Model-Based Filters for 3-D positioning of marine mammals using AHRS- and GPS-equipped UAVs

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.