  This letter investigates the joint recovery of a frequency-sparse signal
ensemble sharing a common frequency-sparse component from the collection of
their compressed measurements. Unlike conventional arts in compressed sensing,
the frequencies follow an off-the-grid formulation and are continuously valued
in $\left\lbrack 0,1 \right\rbrack$. As an extension of atomic norm, the
concatenated atomic norm minimization approach is proposed to handle the exact
recovery of signals, which is reformulated as a computationally tractable
semidefinite program. The optimality of the proposed approach is characterized
using a dual certificate. Numerical experiments are performed to illustrate the
effectiveness of the proposed approach and its advantage over separate
recovery.
