How does ARPA predict future target positions?

• A. By applying a tracking filter using current range, bearing, and target speed/course to extrapolate positions over a prediction horizon.
• B. By using the last measured position only.
• C. By randomizing future positions to simulate uncertainty.
• D. By using own ship motion only.

Answer: (A)

ARPA predicts future target positions by applying a tracking filter that uses the current range, bearing, and target speed/course to estimate the target’s present state, then propagates that state forward in time with a motion model to generate positions over a prediction horizon. The motion model—often constant velocity or constant turn rate—describes how the target is expected to move, so the filter can forecast where the target will be at future times. Measurements are continually fed into the filter to refine the estimate and its uncertainty, improving the accuracy of the forecast. Using only the last measured position would not account for how the target is moving, randomizing future positions isn’t a method, and relying on own-ship motion alone ignores the target’s own motion.