In the scenario of finite sample size, the performance of the generalized sidelobe canceller (GSC) is still affected by the desired signal even if all signal sources are independent with each other. Firstly, the novel expression of weight vector of the auxiliary array is derived under the circumstances of finite sample size. Utilizing this new weight vector and considering the correlative interferences, the general expression for the interference cancellation ratio (CR) is developed. Then, the impacts of the CR performance are further analyzed for the parameters including the input signal-to-noise ratio (SNR), the auxiliary array size, the correlation coefficient between the desired signal and interference as well as the snapshots of the sample data, respectively. Some guidelines can thus be given for the practical application. Numerical simulations demonstrate the agreement between the simulation results and the analytical results.

A robust microphone array for speech enhancement and noise suppression is studied in this paper. To overcome target signal cancellation problem of conventional beamformer caused by array imperfections or reverberation effects of acoustic enclosure, the proposed microphone array adopts an arbitrary model of channel transfer function (TF) relating microphone and speech source. Since the estimation of channel TF itself is often intractable, herein, transfer function ratio (TFR) is estimated instead and used to form a suboptimal beamformer. A robust TFR estimation method is proposed based on signal subspace analysis technique against stationary or slowly varying noise. Experiments using simulated signal and actual signal recorded in a real room illustrate that the proposed method has high performance in adverse environment.