Compressed Sensing for MIMO Radar using SIW Antennas for High Resolution Detection

A particular challenge for modern advanced driver-assistance systems (ADAS) is improving radar resolution for optimal performance. In this paper, compressed sensing (CS) is used for radar detection of a frequency modulated continuous wave (FMCW) radar employing a multiple-input multiple-output (MIMO) array fabricated using substrate-integrated waveguide (SIW) technology. The generated virtual aperture from this SIW-MIMO radar antenna is then complemented by a sparse compressed sensing algorithm to extract the target information accurately. More specifically, an alternating direction algorithm is applied to an automotive radar scenario. The detection setup is simulated and then tested within an anechoic chamber. To the best knowledge of the authors, this work is the first to compare the compressed sensing approach to a wide range of beamformers: classic, adaptive, subspace and functional beamformers. In these trials, compressed sensing is able to identify two targets even in situations where other beamformers are not able to identify them accurately or at all.