In this work we present a new algorithm that enable to perform automatic target recognition (ATR) in high-resolution synthetic aperture radar (SAR) data. According to the microwave backscattering theory and the three-dimension model of target, we calculate radar cross section (RCS) and correspondingly obtain the high resolution inverse synthetic aperture radar (ISAR) image of target. In order t...

This effort advanced the art of applying Grenander’s pattern theory to automatic target recognition (ATR) problems. We extended jump-diffusion ATR algorithms to accommodate unknown infrared camera calibration effects and include more stable diffusion procedures for pose refinement, and developed flexible shape models to accommodate clutter. We also developed performance bounds on estimation and...

AUTOMATIC target recognition (ATR) generally refers to the autonomous or aided target detection and recognition by computer processing of data from a variety of sensors such as forward looking infrared (FLIR), synthetic aperture radar (SAR), inverse synthetic aperture radar (ISAR), laser radar (LADAR), millimeter wave (MMW) radar, multispectral/hyperspectral sensors, low-light television (LLTV)...

Automatic target recognition (ATR) involves processing images for detecting, classifying, and tracking targets embedded in a background scene. This paper presents an algorithm for detecting a specified set of target objects embedded in visual images for an ATR application. The developed algorithm employs a novel technique for automatically detecting man-made and non-manmade single, two, and mul...

Microwave imaging techniques, in particular synthetic aperture radar (SAR), are able to obtain useful images even in adverse weather or darkness, which makes them suitable for target position or feature estimation. However, typical SAR imagery is not informative for the operator, because it is synthesized using complex radio signals with greater than 1.0 m wavelength. To deal with the target id...

In this paper, the structural risk minimization (SRM) criterion is employed to train a large margin classifier, the support vector machine (SVM). Its relative performance is compared with traditional classifiers employing hyperplanes against a realistic difficult problem, the synthetic aperture radar (SAR) automatic target recognition (ATR). In most pattern recognition applications, the task is...

Traditional methods for ATR (Automatic Target Recognition) use infrared (IR) sensors for detecting heat emanating from targets. IR-based ATR techniques are susceptible to sensor-induced errors; for instance, targets may not be detected if they are cold (when vehicle engines are turned o ), or when the background is hot (on a hot day). This work presents an approach to real-time color-based ATR ...

Among the applications of a radar system, target classification for ground surveillance is one of the most widely used. This paper deals with micro-Doppler Signature (μ-DS) based radar Automatic Target Recognition (ATR). The main goal for performing μ-DS classification using speech processing tools was to investigate whether automatic speech recognition (ASR) techniques are suitable methods for...

Automating the process of term recognition and classi cation is important for digital libraries. Automatic Term Recognition (ATR) has many applications in areas related to digital libraries, e.g. information retrieval and extraction from the web, summarisation, machine translation, dictionary construction etc. Automatic term classi cation attracts the interest of researchers following the steps...

This paper presents a novel double weight-based synthetic aperture radar (SAR) and infrared (IR) sensor fusion method (DW-SIF) for automatic ground target recognition (ATR). IR-based ATR can provide accurate recognition because of its high image resolution but it is affected by the weather conditions. On the other hand, SAR-based ATR shows a low recognition rate due to the noisy low resolution ...