Optimal Beam-Space Transformation Design For Robust Data Reduction And Array Processing In Presence Of Strong Interference

This paper presents a novel algorithm for designing beam-space transformation with robust interference suppression, reducing the computation complexity, and improving the performance of applied signal processing algorithms. This approach constructs an objective function that addresses multiple performance criteria simultaneously including the in-sector estimation accuracy and the out-of-sector interference rejection capability, and then utilizes a numerical optimization paradigm to search for the solution. The algorithm is flexible, robust and data independent, which performs well in harsh environment involving a small number of snapshots and highly correlated/coherent sources. Simulation results confirm its effectiveness in the presence of strong moving interference.