  A distributed MIMO radar is considered, in which the transmit and receive
antennas belong to nodes of a small scale wireless network. The transmit
waveforms could be uncorrelated, or correlated in order to achieve a desirable
beampattern. The concept of compressive sampling is employed at the receive
nodes in order to perform direction of arrival (DOA) estimation. According to
the theory of compressive sampling, a signal that is sparse in some domain can
be recovered based on far fewer samples than required by the Nyquist sampling
theorem. The DOAs of targets form a sparse vector in the angle space, and
therefore, compressive sampling can be applied for DOA estimation. The proposed
approach achieves the superior resolution of MIMO radar with far fewer samples
than other approaches. This is particularly useful in a distributed scenario,
in which the results at each receive node need to be transmitted to a fusion
center.
