2-D WSF at Subarray Level Based on Ideal Patterns

2-D subarray level super-resolution finding has an important application in phased array radar. We study super-resolution methods at subarray level for coherent sources and propose the signal model of WSF (weighting subspace fitting) algorithm at subarray level. Constructing simplified array manifolds is an effective way to reduce calibration cost and expense of phased array largely. We post-process the digital subarray output by bringing in weighting network that can increase the flexibility of array processing greatly. By finding the simplified array manifold based on ideal subarray patterns, we can overcome the drawback of the direct simplified array manifold method (the available direction finding range can´t be adjusted) and suppress uninteresting sidelobe sources better. But the precision of the direction finding is decreased accordingly. Simulation results demonstrate the validity of the proposed method