Feature analysis for SAR ATR

David Blacknell

doi:10.1117/12.410643

21 December 2000 Feature analysis for SAR ATR

David Blacknell

Author Affiliations +

Proceedings Volume 4173, SAR Image Analysis, Modeling, and Techniques III; (2000) https://doi.org/10.1117/12.410643
Event: Europto Remote Sensing, 2000, Barcelona, Spain

Abstract

Feature-based automatic target recognition (ATR) discriminates between target classes on the basis of the values taken by certain target features. The conventional approach is to select the best features for a particular task from a large set of features which have been pre-defined on the basis of physical intuition. A simple feature might be target area whilst a more sophisticated feature might be some measure of fractal dimension. ATR performance will be influenced by the choice of features and by the accuracy with which the statistical behaviour of these features has been characterised. This paper describes a technique which can be used to determine statistical feature behaviour despite limited examples of target realisations. It also addresses the problem of feature choice by introducing a method for assessing the information carried by different features. This leads to a potential technique for adaptive feature generation. These ideas are illustrated by application to synthetic aperture radar (SAR) images of vehicles.

Citation Download Citation

David Blacknell "Feature analysis for SAR ATR", Proc. SPIE 4173, SAR Image Analysis, Modeling, and Techniques III, (21 December 2000); https://doi.org/10.1117/12.410643

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

;

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE