Adaptive Subspace Mappings for Super-Resolving Multiple Main-Beam Targets in Jamming
Manuel F. Fernandez, Kai‐Bor Yu · 2020
We show how to super-resolve multiple main-beam targets in the presence of interfering signals such as those due to jamming or clutter returns. This is done via low-dimensionality adaptive mappings that insert nulls at the interfering locations while preserving the target-containing spatial-response region of interest. The outputs resulting from applying such mappings to a snapshot of array data are then used to populate a couple of matrices whose generalized eigenvalues provide the super-resolved spatial locations of the main-beam signals of interest.