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Multiple-input multiple-output (MIMO) radar has several advantages withrespect to the traditional radar array systems in terms of performance andflexibility. However, in order to achieve high angular resolution, a MIMO radarrequires a large number of transmit and receive antennas, which increaseshardware design and computational complexities. Although spatial compressivesensing (CS) has been recently considered for a pulsed-waveform MIMO radar withsparse random arrays, such methods for the frequency-modulated continuous wave(FMCW) radar remain largely unexplored. In this context, we propose a novelmulti-target localization algorithm in the range-angle domain for a MIMO FMCWradar with a sparse array of randomly placed transmit and receive elements. Inparticular, we first obtain the targets' range-delays using a discrete Fouriertransform (DFT)-based focusing operation. The target angles are then recoveredat each detected range using CS-based techniques exploiting the sparsity of thetarget scene. Our simulation results demonstrate the effectiveness of theproposed algorithm over the classical methods in detecting multiple targetswith a sparse array.

Multi-target Range and Angle detection for MIMO-FMCW radar with limited antennas