Results 1 
4 of
4
WideAngle Sparse 3D Synthetic Aperture Radar Imaging for Nonlinear Flight Paths
"... Abstract—Conventional threedimensional (3D) Fourier synthetic aperture radar (SAR) imaging requires a collection of radar returns from multiple linear passes over a scene. Image resolution is improved by increasing the extent of these passes in azimuth and elevation. Hence, high resolution imagery ..."
Abstract

Cited by 4 (3 self)
 Add to MetaCart
(Show Context)
Abstract—Conventional threedimensional (3D) Fourier synthetic aperture radar (SAR) imaging requires a collection of radar returns from multiple linear passes over a scene. Image resolution is improved by increasing the extent of these passes in azimuth and elevation. Hence, high resolution imagery requires large data collection times and storage capacity. In this work we investigate wideangle 3D SAR image reconstruction for a sparse nonlinear collection path. This collection modality requires less data acquisition time and storage capacity than conventional linear collection. Images are reconstructed from measured radar returns using ℓ1penalized leastsquares inversion. An example is presented demonstrating that images with wellresolved features can be formed using data collected along a sparse nonlinear path. I.
Sparse Methods for Model . . .
, 2012
"... In additive component model estimation problems, the number of additive components (model order) and values of the model parameters in each of the additive components are estimated. Traditional methods typically estimate parameters for a set of models with fixed order; parameter estimation is perfor ..."
Abstract
 Add to MetaCart
In additive component model estimation problems, the number of additive components (model order) and values of the model parameters in each of the additive components are estimated. Traditional methods typically estimate parameters for a set of models with fixed order; parameter estimation is performed over a continuous space when parameters are not discrete. The model order is estimated as the minimizer, over the set of fixed model orders, of a cost function compromising between signal fit to measurements and model complexity. This dissertation explores dictionarybased estimation methods for joint model order and parameter estimation. In dictionary estimation, the continuous parameter space is discretized, forming a dictionary. Each column of the dictionary is a model component at a sampled parameter value, and a linear combination of a subset of columns is used to represent the model. It is assumed that the model consists of a small number of components, and a sparse reconstruction algorithm is used to select a sparse superposition of columns to represent the signal. The number of columns selected is the estimated model order, and the parameters of each column are the
SAR Imaging from PartialAperture Data with FrequencyBand Omissions
"... We consider the problem of wideangle SAR imaging from data with arbitrary frequencyband omissions. We propose an approach that involves composite image formation through combination of subaperture images, as well as pointenhanced, superresolution image reconstruction. This framework provides a nu ..."
Abstract
 Add to MetaCart
(Show Context)
We consider the problem of wideangle SAR imaging from data with arbitrary frequencyband omissions. We propose an approach that involves composite image formation through combination of subaperture images, as well as pointenhanced, superresolution image reconstruction. This framework provides a number of desirable features including preservation of anisotropic scatterers that do not persist over the full wideangle aperture; robustness to bandwidth limitations and frequencyband omissions; as well as a characterization of the aspect dependence of scatterers. We present experimental results based on the Air Force Research Laboratory (AFRL) “Backhoe Data Dome, ” demonstrating the effectiveness of the proposed approach.
SAR Imaging from PartialAperture Data with FrequencyBand Omissions
"... We consider the problem of wideangle SAR imaging from data with arbitrary frequencyband omissions. We propose an approach that involves composite image formation through combination of subaperture images, as well as pointenhanced, superresolution image reconstruction. This framework provides a nu ..."
Abstract
 Add to MetaCart
(Show Context)
We consider the problem of wideangle SAR imaging from data with arbitrary frequencyband omissions. We propose an approach that involves composite image formation through combination of subaperture images, as well as pointenhanced, superresolution image reconstruction. This framework provides a number of desirable features including preservation of anisotropic scatterers that do not persist over the full wideangle aperture; robustness to bandwidth limitations and frequencyband omissions; as well as a characterization of the aspect dependence of scatterers. We present experimental results based on the Air Force Research Laboratory (AFRL) “Backhoe Data Dome, ” demonstrating the effectiveness of the proposed approach.