211 research outputs found

    Modal Analysis and Synthesis of Broadband Nearfield Beamforming Arrays

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    This thesis considers the design of a beamformer which can enhance desired signals in an environment consisting of broadband nearfield and/or farfield sources. The thesis contains: a formulation of a set of analysis tools which can provide insight into the intrinsic structure of array processing problems; a methodology for nearfield beamforming; theory and design of a general broadband beamformer; and a consideration of a coherent nearfield broadband adaptive beamforming problem. To a lesser extent, the source localization problem and background noise modeling are also treated. ¶: A set of analysis tools called modal analysis techniques which can be used to a solve wider class of array signal processing problems, is first formulated. The solution to the classical wave equation is studied in detail and exploited in order to develop these techniques. ¶: Three novel methods of designing a beamformer having a desired nearfield broadband beampattern are presented. ..

    Robust Nearfield Wideband Beamforming Design Based on Adaptive-Weighted Convex Optimization

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    Nearfield wideband beamformers for microphone arrays have wide applications in multichannel speech enhancement. The nearfield wideband beamformer design based on convex optimization is one of the typical representatives of robust approaches. However, in this approach, the coefficient of convex optimization is a constant, which has not used all the freedom provided by the weighting coefficient efficiently. Therefore, it is still necessary to further improve the performance. To solve this problem, we developed a robust nearfield wideband beamformer design approach based on adaptive-weighted convex optimization. The proposed approach defines an adaptive-weighted function by the adaptive array signal processing theory and adjusts its value flexibly, which has improved the beamforming performance. During each process of the adaptive updating of the weighting function, the convex optimization problem can be formulated as a SOCP (Second-Order Cone Program) problem, which could be solved efficiently using the well-established interior-point methods. This method is suitable for the case where the sound source is in the nearfield range, can work well in the presence of microphone mismatches, and is applicable to arbitrary array geometries. Several design examples are presented to verify the effectiveness of the proposed approach and the correctness of the theoretical analysis

    Robust Near-Field Adaptive Beamforming with Distance Discrimination

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    This paper proposes a robust near-field adaptive beamformer for microphone array applications in small rooms. Robustness against location errors is crucial for near-field adaptive beamforming due to the difficulty in estimating near-field signal locations especially the radial distances. A near-field regionally constrained adaptive beamformer is proposed to design a set of linear constraints by filtering on a low rank subspace of the near-field signal over a spatial region and frequency band such that the beamformer response over the designed spatial-temporal region can be accurately controlled by a small number of linear constraint vectors. The proposed constraint design method is a systematic approach which guarantees real arithmetic implementation and direct time domain algorithms for broadband beamforming. It improves the robustness against large errors in distance and directions of arrival, and achieves good distance discrimination simultaneously. We show with a nine-element uniform linear array that the proposed near-field adaptive beamformer is robust against distance errors as large as ±32% of the presumed radial distance and angle errors up to ±20⁰. It can suppress a far field interfering signal with the same angle of incidence as a near-field target by more than 20 dB with no loss of the array gain at the near-field target. The significant distance discrimination of the proposed near-field beamformer also helps to improve the dereverberation gain and reduce the desired signal cancellation in reverberant environments

    A Microphone Array System for Multimedia Applications with Near-Field Signal Targets

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    A microphone array beamforming system is proposed for multimedia communication applications using four sets of small planar arrays mounted on a computer monitor. A new virtual array approach is employed such that the original signals received by the array elements are weighted and delayed to synthesize a large, nonuniformly spaced, harmonically nested virtual array covering the frequency band [50, 7000] Hz of the wideband telephony. Subband multirate processing and near-field beamforming techniques are then used jointly by the nested virtual array to improve the performances in reverberant environments. A new beamforming algorithm is also proposed using a broadband near-field spherically isotropic noise model for array optimization. The near-field noise model assumes a large number of broadband random noises uniformly distributed over a sphere with a finite radius in contrast to the conventional far-field isotropic noise model which has an infinite radius. The radius of the noise model, thus, adds a design parameter in addition to its power for tradeoffs between performance and robustness. It is shown that the near-field beamformers designed by the new algorithm can achieve more than 8-dB reverberation suppression while maintaining sufficient robustness against background noises and signal location errors. Computer simulations and real room experiments also show that the proposed array beamforming system reduces beampattern variations for broadband signals, obtains strong noise and reverberation suppression, and improves the sound quality for near-field targets

    Robustness and Distance Discrimination of Adaptive Near Field Beamformers

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    A robust adaptive beamformer is proposed using the near field regionally constrained adaptive approach that designs a set of linear constraints by filtering on a low rank subspace of the near field signal over a spatial region and a wide frequency band. This method can accurately control the beam-former response over the designed spatial-temporal region using a small number of linear constraint vectors and improve the robustness against target location errors. Meanwhile, this method enhances the capability of the near field beamformer in distance discrimination without additional constraints so that interference impinging at the same direction as the desired signal but at a different distance can be effectively suppressed

    A Nested Sensor Array Focusing on Near Field Targets

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    A nested virtual array subband beamforming system is proposed for applications where broadband signal targets are located within the near field of the array. Subband multirate processing and near field beamforming techniques are used jointly for the nested array to improve the performances and reduce the computational complexity. A new noise model, namely the broadband near field spherically isotropic noise model, is also proposed for the optimization design of near field beamformers. It is shown that near field beamforming is essential for better distance discrimination of near field targets, reduced beampattern variations for broadband signals, and stronger reverberation suppression

    On the sparse beamformer design

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    In designing acoustic broadband beamformers, the complexity can grow significantly when the number of microphones and the filter length increase. It is advantageous if many of the filter coefficients are zeroes so that the implementation can be executed with less computation. Moreover, the size of the array can also be pruned to reduce complexity. These problems are addressed in this paper. A suitable optimization model is proposed. Both array pruning and filter thinning can be solved together as a two-stage optimization problem to yield the final sparse designs. Numerical results show that the complexity of the designed beamformers can be reduced significantly with minimal effect on performance

    Blind Beamforming on a Randomly Distributed Sensor Array System

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    We consider a digital signal handling sensor array system, in light of haphazardly dispersed sensor node, for observation and source localization applications. In most array handling system, the sensor array geometry is settled and known and the steering array vector/complex data is utilized as a part of beam- formation. In this system, the array adjustment may be illogical because of obscure situation and introduction of the sensors with obscure frequency/spatial responses.In this project work a blind beamforming method is used by utilizing just the deliberate sensor information, to shape either an example information or a sample correlation matrix. The greatest power accumulation measure is utilized to acquire array weights from the predominant eigenvector connected with the largest eigenvalue of a matrix eigenvalue issue. A productive blind beamforming time delay appraisal of the predominant source is proposed. Source localization in light of a least squares (LS) technique for time delay estimation is additionally given. Results taking into account investigation, simulation, and measured acoustical sensor information demonstrate the viability of this beamforming system for sign upgrade and spacetime filtering
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