Spatial processing technique adaptive beamforming (SPTABF) via compactly supported orthonormal wavelets

We propose a new adaptive beamformer which uses the generalized sidelobe canceller (GSC) as the underlying structure. However, unlike the traditional adaptive beamformer, which uses the time-domain least mean squares (LMS) algorithm, the new one employs the wavelet-based LMS as the adaptive scheme for adjusting the system weights. The latter, as demonstrated in the literature, can indeed yield faster convergence rate as opposed to the time-domain counterpart. In addition, the new beamformer has also incorporated the spatial smoothing technique so that it can handle the case of coherent interference. The resulting adaptive beamformer, thus, admits efficient hardware implementations as the GSC. It also exhibits a fast tracking capability, and, at the same time, works well for both noncoherent and coherent interference. Simulation results are provided to verify this new structure.