  Multiple-input multiple-output (MIMO) radar has several advantages with
respect to the traditional radar array systems in terms of performance and
flexibility. However, in order to achieve high angular resolution, a MIMO radar
requires a large number of transmit and receive antennas, which increases
hardware design and computational complexities. Although spatial compressive
sensing (CS) has been recently considered for a pulsed-waveform MIMO radar with
sparse random arrays, such methods for the frequency-modulated continuous wave
(FMCW) radar remain largely unexplored. In this context, we propose a novel
multi-target localization algorithm in the range-angle domain for a MIMO FMCW
radar with a sparse array of randomly placed transmit and receive elements. In
particular, we first obtain the targets' range-delays using a discrete Fourier
transform (DFT)-based focusing operation. The target angles are then recovered
at each detected range using CS-based techniques exploiting the sparsity of the
target scene. Our simulation results demonstrate the effectiveness of the
proposed algorithm over the classical methods in detecting multiple targets
with a sparse array.
