This work presents the first experimental demonstration of the virtual bandwidth synthetic aperture radar (VB-SAR) imaging scheme. VB-SAR is a newly-developed subsurface imaging technique which, in stark contrast to traditional close-proximity ground penetrating radar (GPR) schemes, promises imaging from remote standoff platforms such as aircraft and satellites. It specifically exploits the dif...

A method for specckle removal in Synthetic Aperture Radar (SAR) images based on wavelets filters is presented. Our method is applied to SAR signals prevously to proceed to the imaging of the data. The spatial resolution and image details are strongly enhanced, without ’blurring’ effects.

Synthetic Aperture Radar (SAR) currently has problems in the processing that lead to smearing of the image. We have developed a new method of processing the data using maximum likelihood theory that will remove the smearing leading to superior images. The goal of this project was to write a MATLAB program to simulate a SAR system to test the new processing method.

This paper presents numeric simulations related to sensing through the wall radar technologies. Our computational approaches include the Finite Difference Time Domain (FDTD) algorithm and the shooting and bouncing ray technique (Xpatch). We analyze the radar signatures of the human body and other objects, in free-space and inside a room. The emphasis is on radar scattering phenomenology, with r...

Based on Canadian Satellite (RADARSAT) synthetic aperture radar (SAR) images and simulations from a radar-backscattering model, we determined that conventional wet snow-mapping algorithms should perform optimally for a snowpack with a liquid-water content 3%, at low incidence angle ( = 20–30 ) and for a rather smooth surface (rms height ≤ 2.1 mm).

The least-mean-square (LMS) adaptive filter is applied to suppress narrow-band radiofrequency interference (R.FI) in wideband synthetic aperture radar (SAR.) signals. Simulation is used to show the working principles of the adaptive filter and to obtain the optimum filter's parameters. The algorithm is tested with P-band synthetic aperture radar (SAR.) data collected by the NASA/JPL airborne SA...

In this paper, radar target classification based on Synthetic Aperture Radar (SAR) images is investigated. Different criteria for extracting features from MSTAR data are presented, and classification rates shown, emphasizing where the useful information in terms of recognition resides. The combination of different features is also examined, linking the classification accuracy of the system to t...

This paper presents despeckling and information extraction using non-quadratic regularization. The novelty of this paper is that instead of the Gaussian prior model a Gauss-Markov random field model is chosen, because it can efficiently model textures in the images. The iterative procedure consist of noise-free image and texture parameter. The experimental results show that the proposed method ...

Introduction Outcomes attributable to the research funded through the 2005 NCPPT grant can be summarized as follows: 1) Protocols for the detection of archaeological sites through the analysis of commercially available synthetic aperture radar (SAR) and multispectral images. Previously existing protocols for site detection through image analysis had utilized images generated from synthetic aper...

This work deals with unsupervised image deblurring. We present a new deblurring procedure on images provided by lowresolution synthetic aperture radar (SAR) or simply by multimedia in presence of multiplicative (speckle) or additive noise, respectively. The method we propose is defined as a two-step process. First, we use an original technique for noise reduction in wavelet domain. Then, the le...