High-resolution Beamforming Research Articles

Construction site environmental pollution management - initiatives, innovation and research

The management of pollution, and in particular of the impact of noise and vibrations, is very important for construction activities, even more so when it comes to urban construction sites. Indeed, some operations have very significant emissive potential and it is appropriate, for the proper conduct of the activities, to adopt a certain strategy in order to control the impacts and thus ensure good acceptance of the construction by the neighborhood. Environmental monitoring is the key to achieving this dual objective: prevent pollution and communicate. This paper presents our innovative approach to localize, identify and report noise pollution on construction sites for efficient noise mitigation. More precisely, usage of acoustic high resolution beamforming is discussed to both identify predominant sources and estimate reliably their contribution to overall noise pollution captured at a given reference point by à Class I metrological device. By combining the easy-to-deploy ATD directional acoustic sensor with its 10cm aperture microphone array, with video recording for event confirmation and labelling on the highly responsive Cadence interface, we show how we can solve complex use cases for a wide range of users, from site managers to acoustic experts.

High-resolution acoustic beamforming based on genetic algorithms

A beamforming technique based on the genetic algorithm is proposed in this paper. This method reconstructs acoustic sources by exploiting the sparsity. To reduce the computational cost and speed up the implementation, a highly efficient algorithm is further developed by narrowing down the search domain for the genetic algorithm. The performance is numerically investigated through a quantitative analysis of the position and amplitude error of the recovered source, and experimentally demonstrated in acoustic imaging. For this newly established approach, the results indicate a higher resolution capability than the conventional beamforming, and better accuracy and robustness than the compressive sensing beamforming. Overall, the present work can enrich existing high-resolution beamforming methods and benefit relevant acoustic testing applications.

From ambient vibration data analysis to 1D ground-motion prediction of the Mj 5.9 and the Mj 6.5 Kumamoto earthquakes in the Kumamoto alluvial plain, Japan

We present horizontal ground motion predictions at a soft site in the Kumamoto alluvial plain for the Mj 5.9 and Mj 6.5 Kumamoto earthquakes of April 2016, in the framework of an international blind prediction exercise. Such predictions were obtained by leveraging all available information which included: (i) analysis of earthquake ground motions; (ii) processing of ambient vibration data (AMV); and (iii) 1D ground response analysis. Spectral analysis of earthquake ground-motion data were used to obtain empirical estimates of the prediction site amplification function, with evidence of an amplification peak at about 1.2 Hz. Horizontal-to-vertical spectral ratio analysis of AMV confirmed this resonance frequency and pointed out also a low-frequency resonance around 0.3 Hz at the prediction site. AMV were then processed by cross-correlation, modified spatial autocorrelation and high-resolution beamforming methods to retrieve the 1D shear-wave velocity (Vs) structure at the prediction site by joint inversion of surface-wave dispersion and ellipticity curves. The use of low frequency dispersion curve and ellipticity data allowed to retrieve a reference Vs profile down to few thousand meters depth which was then used to perform 1D equivalent-linear simulations of the M 5.9 event, and both equivalent-linear and nonlinear simulations of the M 6.5 event at the target site. Adopting quantitative goodness-of-fit metrics based on time–frequency representation of the signals, we obtained fair-to-good agreement between 1D predictions and observations for the Mj 6.5 earthquake and a poor agreement for the Mj 5.9 earthquake. In terms of acceleration response spectra, while ground-motion overpredictions were obtained for the Mj 5.9 event, simulated ground motions for the Mj 6.5 earthquake severely underestimate the observations, especially those obtained by the nonlinear approach.Graphical

A wave glider-based, towed hydrophone array system for autonomous, real-time, passive acoustic marine mammal monitoring.

An autonomous surface vehicle known as a wave glider, instrumented with a low-power towed hydrophone array and embedded digital signal processor, is demonstrated as a viable low-noise system for the passive acoustic monitoring of marine mammals. Other key design elements include high spatial resolution beamforming on a 32-channel towed hydrophone array, deep array deployment depth, vertical motion isolation, and bandwidth-efficient real-time acoustic data transmission. Using at-sea data collected during a simultaneous deployment of three wave glider-based acoustic detection systems near Stellwagen Bank National Marine Sanctuary in September 2019, the capability of a low-frequency towed hydrophone array to spatially reject noise and to resolve baleen whale vocalizations from anthropogenic acoustic clutter is demonstrated. In particular, mean measured array gain of 15.3 dB at the aperture design frequency results in a post-beamformer signal-to-noise ratio that significantly exceeds that of a single hydrophone. Further, it is shown that with overlapping detections on multiple collaborating systems, precise localization of vocalizing individuals is achievable at long ranges. Last, model predictions showing a 4× detection range, or 16× area coverage, advantage of a 32-channel towed array over a single hydrophone against the North Atlantic right whale upcall are presented for the continental shelf environment south of Martha's Vineyard.

A Low-Complexity and High-Resolution Beamformer for Portable Medical Ultrasound Imaging.

So far, researchers have proposed various methods to improve the quality of medical ultrasound imaging. However, in portable medical ultrasound imaging systems, features, such as low cost and low power consumption for battery longevity, are very important. Hence, most of the proposed algorithms have not been proper substitutes for the delay and sum (DAS) algorithm in portable clinical applications due to their high computational complexity and cost. In this article, a new algorithm is presented concentrating on reducing the computational complexity based on a technique that separates the signal from the correlated interferences to overcome the negative characteristics, particularly for portable applications such as high price, high power consumption, and off-axis clutters in the azimuth direction. Also, the proposed algorithm yields a higher contrast compared to that of the DAS algorithm while achieving a similar computation complexity order of O ( n ) similar to the DAS algorithm. Furthermore, the performed simulations confirm that the proposed method is able to achieve a better resolution almost twice as that of the filtered delay multiply and sum (F-DMAS) algorithm with the same sidelobe level.

A nonlinear beamforming for enhanced spatiotemporal sensitivity in high frame rate ultrasound flow imaging

Typically, an ultrasound flow imaging system employs the conventional delay and sum (DAS) beamformer due to its inherent low complexity. But the conventional DAS technique offers poor contrast, low imaging resolution, and limited spatiotemporal sensitivity. This article attempts to improve the spatiotemporal sensitivity of the conventional flow imaging with a novel multiply and sum based nonlinear high-resolution (NLHR) beamforming approach. The major advantages of the proposed beamformer are the harmonic generation and the enhanced coherence in beamformed signals that improve the spatiotemporal sensitivity towards flow transients. We demonstrate the proposed beamformer for a directional cross-correlation as well as an autocorrelation based velocity estimator with simulated parabolic flow profiles of different velocities and flow directions, an in-vitro rotating disk dataset, and pulsatile flow experiments. The sensitivity of NLHR beamforming towards the flow transients is validated in-vitro with a sudden reversal of flow direction and air bubble tracking experiments. The comparison between the time–frequency plots of DAS and NLHR beamforming indicates that the impulsive spatiotemporal changes induced by the flow of air bubbles are clearly characterized by nonlinear beamforming than that of DAS beamforming. Furthermore, better spatiotemporal velocity tracking of a single air bubble and a clear distinguishability between the tracking of two proximal air bubbles are observed in-vitro. Preliminary studies on the in-vivo carotid data also show comparable, if not better, results than that of the DAS algorithm. Detailed results for each test case in simulation, phantom, and in-vivo studies are available as movies with the supplementary material and online [Online Link].

An Optimal Subspace Deconvolution Algorithm for Robust and High-Resolution Beamforming.

Utilizing the difference in phase and power spectrum between signals and noise, the estimation of direction of arrival (DOA) can be transferred to a spatial sample classification problem. The power ratio, namely signal-to-noise ratio (SNR), is highly required in most high-resolution beamforming methods so that high resolution and robustness are incompatible in a noisy background. Therefore, this paper proposes a Subspaces Deconvolution Vector (SDV) beamforming method to improve the robustness of a high-resolution DOA estimation. In a noisy environment, to handle the difficulty in separating signals from noise, we intend to initial beamforming value presets by incoherent eigenvalue in the frequency domain. The high resolution in the frequency domain guarantees the stability of the beamforming. By combining the robustness of conventional beamforming, the proposed method makes use of the subspace deconvolution vector to build a high-resolution beamforming process. The SDV method is aimed to obtain unitary frequency matrixes more stably and improve the accuracy of signal subspaces. The results of simulations and experiments show that when the input SNR is less than −27 dB, signals of decomposition differ unremarkably in the subspace while the SDV method can still obtain clear angles. In a marine background, this method works well in separating the noise and recruiting the characteristics of the signal into the DOA for subsequent processing.

High-Resolution Digital Beamforming Receiver Using DDS–PLL Signal Generator for 5G Mobile Communication

This article presents a signal generator and a digital beamforming receiver (DBR) with high phase control resolution and high beam control resolution, respectively. The signal generator is designed based on a direct digital synthesizer (DDS) and a phase lock loop (PLL). In the DDS–PLL signal generator, the conventional divider in PLL is replaced with a mixer, comb generator, and a doubler to utilize high phase control resolution of DDS (14 bit, 0.022°) as it is to synchronize the DDS–PLL signal generator with the entire system. In the DBR, the output signals of the DDS–PLL signal generators are used as the second local oscillator (LO) signal, and the beamforming technique is implemented through the change of the phase of the second LO signals. Also, for sophisticated beamforming, all signal generator components in the DBR are synchronized for generating same and fixed frequency and phase. Finally, the DBR has the same phase control resolution as the DDS, and the phase of each chain of the DBR can be adjusted up to 0.022° (14 bit). The DBR using the DDS–PLL signal generator is designed and fabricated. The DBR consists of a <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$1 \times 8$ </tex-math></inline-formula> array tapered slot antenna (TSA) part, a first and second frequency conversion part, a <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$1 \times 8$ </tex-math></inline-formula> data acquisition and combiner part, DDS–PLL signal generator part, and a reference signal generator part. The phase control performance of the DBR was verified by measuring the phase change of the chain in the DBR according to the DDS phase change. Also, to verify the beamforming performance of the DBR with high beam control resolution, the radiation pattern of the DBR when the angle of the main lobe was 0°, 0.2°, 0.4°, 15°, and 30° was measured in the 28 GHz band. At the main lobe, the gain error is within 1 dB and the beam angle error is within 0.2°. The simulation results are in good agreement with the measured results. A high-resolution beamforming performance is achieved in the DBR using the DDS–PLL signal generator.

Deep learning-based direction-of-arrival estimation for multiple speech sources using a small scale array.

A high resolution direction-of-arrival (DOA) approach is presented based on deep neural networks (DNNs) for multiple speech sources localization using a small scale array. First, three invariant features from the time-frequency spectrum of the input signal include generalized cross correlation (GCC) coefficients, GCC coefficients in the mel-scaled subband, and the combination of GCC coefficients and logarithmic mel spectrogram. Then the DNN labels are designed to fit the Gaussian distribution, which is similar to the spatial spectrum of the multiple signal classification. Finally, DOAs are predicted by performing peak detection on the DNN outputs, where the maximum values correspond to speech signals of interest. The DNN-based DOA estimation method outperforms the existing high resolution beamforming techniques in numerical simulations. The proposed framework implemented with a four-element microphone array can effectively localize multiple speech sources in an indoor environment.

Fast compressive beamforming with a modified fast iterative shrinkage-thresholding algorithm.

Compressive beamforming has been successfully applied to direction-of-arrival estimation with sensor arrays. The results demonstrated that this technique achieves superior performance when compared with traditional high-resolution beamforming methods. The existing compressive beamforming methods use classical iterative optimization algorithms in their compressive sensing theories. However, the computational complexity of the existing compressive beamforming methods tend to be excessively high, which has limited the use of compressive beamforming in applications with limited computing resources. To address this issue, this paper proposes a fast compressive beamforming method which combines the shift-invariance of the array beam patterns with a fast iterative shrinkage-thresholding algorithm. The evaluation shows that the proposed fast compressive beamforming method successfully reduces the number of floating-point operations by 3 orders of magnitude when compared with the existing methods. In addition, both the simulations and experiments demonstrate that the resolution limit for discerning closely spaced sources of the introduced fast method is comparable to those of the existing compressive beamforming methods, which use classical iterative optimization algorithms.

Relation between ocean wave activity and wavefield of the ambient noise recorded in northern Poland

The temporal and spatial variations of the wavefield of ambient noise recorded at ‘13 BB star’ array located in northern Poland were related to the activity of high, long-period ocean waves generated by strong storms in the Northern Indian Ocean, the Atlantic Ocean, and the Northern Pacific Ocean between 2013 and 2016. Once pre-processed, the raw noise records in time- and frequency-domains, and spectral analysis and high-resolution three-component beamforming techniques were applied to the broadband noise data. The power spectral density was analysed to quantify the noise wavefield, observing the primary (0.04–0.1 Hz) microseism peak and the splitting of the secondary microseism into long-period (0.2–0.3 Hz) and short-period (0.3–0.8 Hz) peaks. The beam-power analysis allowed to determine the changes in the azimuth of noise sources and the velocity of surface waves. The significant wave height, obtained by combining observed data and forecast model results for wave height and period, was analysed to characterise ocean wave activity during strong storms. The comparison of wave activity and beam-power led to distinguish the sources of Rayleigh and Love waves associated to long-period microseisms, of short-period microseisms, and of primary microseisms. High, long-period ocean waves hitting the coastline were found to be the main source of noise wavefield. The source of long-period microseisms was correlated to such waves in the open sea able to reach the shore, whereas the source of primary microseisms was tied to waves interacting with the seafloor very close to the coastlines. The source of short-period microseisms was attributed to strong storms constituted of short-period waves not reaching the coast.

Multi-Operator Minimum Variance Adaptive Beamforming Algorithms Accelerated With GPU.

The goal of this work is to design high-resolution, high-contrast and robust MV adaptive beamforming algorithms, which are also implemented in real-time frame rate. Multi-operator optimization is introduced into MV adaptive beamforming in this work to propose a multi-operator MV adaptive beamforming algorithmic optimization framework. Based on the proposed algorithmic optimization framework, the algorithm optimization can be either conducted by activating a single optimization operator, or conducted by activating multiple optimization operators. The multi-operator MV (MOMV) adaptive beamforming algorithms are then derived from this framework. Moreover, in order to promote the real-time imaging capability of MOMV beamforming, a GPU-based parallel acceleration framework is proposed along with the algorithmic optimization framework by exploring the image-level coarse-grained parallelization and pixel-level fine-grained parallelization. GPU computing resource allocation strategy and memory access strategy are both explored to better design the acceleration framework. Comprehensive quantitative simulation evaluations and qualitative in vivo experiments of imaging performance are studied, and the results demonstrate that the proposed MOMV adaptive beamforming algorithms significantly improve the imaging performance as compared with other MV beamforming algorithms, which have high resolution, high contrast, good robustness, and real-time imaging capability with thousands of acceleration speedup. Furthermore, the MOMV beamforming algorithm without eigen-decomposition and projection optimization operator achieves much higher beamforming frame rate with little downgrade of image quality as compared with the MOMV beamforming algorithm with all optimization operators.

A High-Resolution and Low-Frequency Acoustic Beamforming Based on Bayesian Inference and Non-Synchronous Measurements

Beamforming is a powerful technique to achieve acoustic imaging in far-field. However, its spatial resolution is strongly blurred by the point spread function (PSF) of phased microphone array. Due to the limitation of array aperture and microphone density, the PSF is far from Dirac delta function, so that it is difficult to obtain a high-resolution beamforming image at low-frequencies (e.g.500-1500Hz). This paper proposes a Bayesian inference method based on Non-synchronous Array Measurements (Bi-NAM) so as to refine the PSF and break through the beamforming limitation for low-frequency source imaging. Firstly, by sequentially moving prototype array at different positions, the non-synchronous measurements can get a sizeable synthetic aperture and high density of microphones. The synthetic cross-spectrum matrix (CSM) can significantly improve the beamforming performance. To confine the approximation error of synthetic CSM and the uncertainty of forward model, as well as the noise interference, a Bayesian inference based on joint maximum a posterior (JMAP) is proposed to solve an ill-posed inverse problem. A Student-t prior is employed to enforce the sparse property of acoustic strength distribution. The background noise can be adaptively modeled by the Student-t distribution, which is related to some of the typical symmetric distributions. Then the hyper-parameters in JMAP inference are efficiently estimated by the Bayesian hierarchical framework. Through experimental data, the proposed Bi-NAM approach is confirmed to achieve high-resolution acoustic imaging at 1000Hz and 800Hz, respectively, even under the Laplace noise interference.

High-resolution remote acoustic localization of damage in vibrating plates

Two major challenges exist for the remote acoustic localization of damage in vibrating structures. First, the presence of damage typically results in small acoustic changes that may become “drowned out” by the majority of the sound which remains unchanged. To mitigate this, a high-resolution beamformer can be used to better resolve the acoustic sources, including the small changes (i.e., damage). However, this elicits the second challenge; many popular high-resolution beamformers exhibit poor performance in the presence of coherent sources—exactly the type of sources provided by extended, vibrating structures like a plate. To address both challenges, the Spectral Estimation Method with Coherent Background Removal (SEMCBR) is introduced, enabling the localization of small acoustic changes in a distribution of coherent sources. SEMCBR is an extension of the existing Spectral Estimation Method with Additive Noise (SEMWAN), which has previously been applied to quantify incoherent aeroacoustic sources, combined with an additional subarray averaging step to suppress coherent cross-terms. Experimental results using SEMCBR are provided for the localization of cuts, fastener faults, and delamination in 30-×-30-×-0.16 cm plates base-excited from 100–6000 Hz, using an 8-×-8 array of remote receivers. [Sponsored by NAVSEA through the NEEC and by the US DoD through an NDSEG Fellowship.]Two major challenges exist for the remote acoustic localization of damage in vibrating structures. First, the presence of damage typically results in small acoustic changes that may become “drowned out” by the majority of the sound which remains unchanged. To mitigate this, a high-resolution beamformer can be used to better resolve the acoustic sources, including the small changes (i.e., damage). However, this elicits the second challenge; many popular high-resolution beamformers exhibit poor performance in the presence of coherent sources—exactly the type of sources provided by extended, vibrating structures like a plate. To address both challenges, the Spectral Estimation Method with Coherent Background Removal (SEMCBR) is introduced, enabling the localization of small acoustic changes in a distribution of coherent sources. SEMCBR is an extension of the existing Spectral Estimation Method with Additive Noise (SEMWAN), which has previously been applied to quantify incoherent aeroacoustic sources, combine...

Performance analysis of sparse and small arrays

Horizontal arrays are often used to detect/separate a weak signal and estimate its direction of arrival among many loud interfering sources and ambient noise. Conventional beamforming (CBF) is robust but suffers from fat beams and high level sidelobes. To improve performance, either high resolution beamforming is used, which has its own problems, or one needs to increase the array aperture, hence requiring more elements on the array. To reduce the cost, sparse and/or nested arrays have been proposed, such as the coprime arrays, to achieve approximately the same aperture, and hence the same beam resolution with a less number of elements. For sonar arrays, deconvolution is shown to yield an unique solution as opposed to, say, image processing. For coprime array, deconvolution algorithm is shown to yield a narrower beam width, lower sidelobe levels and higher array gain than the product or min processing, Deconvolution is shown to yield superdirectivity and supergain for a small array. This raises new research issues about optimal array configuration design.

Aeroacoustic source localization and source level estimation during wind tunnel testing of a flat plate with and without a gap

Acoustic measurements in wind tunnels are notoriously difficult because of machinery noise from the tunnel, and aeroacoustic noise generated within the tunnel and by the test model; and because the potentially-weak signals of interest may share a common frequency range with these noise sources. Thus, when model changes are made, localizing any new aeroacoustic source(s) and determining their level(s) are challenging tasks. This presentation provides such experimental results for the aeroacoustic source associated with addition of a 6 mm gap in a 0.5-m-by-1.0-m flat plate aligned with the flow direction. When present, the gap was located 0.40-m from the plate’s leading edge. The measurements were collected in the Anechoic Flow Facility of the Naval Surface Warfare Center – Carderock Division at nominal air speeds of 19 and 30 m/s using a ∼0.6-m-diameter spiral microphone array with 24 elements placed 1.24 m from the plate and separated from the air flow by a thin barrier. Measurements in the 4-to-12 kHz frequency range were processed using conventional and high-resolution beamforming methods with and without noise-reference subtraction. Source location and level estimation for the gap-induced aeroacoustic sound source was successful at nominal signal-to-noise ratios of –20 dB. [Work supported by NAVSEA through the NEEC.]

Image improvement in linear-array photoacoustic imaging using high resolution coherence factor weighting technique

BackgroundIn Photoacoustic imaging (PAI), the most prevalent beamforming algorithm is delay-and-sum (DAS) due to its simple implementation. However, it results in a low quality image affected by the high level of sidelobes. Coherence factor (CF) can be used to address the sidelobes in the reconstructed images by DAS, but the resolution improvement is not good enough, compared to the high resolution beamformers such as minimum variance (MV). In this paper, it is proposed to use high-resolution-CF (HRCF) weighting technique in which MV is used instead of the existing DAS in the formula of the conventional CF.ResultsThe higher performance of HRCF is proved numerically and experimentally. The quantitative results obtained with the simulations show that at the depth of 40 mm, in comparison with DAS+CF and MV+CF, HRCF improves the full-width-half-maximum of about 91% and 15% and the signal-to-noise ratio about 40% and 14%, respectively.ConclusionProposed method provides a high resolution along with a low level of sidelobes for PAI.

Angle-Domain Approach for Parameter Estimation in High-Mobility OFDM With Fully/Partly Calibrated Massive ULA

In this paper, we consider a downlink orthogonal frequency division multiplexing (OFDM) system from a base station to a high-speed train (HST) equipped with fully/partly calibrated massive uniform linear antenna-array (ULA) in wireless environments with abundant scatterers. Multiple Doppler frequency offsets (DFOs) stemming from intensive propagation paths together with transceiver oscillator frequency offset (OFO) result in a fast time-varying frequency-selective channel. We develop an angle domain carrier frequency offset (CFO, general designation for DFO and OFO) estimation approach. A high-resolution beamforming network is designed to separate different DFOs into a set of parallel branches in angle domain such that each branch is mainly affected by a single dominant DFO. Then, a joint estimation algorithm for both maximum DFO and OFO is developed for fully calibrated ULA. Next, its estimation mean square error (MSE) performance is analyzed under inter-subarray mismatches. To mitigate the detrimental effects of inter-subarray mismatches, we introduce a calibration-oriented beamforming parameter (COBP) and develop the corresponding modified joint estimation algorithm for partly calibrated ULA. Moreover, the Cramer-Rao lower bound of CFO estimation is derived. Both theoretical and numerical results are provided to corroborate the proposed method.

Smart Ocean: A New Fast Deconvolved Beamforming Algorithm for Multibeam Sonar

A new fast deconvolved beamforming algorithm is proposed in this paper, and it can greatly reduce the computation complexity of the original Richardson–Lucy (R–L algorithm) deconvolution algorithm by utilizing the convolution theorem and the fast Fourier transform technique. This algorithm makes it possible for real-time high-resolution beamforming in a multibeam sonar system. This paper applies the new fast deconvolved beamforming algorithm to a high-frequency multibeam sonar system to obtain a high bearing resolution and low side lobe. In the sounding mode, it restrains the tunnel effect and makes the topographic survey more accurate. In the 2D acoustic image mode, it can obtain clear images, more details, and can better distinguish two close targets. Detailed implementation methods of the fast deconvolved beamforming are given, its computational complexity is analyzed, and its performance is evaluated with simulated and real data.

Deconvolved conventional beamforming applied to the SWellEx96 data

Horizontal arrays are often used to detect/separate a weak signal and estimate its direction of arrival among many loud interfering sources and ambient noise. Conventional beamforming (CBF) is robust but suffers from fat beams and high level sidelobes. High resolution beamforming such as minimum-variance distortionless-response (MVDR) yields narrow beam widths and low sidelobe levels but is sensitive to signal mismatch and requires many snapshots of data to estimate the signal covariance matrix, which can be a problem for a moving source. Deconvolution algorithm used in image de-blurring was applied to the conventional beam power of a uniform line array (spaced at half-wavelength) to avoid the instability problems of common deconvolution methods and demonstrated with real data (T. C. Yang, IEEE J. Oceanic Eng., 43, 160–172, 2018). The deconvolved beam output yields narrow beams, and low sidelobe levels similar to MVDR and at the same time retains the robustness of CBF. It yields a higher output signal-to-noise ratio than MVDR for isotropic noise. The method is applied here to the horizontal array data collected during the SWellEx96 experiment. Bearing time record are created to compare the performance of various beamforming methods and used to track the source position.