In this paper, we design an attractivealgorithm aiming to classify moving targets includinghuman, animal, vehicle and drone, at groundsurveillance radar systems. The non-stationary reflectedsignal of the targets is represented with a novelmathematical framework based on behavior of thesignal components in reality. We further propose usingthe generalized linear chirp transform for the analysisst...

polarimetric synthetic aperture radar (pol.-sar) allows us to implement the recognition and classification of radar targets. this article investigates the arrangement of scatterers by sar data and proposes a new look-up table of region (ltr). this look-up table is based on the combination of (entropy h/anisotropy a) and (anisotropy a/scattering mechanism α), which has not been reported up now. ...

The paper deals with Radar Target Classification based on the use of a neural network. A radar signal was acquired from the output of a J frequency band non-coherent radar. We applied the three layer feed forward neural network using backpropagation learning algorithm. We defined classes of radar targets and designated each of them by its number. Our classification process resulted in number of...

Apart from object detection, plot extraction and tracking, automatical classification is becoming one of the challenges of modern sensor systems. In civil applications for example, different classification techniques are used for air traffic control (ATC) purposes. The primary purposes of air traffic control systems are collision prevention, the organization and control of the air traffic; furt...

sar (synthetic aperture radar) image enhancement and segmentation is purpose of this thesis. sar image segmentation is a primary step before steps such as classification and target recognition. the main obstacle in sar image segmentation is inherent speckle noise. speckle noise is a multiplicative and highly destructive noise which results to intensity inhomogeneity. hence common segmentation m...

land cover classification is one of the most important applications of polarimetric radar images, especially in urban areas. there are numerous features that can be extracted from these images for the use of their high potential, hence feature selection plays an important role in polsar image classification. in this study, three main steps are used to improve the classification: 1) feature extr...

Polarimetric Synthetic Aperture Radar (Pol.-SAR) allows us to implement the recognition and classification of radar targets. This article investigates the arrangement of scatterers by SAR data and proposes a new Look-up Table of Region (LTR). This look-up table is based on the combination of (entropy H/Anisotropy A) and (Anisotropy A/scattering mechanism α), which has not been reported up now. ...

Since the improvement in Anti Radar Material technology and stealth technology grows, there are immense counter measures that have opened to deny such technologies for classification to the adversary. At the same time it is observed that radar is continuously tracking the air target. This track data represents the kinematics which can be efficiently manipulated for effective classification with...