  This paper presents a novel norm-one-regularized, consensus-based imaging
algorithm, based on the Alternating Direction Method of Multipliers (ADMM).
This algorithm is capable of imaging composite dielectric and metallic targets
by using limited amount of data. The distributed capabilities of the ADMM
accelerates the convergence of the imaging. Recently, a Compressive Reflector
Antenna (CRA) has been proposed as a way to provide high-sensing-capacity with
a minimum cost and complexity in the hardware architecture. The ADMM algorithm
applied to the imaging capabilities of the Compressive Antenna (CA) outperforms
current state of the art iterative reconstruction algorithms, such as
Nesterov-based methods, in terms of computational cost; and it ultimately
enables the use of a CA in quasi-real-time, compressive sensing imaging
applications.
