed adjustments, new routing, port calls, or delays, and there can be delays or errors in how the data is reported or updated. Some vessels may also have AIS off or send incomplete information, and human error or intentional misreporting can occur. Because of these factors, you should treat AIS destination and ETA with caution and corroborate it with other sources like radar, direct communications with the vessel, and official port or voyage information. The other statements are too absolute: AIS is not always inaccurate, it is widely transmitted, and it isn’t guaranteed to be 100% correct at all times.