Denoising for Generalized Sidelobe Canceller

The generalized sidelobe canceller (GSC) efficiently realizes the optimal linearly constrained minimum variance (LCMV) beamformer and delivers excellent beamforming results by reducing directional interference and noise. However, when the input signals are contaminated by other type of noises, such as background and diffused noises, the overall performance of GSC can be even worse than the traditional delay-and-sum beamformers. In this paper, we investigate the application of the spatially adaptive multiwavelet (MWT) denoising technique to the GSC in an environment with severe diffused noise. Comparing with the traditional scalar wavelets, the multiwavelets can better characterize the noise information in the signal such that better denoising performance can be achieved. Different approaches for integrating the GSC and the multiwavelet denoiser were studied. It is found that by adding two denoisers, one to the fixed constrained part and another to the final GSC output, an improvement of 2dB in SNR can be achieved as compared with the traditional GSC method