Influence of Waveform Orthogonality and Array Geometry on Compressed Sensing Algorithms for CDMA MIMO Radar

Codes with good correlation properties, is a requirement for Code Division Multiple Access (CDMA) Multiple Input Multiple Output (MIMO) radar systems, for obtaining the enhanced degrees of freedom and improved target detectability. In addition, Compressed Sensing (CS) has been proven as an effective technique to ease the burden due to computational loads and mitigate waveform artifacts such as sidelobes. However, the question as to how the correlation properties of these waveforms or the choice of array geometry contribute towards the performance of CS algorithms specifically (/jointly) has not been analysed. In this paper, we present a study that investigates the influence of waveform orthogonality and array geometry as parameters influencing the CS algorithms reconstruction performance. The numerical simulations have been carried out for a CS CDMA MIMO radar reconstructing a 2D range-angle (RA) target scene with multiple targets, using different code sequences in combination with different array geometries. The results present how the right combination of array configuration and transmission waveform leads to lower estimation errors and increased success.