This work tackles the problem of estimating the position of a marine mammal moving at the ocean surface by using an unmanned aerial vehicle equipped with a camera, a GPS receiver, and an attitude and heading reference system. Two Kalman filters - inserted on a multiple-model adaptive estimation framework - which use an unstable model for the target depending on an unknown parameter that must be identified (its angular speed) are proposed and compared with an extended Kalman filter.