MIT Lincoln Laboratory is responsible for developing the ATR (automatic target recognition) system for the DARPA-sponsored SAIP program; the baseline ATR system recognizes 10 GOB (ground order of battle) targets; the enhanced version of SAIP requires the ATR system to recognize 20 GOB targets. This paper presents ATR performance results for 10and 20-target MSE classifiers using highresolution S...

Novel transform domain formulations and implementations of PCA techniques will be given. It will be shown that this new approach results in considerable computational and storage savings while yielding very high accuracy. Useful applications such as Facial and Automatic Target Recognition are given confirming the considerable performance improvement. Key-Words: Transform Domain Techniques, Prin...

Automatic Target Recognition (ATR) has become a widely researched problem due to its applicability in domains such as surveillance systems. It can be implemented on various types of images captured by different sensors. In this paper a novel framework for Automatic Target Recognition (ATR) in Synthetic Aperture Radar (SAR) imagery using Ensemble Classifier is presented. A combination of Princip...

Automatic target recognition (ATR) is a computationally intensive problem that benefits from the abilities of the Connection Machine (CM), a massively parallel computer used for data-level parallel computing. The large computational resources of the CM can efficiently handle an approach to ATR that uses parallel stereo-matching and neural-network algorithms. Such an approach shows promise as an...

FPGAs can be used to build systems for automatic target recognition (ATR) that achieve an order of magnitude increase in performance over systems built using general purpose processors. This improvement is possible because the bit-level operations that comprise much of the ATR computational burden map extremely efficiently into FPGAs, and because the specificity of ATR target templates can be l...

Although a number of object recognition techniques have been developed to process LADAR scanned terrain scenes, these techniques have had limited success in target discrimination in part due to low-resolution data and limits in available computation power. We present a pose-independent Automatic Target Detection and Recognition System that uses data from an airborne 3D imaging Ladar sensor. The...

Template-based automatic target recognition (ATR) algorithms such as the Synthetic Aperture Radar Target Location and Recognition System (STARLOS) algorithm typically use separate templates to represent target signatures for ranges of articulations, aspect, depression, and squint angles. There is a performance tradeoo between ATR accuracy and the number of templates used. We use a hybrid model/...

Recent research in the calculation and exploitation of geometric object/image relations suggests new approaches to automatic target recognition (ATR). The resulting conceptual advances have efficiently solved the geometry problem and have transformed the ATR problem into a correspondence problem. This paper provides an analysis of the elementary algorithms which exploit object/image relations a...

II In this article we introduce the subject of automatic target recognition (ATR). Interest in ATR is increasing in the defense community as the need for precision strikes in limited warfare situations becomes an increasingly important part of our defense posture. We discuss reasons for the difficulty of the ATR problem and we survey the variety of approaches that try to solve the problem. We c...

A fundamental problem facing the designers of automatic target recognition (ATR) systems is how to deal with out-of-library or non-registered targets. This research extends a mathematical programming framework that selects the optimal classifier ensemble and fusion method across multiple decision thresholds subject to classifier performance constraints. The extended formulation includes treatme...