| Popis: |
The paper presents a second part of the paper: Automatic SAR Target Recognition and Pose Estimation, in which we analyze ATR, automatic target recognition. The first part deals with pose angle determination and target data base search space reduction using a variety of geometrical methods. Both papers use US Government MSTAR, public target data base released for academic research and development. SAR target images are separated by a small pose angle (between 1° and 2°). They are obtained form an air surveillance moving plane platform at a certain depression angle and at a certain distance which all produce SAR images of 1 × 1 foot pixel resolution. The objects (targets) data base consists of 100s of commercial and military vehicles, as well as wall and building structures. We focus on three typical targets which have symmetric geometry, each of different size and shape. In addition to these three real targets we also generate several synthetic targets of various symmetric shapes to serve as the ideal test cases. The target recognition analysis is based on simple first and second order statistics including correlation and stochastic processes independence analysis. This analysis is done both in spatial as well as corresponding frequency domain. The overall methodology aims at significantly reducing computational time which is of order of fractions of a second. The end result is very accurate target type determination algorithm of the order of 97–99% precision. Once the pose angle (Part 1) and ATR (Part 2) are determined, this information can be used for target tracking. The methodologies developed in this work can be also applied to other objects, such as facial recognition. Other applications are in analysis and recognition of sound effects which may be useful to police and home land security applications. |
