In this study, we propose a one dimensional (1D) based successive generalized sidelobe canceller (GSC) structure for the implementation of 2D adaptive beamformers using a uniform rectangular antenna array (URA). The proposed approach takes advantage of the URA feature that the 2D spatial signature of the receive signal can be decomposed into an outer product of two 1D spatial signatures. The 1D spatial signatures lie in the column and the row spaces of the receive signal matrix, respectively. It follows that the interferers can be successively eliminated by two rounds of 1D-based GSC structure. As compared to the conventional 2D-GSC structure, computer simulations show that in addition to having significantly low computational complexity, the proposed adaptive approach possesses higher convergence rate.

In this paper, we present a new approach for the design of partially adaptive broadband beamformers with the generalized sidelobe canceller (GSC) as an underlying structure. The approach designs the blocking matrix involved by utilizing a set of P-regular, M-band wavelet filters, whose vanishing moment property is shown to meet the requirement of a blocking matrix in the GSC structure. Furthermore, basing on the subband decomposition property of these wavelet filters, we introduce a new dynamic subband selection scheme succeeding the blocking matrix. The scheme only retains the principal subband components of the blocking matrix outputs based on a prescribed statistical hypothesis test and thus further reduces the dimension of weights in adaptive processing. As such, the overall computational complexity, which is mainly dictated by the dimension of adaptive weights, is substantially reduced. The furnished simulations show that this new approach offers comparable performance as the existing fully adaptive beamformers but with reduced computations.