A Review on Automatic Target Recognition and Detection Approaches for SAR Images

Abstract

This paper present a comparative or survey study of object detection or target recognition techniques for synthetic aperture radar images. As know, SAR is an artificial aperture microwave radar or remote sensing equipment which has capability to capture the scene of object by millions of kilometer or where human beings not supposed to reached, generally SAR images known as satellites imaginary. Here in this paper discusses the different techniques and approaches for the target recognition and object detection for SAR imaginary and find the common problem face by the researchers during implementation of such kind of artificial intelligence. Basically ATR i.e. automatic target recognition such as oil spills, missing air-bourn, ships and object identification or recognition at polar surface where human being not supposed to be present or reached has an interested area for the any researchers. In this paper discusses the various techniques such as prescreening method, CFAR, neural networks algorithms, and supervised classifier and many other methods and find the optimal solution or method for fast automatic target recognition and object detection according of their geometry and size. Finally a unique discussion has to be done in this paper and concluded the paper topic.