  In this paper, we address the problem of detecting multiple Noise-Like
Jammers (NLJs) through a radar system equipped with an array of sensors. To
this end, we develop an elegant and systematic framework wherein two
architectures are devised to jointly detect an unknown number of NLJs and to
estimate their respective angles of arrival. The followed approach relies on
the likelihood ratio test in conjunction with a cyclic estimation procedure
which incorporates at the design stage a sparsity promoting prior. As a matter
of fact, the problem at hand owns an inherent sparse nature which is suitably
exploited. This methodological choice is dictated by the fact that, from a
mathematical point of view, classical maximum likelihood approach leads to
intractable optimization problems (at least to the best of authors' knowledge)
and, hence, a suboptimum approach represents a viable means to solve them.
Performance analysis is conducted on simulated data and shows the effectiveness
of the proposed architectures in drawing a reliable picture of the
electromagnetic threats illuminating the radar system.
