  The problem of multiple sensors simultaneously acquiring measurements of a
single object can be found in many applications. In this paper, we present the
optimal recovery guarantees for the recovery of compressible signals from
multi-sensor measurements using compressed sensing. In the first half of the
paper, we present both uniform and nonuniform recovery guarantees for the
conventional sparse signal model in a so-called distinct sensing scenario. In
the second half, using the so-called sparse and distributed signal model, we
present nonuniform recovery guarantees which effectively broaden the class of
sensing scenarios for which optimal recovery is possible, including to the
so-called identical sampling scenario. To verify our recovery guarantees we
provide several numerical results including phase transition curves and
numerically-computed bounds.
