Super-resolution Method for Coherent DOA Estimation of Multiple Wideband Sources

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.