Compressed sensing joint range and cross-range MIMO Radar imaging

Compressed sensing has proved key in resolving commonly sparse scenarios where MIMO Radar schemes are envisioned. This is normally addressed via cross-range imaging, equipped with a matched filter for each desired range. This paper takes a more general approach by formulating a full 3D convolution sensing matrix for joint range/cross-range imaging, while setting conditions for minimizing its corresponding mutual coherence. These conditions suggest that both the so-called complementary sequence sets, and manifold vectors allow for an extra degree of freedom in the design process. Simulations suggest that in comparison to independent Gaussian sequences, these complementary sets greatly improve robustness by reducing the system mutual coherence by an order of magnitude.