Abstract: Virtual Aperture Radar (VAR) imaging provides terminal phase radar imaging for an airborne weapon that can resolve multiple closely-spaced or highly correlated scatterers on a given target with a single pulse to provide an aimpoint update at a useful range to target without training data and without requiring a large aperture antenna. VAR imaging exploits the sparse, dominant-scatterer nature of man-made targets. The array manifold is constructed with a large number of basis functions that are parameterized by range or angle (or both) to target. The number of basis functions extends the capability to resolve scatterers beyond the Rayleigh resolution. However, this also makes the manifold underdetermined. A sparse reconstruction technique that places a sparsity constraint on the number of scatterers is used to solve the manifold to uniquely identify the ranges or angles to the scatterers on the target.

Abstract: Virtual Aperture Radar (VAR) imaging provides terminal phase radar imaging for an airborne weapon that can resolve multiple closely-spaced or highly correlated scatterers on a given target with a single pulse to provide an aimpoint update at a useful range to target without training data and without requiring a large aperture antenna. VAR imaging exploits the sparse, dominant-scatterer nature of man-made targets. The array manifold is constructed with a large number of basis functions that are parameterized by range or angle (or both) to target. The number of basis functions extends the capability to resolve scatterers beyond the Rayleigh resolution. However, this also makes the manifold underdetermined. A sparse reconstruction technique that places a sparsity constraint on the number of scatterers is used to solve the manifold to uniquely identify the ranges or angles to the scatterers on the target.