  In this work, we investigate sensing parameter estimation in the presence of
clutter in perceptive mobile networks (PMNs) that integrate radar sensing into
mobile communications. Performing clutter suppression before sensing parameter
estimation is generally desirable as the number of sensing parameters can be
signiffcantly reduced. However, existing methods require high-complexity
clutter mitigation and sensing parameter estimation, where clutter is ffrstly
identiffed and then removed. In this correspondence, we propose a much simpler
but more effective method by incorporating a clutter cancellation mechanism in
formulating a sparse signal model for sensing parameter estimation.
  In particular, clutter mitigation is performed directly on the received
signals and the unitary approximate message passing (UAMP) is leveraged to
exploit the common support for sensing parameter estimation in the formulated
sparse signal recovery problem. Simulation results show that, compared to
state-of-theart methods, the proposed method delivers signiffcantly better
performance while with substantially reduced complexity.
