Super-Resolving Multiple Mainlobe Signals in Jamming

We present a practical, effective algorithm that uses a few (10 to 20) snapshots of uniform line array data to spatially super-resolve multiple narrowband mainlobe signals even in the presence of skirt-jammers. This is done by splitting the array into two sets of sub-apertures and beamforming the data in each set with vectors of adaptive and of fixed weights. The adaptive weights are designed to suppress interferers while preserving a signal-containing spatial-response region of interest. The fixed beams are employed to sample such spatial region and help mollify any sidelobe distortions that may be introduced by the adaptive stage. The eigenvalues of the mapping interrelating the two sets of doubly-beamformed sub-apertures provide the super-resolved spatial locations of the mainlobe signals of interest.