Sparse frequency diverse MIMO radar imaging

By synthesizing multiple frequency signals into a wideband signal, the frequency diverse multiple-input-multiple-output (FD-MIMO) radar has the potential to achieve higher resolution than ordinary MIMO radar. However, conventional imaging methods based on Matched Filter (MF) can not enjoy good inversion performance. From the perspective of the range angle frequency (RAF) domain, this paper analyzes the reason for the poor imaging result and derives the limit of resolution for FD-MIMO radar. Therefore, for better imaging performance, we consider to exploit the sparsity of the scatterers in the scene of interest. Unlike most existing sparse imaging methods which extract the range and angle information simultaneously, here we propose a novel approach to recover the range and angle space separately, an approach that not only has lower computer complexity but also takes the various noises of different propagation channels into consideration. For angle compression, the weighted simultaneous orthogonal matching pursuit (WSOMP) method is proposed to utilize both inter- and intra- sparsity of the echoes while taking into account the noise differences among propagation channels. For range compression, the inverse fast Fourier transform (IFFT) operation is implemented to each non-zero angle profile. Simulation results verify the effectiveness of the proposed method.