Adaptive beamformer

About: Adaptive beamformer is a research topic. Over the lifetime, 4934 publications have been published within this topic receiving 93100 citations.

Space constrained beamforming with source PSD updates

Abstract: This paper presents a new space constrained adaptive beamformer employing an updated source power spectral density (PSD). The space constraints are used to capture the target signal spatially and to provide robustness against steering error vectors. The PSD update on the other hand ensures that the spectral information of the desired source is reflected continuously on the space constraints. As such, target signal extraction can be achieved with minimum distortion. The beamformer operates in a subband structure to allow time-frequency operation for each channel, yielding a combination of weighted spatial and temporal filters. Evaluations on real car data show that the proposed algorithm significantly improves the speech intelligibility with noise suppression level up to 21 dB.

Sparse LCMV beamformer design for suppression of ground clutter in airborne radar

Abstract: Cancellation of the ground clutter received at an airborne phased array radar is an inherently two dimensional problem. Clutter returns are Doppler shifted due to platform motion forcing the use of processors that can resolve targets in both velocity (Doppler) and azimuth. Fully adaptive processors that operate in both dimensions require prohibitively large computation so that reduced adaptive dimension, or partially adaptive processors must be considered. In conventional partially adaptive linearly constrained minimum variance (LCMV) beamformer design the approach taken has been to represent the interference subspace with some reduced set of vectors, typically the eigenvectors associated with the largest eigenvalues of the interference covariance matrix. This technique does yield good performance but will not give the optimum performance for a given partially adaptive dimension. In this paper, an off-line method for selecting the "best" degrees of freedom to be retained in a partially adaptive design is presented. The sequential algorithm described selects those degrees of freedom that best minimize the beamformer output mean square error. This approach leads to a sparse structure for the transformation matrix, which when implemented in a generalized sidelobe canceller (GSC) structure results in a reduction in the computational load. This approach also allows a reduction in the required adaptive dimension as compared to the eigenvector based approach. Illustrative examples demonstrate the effectiveness of this method.

Two-channel signal detection and speech enhancement based on the transient beam-to-reference ratio

Abstract: In reverberant and noisy environments, multichannel systems are designed for spatially filtering interfering signals coming from undesired directions. In case of incoherent or diffuse noise fields, beamforming alone does not provide sufficient noise reduction, and post-filtering is normally required. In this paper, we present a two-channel post-filtering approach for signal detection and speech enhancement. A mild assumption is made, that a desired signal component is stronger at the beamformer output than at the reference noise signal, and a noise component is stronger at the reference signal. The ratio between the transient power at the beamformer output and the transient power at the reference noise signal is used for indicating whether such a transient is desired or interfering. Experimental results demonstrate the usefulness of the proposed approach in a car environment.

Shifted sideband beamformer

Abstract: A fundamentally different time domain beamformer structure is described which can be used to process bandpass sensor signals efficiently. The beamformer operates directly on complex, frequency translated, single sideband representations of the input signals to obtain a similar representation of the beam output. Such representations are typically obtained by complex demodulation of the signals to facilitate the use of bandwidth sampling procedures. This new technique, which is referred to as the shifted sideband beamformer, is functionally a time-domain beamformer but it combines attributes of both time-domain and frequency-domain beamforming. Shifted sideband beam-forming has the advantage that beamformer vernier delay and throughput requirements depend on the frequency content of the translated band rather than of the original band. This paper discusses the potential hardware savings associated with shifted sideband beamforming in terms of analog to digital conversion, cable bandwidth, digital processing and, also, signal conditioning hardware. The impact of delay quantization on beam-pattern structure is compared for a shifted sideband and a conventional digital implementation. Beamformer throughput is also analyzed for both implementations. A further reduction in the beamformer throughput requirement is demonstrated by the use of digital interpolation in conjunction with the shifted sideband beam-forming concept.

Signal-dependent spatial filtering based on weighted-orthogonal beamformers in the spherical harmonic domain

Abstract: Spatial filtering with microphone arrays is a technique that can be utilized to obtain the signal of a target sound source from a specific direction. Typical approaches in the field of audio underperform in practical environments with multiple sound sources and diffuse sound. In this contribution, we propose a post-filtering technique to suppress the effect of interferers and diffuse sound. The proposed technique utilizes the cross-spectral estimates of the output of two beamformers to formulate a time-frequency soft masker. The beamformers' outputs are used only for parameter estimation and not for generating an audio signal. Two sets of beamformer weights, a constant and an adaptive, are applied to the microphone array signals for the parameter estimation. The weights of the constant beamformer are designed such that they provide a spatially narrow beam pattern that is time and frequency invariant, having a unity gain toward the direction of interest. The weights of the adaptive beamformer are formulated using linearly constrained optimization with the constraint of weighted orthogonality with respect to the constant beamformer weights, as well as the unity gain toward the look direction. The orthogonality constraint provides diffuse sound suppression while the unity gain distortionless response. The cross spectrum of these two beamformers provides the target energy at a given look direction for the post filter. The study focuses on compact microphone arrays with which the typical beamforming techniques feature a tradeoff between noise amplification and spatial selectivity, especially in the low frequency region. The proposed method is evaluated with instrumental measures and listening tests under different reverberation times, in dual and multitalker scenarios. The evaluation shows that the proposed method provides a better performance when compared with a previous state-of-the-art spatial filter based on cross-pattern coherence, a linearly constrained beamformer and a Wiener postfilter.