A novel wavelet-based generalized sidelobe canceller

This paper presents a novel narrowband adaptive beamformer with the generalized sidelobe canceller (GSC) as the underlying structure. The new beamformer employs the regular M -band wavelet lters in the design of the blocking matrix of the GSC, which, as justi ed analytically, can indeed block the desired signals as required, provided the wavelet lters have su ciently high regularity. Additionally, the eigenvalue spreads of the covariance matrices of the blocking matrix outputs, as demonstrated in various scenarios, decrease, thus accelerating the convergence speed of the succeeding least mean squares (LMS) algorithm. Also, the new beamformer belongs to a speci c type of partially adaptive beamformers, wherein only a portion of weights is utilized in the adaptive processing. Consequently, the computational complexity is substantially reduced as compared with previous approaches. The issues of choosing the parameters involved for superior performance are addressed as well. Simulation results are furnished to justify this new approach.