Vessel Route Intelligence

Two questions, one model. Backwards: a vessel stopped reporting for eleven hours, where could it plausibly have been, and did it pass through anywhere that matters? Forwards: given its current course, history and the routes vessels like it take, where will it be in six hours, and what is the uncertainty around that?

Reconstruction constrains the gap with physics and precedent (the vessel’s speed and turning limits, the bathymetry it can cross, and the corridors that traffic of its type actually uses) producing not a line but a reachable region with probability across it, which is the only honest answer when the data is absent. Prediction runs the same machinery forward, learned from historical traffic, giving destination and arrival estimates with an uncertainty ellipse.

The operationally interesting consequence is acquisition cueing. Satellite passes are scarce and oceans are large; a predicted position with an uncertainty ellipse tells a surveillance operator where to look on the next pass. That closes the loop with vessel detection and turns a passive monitoring chain into a directed one, which is the difference between watching the sea and following a ship.