Array Beamforming Algorithms Research Articles

Leakage Source Localization Method for Aerospace Composite Structures Based on U-Array Wave Velocity-Compensated Beamforming

Composite materials have been widely used in spacecraft structures. Due to the harsh environment in space, gas leakage will occur in the structure, so it is necessary to locate the leakage position in time. In this paper, a beamforming localization method based on a U-shaped sensor array is studied. The array can be divided into two subarrays, which can orientate the direction of leakage sources, respectively. To solve the problem of uneven wave velocity caused by the anisotropy of composite materials, this method modifies the relationship between wave velocity and direction and combines it with the dispersion curve to select a filtering frequency band to reduce the influence of dispersion. The experiment simulates vacuum leakage by pumping holes with a diameter of 3 mm with a vacuum pump. The results show that the U-shaped array beamforming algorithm proposed in this paper can obtain a positioning error of 2.21 cm, which provides a new idea for the structural health detection of spacecraft.

A continuous underwater bubble localization method using passive acoustic array beamforming

The bubble is an effective carrier of underwater gas leakage detection, and its rapid localization is of great significance. In this paper, a continuous underwater bubble localization method using passive acoustic array beamforming is proposed. A specific array of hydrophones was constructed to capture the bubble acoustic signal. The signal of finite length is obtained by introducing the time window. Then, the time delay compensation is carried out according to the positions of the hydrophones in the array to estimate the direction of arrival. The influence of shape, number, and aperture of the hydrophone array on the algorithm performance is studied by simulation. Moreover, the experiment was carried out in a cuboid transparent tempered glass water tank in the laboratory, and a field programmable gate array is used as the core control unit of the data processing system to complete the signal acquisition and the algorithm execution. The localization results show that the passive acoustic cross array beamforming algorithm can accurately and stably estimate the leakage direction at different positions.

N Adaptive Sparse Array Beamforming Algorithm Based on Approximate L0-norm and Logarithmic Cost

This paper introduces a constrained normalized adaptive sparse array beamforming algorithm based on approximate L0-norm and logarithmic cost (L0-CNLMLS). The proposed algorithm can control the sparsity of the array by introducing an approximate function of L0-norm. In addition, the introduction of logarithmic cost improves the stability of the algorithm as well as the convergence rate of the algorithm. The sparsity of the array can be controlled when adjusting related parameter in the proposed algorithm. Simulation results show the better performance of L0-CNLMLS compared with some conventional algorithms.

Noise Source Localization on a Small Wind Turbine Using a Compact Microphone Array with Advanced Beamforming Algorithms: Part I — A Study of Aerodynamic Noise from Blades

Small wind turbines, which are increasingly being used near residential areas, sound louder than their larger counter parts due to their close proximity to dwellings. Previous noise measurements on small scale wind turbines were performed using single microphones which only provide an overall estimate of the total noise emitted from the wind turbine. For wind turbine manufacturers trying to address the issue of noise reduction through design, the knowledge of the dominant noise source location and source mechanisms is important. This information can be obtained using a microphone array and sophisticated beamforming algorithms. In this paper we use a compact microphone array to locate and quantify noise sources on a small (8 kW) Viryd 8000 wind turbine. The results from the microphone array show that we are able to successfully locate and separate both mechanical and aerodynamic noise on the wind turbine using advanced deconvolution algorithms such as TIDY, CLEAN based on Source Coherence (CLEAN-SC), and Deconvolution Approach for Mapping Acoustic Sources (DAMAS). For frequencies above 4000 Hz, aerodynamic noise appears to be the dominant noise source and for frequencies below 3000 Hz, mechanical noise from the nacelle appears to be the dominant noise source.

A comparison between ultrasonic array beamforming and super resolution imaging algorithms for non-destructive evaluation

In this paper the total focusing method, the so called gold standard in classical beamforming, is compared with the widely used time-reversal MUSIC super resolution technique in terms of its ability to resolve closely spaced scatterers in a solid. The algorithms are tested with simulated and experimental array data, each containing different noise levels. The performance of the algorithms is evaluated in terms of lateral resolution and sensitivity to noise. It is shown that for the weak noise situation (SNR>20dB), time-reversal MUSIC provides significantly enhanced lateral resolution when compared to the total focusing method, breaking the diffraction limit. However, for higher noise levels, the total focusing method is shown to be robust, whilst the performance of time-reversal MUSIC is degraded. The influence of multiple scattering on the imaging algorithms is also investigated and shown to be small.

Application of a Beamforming Technique to the Measurement of Airfoil Leading Edge Noise

The present paper describes the use of microphone array technology and beamforming algorithms for the measurement and analysis of noise generated by the interaction of a turbulent flow with the leading edge of an airfoil. Experiments were performed using a setup in an aeroacoustic wind tunnel, where the turbulent inflow is provided by different grids. In order to exactly localize the aeroacoustic noise sources and, moreover, to separate airfoil leading edge noise from grid-generated noise, the selected deconvolution beamforming algorithm is extended to be used on a fully three-dimensional source region. The result of this extended beamforming are three-dimensional mappings of noise source locations. Besides acoustic measurements, the investigation of airfoil leading edge noise requires the measurement of parameters describing the incident turbulence, such as the intensity and a characteristic length scale or time scale. The method used for the determination of these parameters in the present study is explained in detail. To demonstrate the applicability of the extended beamforming algorithm and the experimental setup as a whole, the noise generated at the leading edge of airfoils made of porous materials was measured and compared to that generated at the leading edge of a common nonporous airfoil.

Beamforming algorithm for circular antenna array immune to multipath propagation and non-stationary interference sources

A circular antenna array beamforming algorithm with extended zeros based on using correlation function of antenna array, which should provide continuous uniform or Gaussian angular signal’s energy distribution along the given direction, is presented.

Robust adaptive beamforming algorithm based on Bayesian approach

The performance of adaptive array beamforming algorithms substantially degrades in practice because of a slight mismatch between actual and presumed array responses to the desired signal. A novel robust adaptive beamforming algorithm based on Bayesian approach is therefore proposed. The algorithm responds to the current environment by estimating the direction of arrival (DOA) of the actual signal from observations. Computational complexity of the proposed algorithm can thus be reduced compared with other algorithms since the recursive method is used to obtain inverse matrix. In addition, it has strong robustness to the uncertainty of actual signal DOA and makes the mean output array signal-to-interference-plus-noise ratio (SINR) consistently approach the optimum. Simulation results show that the proposed algorithm is better in performance than conventional adaptive beamforming algorithms.

Adaptive linearly constrained inverse QRD-RLS beamforming algorithm for moving jammers suppression

A general, linearly constrained (LC) recursive least squares (RLS) array-beamforming algorithm, based on an inverse QR decomposition, is developed for suppressing moving jammers efficiently. In fact, by using the inverse QR decomposition-recursive least squares (QRD-RLS) algorithm approach, the least-squares (LS) weight vector can be computed without back substitution and is suitable for implementation using a systolic array to achieve fast convergence and good numerical properties. The merits of this new constrained algorithm are verified by evaluating the performance, in terms of the learning curve, to investigate the convergence property and numerical efficiency, and the output signal-to-interference-and-noise ratio. We show that our proposed algorithm outperforms the conventional linearly constrained LMS (LCLMS) algorithm, and the one using the fast linear constrained RLS algorithm and its modified version.

Towed array shape estimation using frequency-wavenumber data

Towed array beamforming algorithms require accurate array shape information in order to perform properly. Very often, these algorithms assume the array is linear. Unfortunately, the mechanical forces on the array due to ship motion and sea dynamics can change the shape of the array, which degrades the performance of the beamforming algorithm. A data-driven approach to estimating the relative shape of a nominally linear array is presented. The algorithm is robust in that it optimally combines information contained in a wide band of frequencies and source bearings. At the heart of the algorithm is a maximum-likelihood (ML) estimation scheme. The Cramer-Rao lower bound is derived and compared to the performance of the ML estimator. The utility of the algorithm is verified using both simulated and actual towed array data experiments. >