Automatic target recognition (ATR) algorithms are used to classify a given synthetic aperture
radar (SAR) image into one of the known target classes by using the information gleaned …

We present a compressive radar design that combines multitone linear frequency modulated
(LFM) waveforms in the transmitter with a classical stretch processor and sub-Nyquist …

We study different modeling approaches to anisotropic scattering from man-made objects to
derive novel solutions to the 3D imaging problem from multi-pass circular synthetic aperture …

In this paper, we study the problem of interrupted synthetic aperture radar (SAR) imaging
and coherent change detection (CCD) in the setting of gapped collections with missing …

The deep learning-based target recognition methods have achieved great performance in
the preceding works. Large amounts of training data with label were collected to train a deep …

A synthetic aperture radar (SAR) collects samples of the three-dimensional (3D) spatial
Fourier transform of the scene on a two dimensional conical manifold corresponding to the …

Here, the authors study the modelling of bistatic synthetic aperture radar (SAR) target
signatures. They focus on building concise models inspired by physical phenomenology that …

This paper presents a novel approach to reconstruct a unique image of an observed scene
via synthetic apertures (SA) generated by employing widely distributed radar sensors. The …

Target recognition via deep learning has achieved great performances in the preceding
works. Yet this family of method are dependent on large amounts of training data with label …

Previously, we proposed a new compressive sensing (CS) scheme for polarimetric synthetic
aperture radar (SAR) that takes advantage of antenna crosstalk. The proposed framework …