  This work deals with the problem of uplink communication and localization in
an integrated sensing and communication system, where users are in the near
field (NF) of antenna aperture due to the use of high carrier frequency and
large antenna arrays at base stations. We formulate joint NF signal detection
and localization as a problem of recovering signals with a sparse pattern. To
solve the problem, we develop a message passing based sparse Bayesian learning
(SBL) algorithm, where multiple unitary approximate message passing
(UAMP)-based sparse signal estimators work jointly to recover the sparse
signals with low complexity. Simulation results demonstrate the effectiveness
of the proposed method.
