A robust adaptive beamformer for microphone arrays with a blocking matrix using constrained adaptive filters

This paper proposes a new robust adaptive beamformer a p plicable to microphone arrays. The proposed beamformer is a generalized sidelobe canceller (GSC) with a variable blocking matrix using coefficient-constrained adaptive digital filters (CCADFs). The CCADFs minimize leakage of target signal into the interference path of the GSC. Each coefficient of the CCADFs is constrained to avoid mistracking. The input signal to all the CCADFs is the output of a fixed beamformer. In multiple-input canceller, leaky ADFs are used to decrease undesirable target-signal cancellation. The proposed beamformer can allow large look-direction error with almost no degradation in interference-reduction performance and can be implemented with a small number of microphones. The maximum allowable look-direction error can be specified by the user. Simulation results show that the proposed beamformer designed to allow about 20 degrees of look-direction error can suppress interferences by more than 17dB. 1. I N T R O D U C T I O N Microphone arrays have been studied for teleconferencing, hearing aid, speech recognition, and speech enhancement, Especially adaptive microphone arrays are promising technique. They are based on adaptive beamforming such as generalized sidelobe canceller (GSC) and can attain high interference-reduction performance with a small number of microphones arranged in small space [l]. Adaptive beamformers extract the signal from the direction of arrival (DOA) specified by the steering vector, a parameter of beamforming. However, with classical adaptive beamformers based on GSC like simple Griffiths-Jim beamformer (GJBF)[2], target-signal cancellation occurs in the presence of steering-vector error. The error in the steering vector is inevitable with actual microphone arrays. Several signal processing techniques have been proposed to avoid the signal cancellation. These techniques are called robust beamformer after the fact that they are robust against errors. Unfortunately, they still have other problems such as degradation in interference-reduction performance, increase in the number of microphones, or mistracking. In this paper, a new robust adaptive beamformer to avoid these difficulties is proposed. The proposed beamformer uses a variable blocking matrix with coefficient-constrained adaptive digital filters (CCADFs). 0-7803-3 192-3/96 $5.0001996 IEEE 925 2. R O B U S T B E A M F O R M E R S BASED ON GENERALIZED SIDELOBE C A N C E L L E R A structure of the GSC with M microphones is shown in Fig.1. The GSC includes a fixed beamformer (FBF), multiple-input canceller (MC), and blocking matrix (BM). The FBF enhances the target signal. d(b ) is the output signal of the FBF a t sample index b, and zm(b) is the output signal of the m-th imicrophone ~ ( m = 0, ..., M). The MC adaptively subtracts the components correlated to the output signals ym(b) of the BM, froin the delayed output signal d ( k Q) of the FEIF, where Q is the number of delay samples for causality. The BM is a kind of spatial rejection filter. It rejects the target signal and passes interferences. If the input signals ym(b) of MC, which are the output signals of the BM, contain only interferences, the MC rejects the interferences and extract the target signal. However, if the target signal leaks in ym ( I C ) , target-signal cancellation occurs a t the MC. The BM in the simple GJBF is sensitive to the steering-vector error and easily leaks the target signal. The vector error is caused by microphone arrangement error, microphone sensitivity error, look-direction error, and so on. In the actual usage, the major factor of the steeringvector error is the look-direction error. This is because the target often changes the position by tlhe speaker movement. It is impossible to know t8he exact DOA of the target signal. Thus, the signal cancellation is an important problem. Several approaches to inhibit target-signal cancellation have been proposed[3]-[SI. Some robust beamformers introduce constraints to the adaptive algorithm in the MCs. Adaptive ailgorithms with leakage[3], noise injection[4], or norm conistraint[5] restrain the undesirable signal-cancellation. The beamformers pass the target signal in the presence of small steering-vector error. However, when they are designed to allow large look-direction error which is often required for microphone arrays, interference reduction is also restrained. Some robust beamformers use improved spatial filters in BM [3][6][7]. The filters eliminate the target signal in the presence of steering-vector error. However, they have been developed to allow small look-direction error. When they are designed to allow large look-direction error, the filters lose a lot of degrees of freedom for interference reduction. The loss in the degrees of freedom degrades interferencereduction performance or requires increase in the number of microphones. Target tracking or calibration is (another approach for