this paper. Furthermore, besides sparsity we show that the proposed reweighted algorithm enhances resolution that is of great importance in CCS.

Notations used in this paper are as follows. $\bR$ and $\bC$ denote the sets of real and complex numbers respectively. $\bT$ denotes the unit circle $\left[0,1\right]$ by identifying the beginning and the ending points. Boldface letters are reserved for vectors and matrices. For an integer $N$, $[N]\triangleq\lbra{1,\cdots,N}$. $\abs{\cdot}$ denotes cardinality of a set, amplitude of a scalar, or determinant of a squared matrix. $\onen{\cdot}$, $\twon{\cdot}$ and $\frobn{\cdot}$ denote the $\ell_1$, $\ell_2$ and Frobenius norms respectively. $\m{A}^T$ and $\m{A}^H$ are the matrix transpose and conjugate transpose of $\m{A}$ respectively. $x_j$ is the $j$th entry of a vector $\m{x}$. Unless otherwise stated, $\m{x}_{\m{\Omega}}$ and $\m{A}_{\m{\Omega}}$ respectively reserve the entries of $\m{x}$ and the rows of $\m{A}$ indexed by a set $\m{\Omega}$. For a vector $\m{x}$, $\diag\sbra{\m{x}}$ is a diagonal matrix with $\m{x}$ being its diagonal. $\rank\sbra{\cdot}$ denotes the rank and $\tr\sbra{\cdot}$ the trace. $\m{A}\geq\m{0}$ means that $\m{A}$ is positive semidefinite (PSD).

The rest of the paper is organized as follows. Section \[sec:preliminary\] revisits preliminary gridless sparse methods that motivate this paper. Section \[sec:novelmetric\] presents a novel sparse metric for signal and 