An Improved Super-Resolution Direction Finding Method at Subarray Level for Coherent Sources

2-D subarray level super-resolution direction finding method has an important application in phased array radar. We study the method suited for coherent sources and propose the signal model of WSF (weighting subspace fitting) algorithm at subarray level. Constructing simplified array manifolds can reduce calibration cost and expense of phased array enormously. We post-process the digital subarray outputs by bringing in weighting network and thus increase the flexibility of array processing greatly. By constructing simplified array manifold based on approximate Gaussian subarray patterns, we can overcome the limitations of the method based on DSAM (direct simplified array manifold) whose available direction estimation area can´t be changed and the sidelobe sources can´t be suppressed completely. Compared with the simplified array manifold based on the Gaussian patterns , this new constructed manifold can reduce the cost and complexity of calculation largely, with the performance of direction finding is not degraded. Simulation results demonstrate the validity of the proposed method