  We focus on coherent direction of arrival estimation of wideband sources
based on spatial sparsity. This area of research is encountered in many
applications such as passive radar, sonar, mining, and communication problems,
in which an increasing attention has been devoted to improving the estimation
accuracy and robustness to noise. By the development of super-resolution
algorithms, narrowband direction of arrival estimation based on gridless sparse
algorithms and atomic norm minimization has already been addressed. In this
paper, a superresolution based method is proposed for coherent direction of
arrival estimation of multiple wideband sources. First, unlike the conventional
coherent methods, we develop a new focusing method to map the subband with the
largest center frequency to the other ones, which leads to an accurate method
with no requirement for initial estimates for DOAs. Then, we introduce an
atomic norm problem by defining a new set of atoms and exploiting the signal
joint sparsity of different frequency subbands in a continuous spatial domain.
This problem is then cast as a semidefinite program, which leads to
implementing a new coherent direction of arrival estimation method with higher
resolution and more robustness to noise. Our method needs only one single
snapshot for each frequency subband, leading to a small number of snapshots for
the received wideband signal compared to the other coherent DOA techniques.
Numerical simulations show the outperformance of the proposed method compared
to the conventional ones.
