Localized subspace projection

The authors explore a new data-independent rank-reduction technique, called localized subspace projection (LSP), for adaptive array processing applications. The subspace is determined solely by the desired mainbeam location and width and the a priori knowledge of the array manifold, and is therefore independent of the directional interference environment. Due to the subspace construction, the algorithm provides enhanced sidelobe control over fully adaptive patterns, while still achieving nulling performance comparable with alternative data-adaptive subspace techniques. It was found that the LSP algorithm was sensitive to array manifold errors which distort the array sidelobe pattern, and a scheme for detecting and correcting them is proposed. In addition to enhancing the robustness of the LSP technique, this detection/correction process provides a blind calibration capability (unavailable for data-adaptive subspaces) which reveals the actual (i.e. distorted) array manifold without any knowledge of the interference environment.<>