Vector Approximate Message Passing for 3D MIMO Radar

Bastian Eisele, Ali Bereyhi, Ralf R. Müller, Sundeep Rangan

Abstract: Compressive sensing has been widely used in MIMO radar to reduce the number of measurement antennas while preserving high spatial resolution. In this paper, we deal with the reconstruction of a 3D target scene in the array near-field. By modeling the depth dimension of the target as a property of the reflection coefficients, we can transform the problem of 3D target recovery into an equivalent 2D recovery task. In turn, we have to convert the measurement model to a distributed compressive sensing model to preserve the linearity of the measurement model. For this alternative problem, we develop a vector approximate message passing algorithm. We validate our proposed algorithm through numerical investigations.