Radar Classification based on Extra-Trees

In this paper, we describe a new automatic target recognition
algorithm for classifying SAR images based on the PiXiT im-
age classifier. It uses randomized sub-windows extraction and
extremely randomized trees (extra-trees). This approach re-
quires very little pre-processing of the images, thereby lim-
iting the computational load. It was successfully tested on
an extended version of the public standard MSTAR database,
that includes targets of interest, false targets, and background
clutter. A misclassification rate of about three percent has
been achieved.