ÐA model-based automatic target recognition (ATR) system is developed to recognize articulated and occluded objects in Synthetic Aperture Radar (SAR) images, based on invariant features of the objects. Characteristics of SAR target image scattering centers, azimuth variation, and articulation invariants are presented. The basic elements of the new recognition system are described and performanc...

II A variety of machine intelligence (MI) techniques have been developed at Lincoln Laboratory to increase the performance reliability of automatic target recognition (ATR) systems. Useful for recognizing targets that are only marginally visible (due to sensor limitations or to the intentional concealment of the targets), these MI techniques have become integral parts of the Experimental Target...

In order to assist in the development of automation techniques for target recognition within SAR imagery, we have implemented an evaluation platform, the ATR Workbench. This will allow researchers and Geospatial Image Analysts (GIAs) to investigate the capabilities of various commercial and experimental applications, singly or in combination, as applied to the target recognition process. The pl...

Automatic target detection and recognition (ATR) requires the ability to optimally extract the essential features of an object from (usually) cluttered environments. In this regard, eecient data representation domains are required in which the important target features are both compactly and clearly represented, enhancing ATR. Since both detection and identiication are important, multidimension...

To overcome the shortcomings of traditional manual detection underwater targets in side-scan sonar (SSS) images, a real-time automatic target recognition (ATR) method is proposed this paper. This consists image preprocessing, sampling, ATR by integration transformer module and YOLOv5s (that is, TR–YOLOv5s), localization. By considering target-sparse feature-barren characteristics SSS novel TR–Y...

The standard architecture of synthetic aperture radar (SAR) automatic target recognition (ATR) consists of three stages: detection, discrimination, and classification. In recent years, convolutional neural networks (CNNs) for SAR ATR have been proposed, but most of them classify target classes from a target chip extracted from SAR imagery, as a classification for the third stage of SAR ATR. In ...

Automatic target recognition (ATR) in target search phase is very challenging because the target range and mobility are not yet perfectly known, which results in delay-Doppler uncertainty. In this paper, we firstly perform some theoretical studies on radar sensor network (RSN) design based on linear frequency modulation (LFM) waveform: (1) the conditions for waveform coexistence, (2) interferen...

Satellite-borne or aircraft-borne synthetic aperture radar (SAR) is useful for high resolution imaging analysis for terrain surface monitoring or surveillance, particularly in optically harsh environments. For surveillance application, there are various approaches for automatic target recognition (ATR) of SAR images aiming at monitoring unidentified ships or aircraft. In addition, various types...

VOLUME 10, NUMBER 2, 1997 THE LINCOLN LABORATORY JOURNAL 187 T   automatic target recognition (ATR) is to detect and recognize objects, such as tanks, in images produced by a laser radar, a synthetic-aperture radar (SAR), or an infrared or video camera. Current ATR methods are not fully automatic, relying instead on a partnership between computer processing and human analysis. Although ...