Title :
A Study of the LCMV and MVDR Noise Reduction Filters
Author :
Souden, Mehrez ; Benesty, Jacob ; Affes, Sofiene
Author_Institution :
INRS-EMT, Univ. du Quebec, Montréal, QC, Canada
Abstract :
In real-world environments, the signals captured by a set of microphones in a speech communication system are mixtures of the desired signal, interference, and ambient noise. A promising solution for proper speech acquisition (with reduced noise and interference) in this context consists in using the linearly constrained minimum variance (LCMV) beamformer to reject the interference, reduce the overall mixture energy, and preserve the target signal. The minimum variance distortionless response beamformer (MVDR) is also commonly known to reduce the interference-plus-noise energy without distorting the desired signal. In either case, it is of paramount importance to accurately quantify the achieved noise and interference reduction. Indeed, it is quite reasonable to ask, for instance, about the price that has to be paid in order to achieve total removal of the interference without distorting the target signal when using the LCMV. Besides, it is fundamental to understand the effect of the MVDR on both noise and interference. In this correspondence, we investigate the performance of the MVDR and LCMV beamformers when the interference and ambient noise coexist with the target source. We demonstrate a new relationship between both filters in which the MVDR is decomposed into the LCMV and a matched filter (MVDR solution in the absence of interference). Both components are properly weighted to achieve maximum interference-plus-noise reduction. We investigate the performance of the MVDR, LCMV, and matched filters and elaborate new closed-form expressions for their output signal-to-interference ratio (SIR) and output signal-to-noise ratio (SNR). We theoretically demonstrate the tradeoff that has to be made between noise reduction and interference rejection. In fact, the total removal of the interference may severely amplify the residual ambient noise. Conversely, totally focussing on noise reduction leads to increased level of residual interference. The proposed study is finall- - y supported by several numerical examples.
Keywords :
array signal processing; interference suppression; noise; speech processing; LCMV beamformer; LCMV noise reduction filters; MVDR beamformer; MVDR noise reduction filters; SIR; interference rejection; interference-plus-noise energy; linearly constrained minimum variance; matched filter; microphones; minimum variance distortionless response beamformer; signal-to-interference ratio; signal-to-noise ratio; speech communication system; Beamforming; interference rejection; linearly constrained minimum variance (LCMV); minimum variance distortionless response (MVDR); noise reduction; speech enhancement;
Journal_Title :
Signal Processing, IEEE Transactions on
DOI :
10.1109/TSP.2010.2051803