Motivated by the recent advances in deep learning, we lay out a vision of how deep learning
techniques can be used in radar. Specifically, our discussion focuses on the use of deep …

Due to several sources of multipath in through-wall radar sensing, such as walls, floors, and
ceilings, there could exist multipath ghosts associated with a few genuine targets in the …

Spaceborne-airborne multistatic synthetic aperture radar (SA-MuSAR) has the ability to
provide high-resolution forward-looking imagery for receivers, but it relies on careful design …

Forward-looking multi-channel synthetic aperture radar (FLMC-SAR) is of the capability to
achieve unambiguous 2-D images in the forward-looking slight direction. FLMC-SAR …

We present a novel image formation method for passive synthetic aperture radar (SAR)
imaging. The method is an alternative to widely used time difference of arrival (TDOA) or …

In recent years, the research of multistatic synthetic aperture radar (SAR) has become a hot
spot because of its great potentials in military and civil applications. However, it is inevitably …

Multistatic airborne synthetic aperture radar (MuA-SAR) systems can achieve high-
resolution imaging in a short time by fusing observation data from multiple radar platforms …

Multistatic SAR is able to observe targets from different angles simultaneously, which
enhances the information acquiring capability. However, multistatic SAR can still be affected …

The recent success of deep learning has lead to growing interest in applying these methods
to signal processing problems. This paper explores the applications of deep learning to …

In the Part 1 of this two-part study, we present a method of imaging and velocity estimation of
ground moving targets using passive synthetic aperture radar. Such a system uses a …