In this paper we propose a new method for solving the Automatic Aircraft Recognition (AAR) problem from a sequence of images of an unknown observed aircraft. Our method
exploits the knowledge extracted from a training image data set (a set of binary images of different aircrafts observed under three
different poses) with the fusion of information of multiple features drawn from the image sequence using Dezert-Smarandache
Theory (DSmT) coupled with Hidden Markov Models (HMM).