Adaptive beamformer

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

Pattern Synthesis for Arbitrary Arrays via Weight Vector Orthogonal Decomposition

Abstract: This paper presents a new scheme based on Weight vector ORthogonal Decomposition (WORD) to control the array response at a given direction and a novel WORD-based approach to pattern synthesis for arbitrary arrays. The central concept of the proposed methods stems from the adaptive array theory. More precisely, it is found that the inverse of the noise-plus-interference covariance matrix in adaptive beamforming can be regarded as a linear combination of two orthogonal projection matrices, and, accordingly, the optimal weight vector is a linear combination of two orthogonal vectors. With such an observation, the WORD scheme is developed to design the desired weight vector. It is shown that the array response at a given direction can be precisely adjusted to an arbitrary level, by simply determining appropriate combination coefficients for those two orthogonal vectors. Furthermore, a closed-form expression of the weight vector can be achieved by introducing a new cost function that measures pattern variation. By employing the WORD scheme successively, a novel approach to pattern synthesis for arbitrary arrays is devised. At each implementation step of this approach, the array pattern is adjusted in a point-by-point manner by successively modifying the weight vector. As such, both the sidelobe and mainlobe regions can be flexibly synthesized. Numerical examples are provided to demonstrate the effectiveness and flexibility of the WORD scheme in array response control at a single direction as well as pattern synthesis.

System and method for processing a signal being emitted from a target signal source into a noisy environment

Abstract: The invention relates to a system and method for processing a signal being emitted from a target signal source (20) into a noisy environment, wherein said target signal source (20) is located in a target signal source direction ζs with regard to the position of a transducer array (10), the method comprising the following steps: receiving, transforming and filtering said signal according to filter coefficients of a beamformer (30I, 30II) in order to generate at least one beamformer output signal Y'i(n), i=1 N, the filter coefficients defining a desired predetermined filter characteristic of the beamformer; and generating a control signal t(n) representing said target signal source direction ζs. It is the object of the invention to improve such a system and method in the way that clear signal reception is achieved for any target signal source direction ζs with only a minimum of computational effort and memory capacity. The object is achieved by providing adjustable filter coefficients which are generated in response to said control signal t(n) such that the beamformer (30I, 30II) has a predetermined filtering characteristic for said target signal source (20) at said target signal source direction ζs.

Microphone array signal enhancement using mixture models

Abstract: A system and method facilitating signal enhancement utilizing mixture models is provided. The invention includes a signal enhancement adaptive system having a speech model, a noise model and a plurality of adaptive filter parameters. The signal enhancement adaptive system employs probabilistic modeling to perform signal enhancement of a plurality of windowed frequency transformed input signals received, for example, for an array of microphones. The signal enhancement adaptive system incorporates information about the statistical structure of speech signals. The signal enhancement adaptive system can be embedded in an overall enhancement system which also includes components of signal windowing and frequency transformation.

Adaptive Constrained Constant Modulus Algorithm Based on Auxiliary Vector Filtering for Beamforming

Abstract: A constrained constant modulus (CCM) algorithm with the auxiliary vector filtering (AVF) technique is introduced for robust adaptive beamforming. The proposed scheme decomposes the adaptive filter into constrained (reference vector filters) and unconstrained (auxiliary vector filters) components. The weight vector is iterated by subtracting the scaling auxiliary vector from the reference vector, which are computed according to the CCM criterion. The proposed algorithm provides an iterative exchange of information between the scalar factor and the auxiliary vector, resulting in a faster convergence and an improved steady-state performance as compared with existing techniques with large filters. The convergence properties of the proposed algorithm are analyzed. Simulation results show that the proposed beamforming algorithm outperforms existing techniques and is robust against signature mismatch problems.