Beamforming Results Research Articles

Seismic Interferometry Applied to Wind Farm and Other Anthropogenic Noise Sources

Abstract Seismic noise from anthropogenic sources is investigated using data from the Autocorr Seismic Array located in the midwestern United States. The array has a linear component that extends about 29 km from north to south and a spiral subarray component to the south with a diameter of about 10 km. A motivation of the study is to identify the dominant sources of the anthropogenic noise in the area. The northernmost seismic stations of the array are located within the southern end of a large wind farm. To the south of the array, there are regularly occurring east–west running trains. However, even during times when trains are present, the frequency signatures of the wind turbines are dominant over much of the array. Because the spectral signatures do not vary for stations with differing basement depths, they are inferred to be from source effects. The interferometric results show clear south-propagating waves traveling at the Rayleigh speed inferred to be from the wind farm to the north of the array for moderate-to-large wind speeds. For lower wind speeds, less coherent signals are observed in the one-hour noise correlations, and some north-propagating waves are also present. Both north- and south-propagating waves are observed in the interferometric results for seismic stations within the wind farm. For seismic stations to the south of the wind farm, mostly south-propagating waves are observed, which are inferred to be coming from the wind farm. Using the spiral subarray, beamforming results show dominant energy from the north of the array in the direction of the wind farm for moderate-to-high wind speeds. For lower wind speeds, seismic energy from the north is no longer dominant, and seismic energy from the south and east of the array also occur.

The Effects of Vertical Correlation Characteristics on Vertical Array Gain Performance in Deep Water

Spatial correlation characteristics of sound field have significant impact on array gain. Compared with the single-sensor receiving scenario, the vertical array with multiple receivers can remarkably enhance signal-to-noise ratio and detection ability. For the large-scale vertical array deployed in the incomplete deep-water sound channel, different bathymetry conditions or source-receiver ranges lead to different vertical correlation patterns, thus leading to the variation of array gain. Based on the deep-water experimental data conducted in the South China Sea, the effects of the vertical correlation on array gain performance are studied in both the flat and the uneven bottom environments. In the flat bottom environment, three representative ranges in the direct arrival zone and first shadow zone are chosen, respectively, to analyze how vertical correlation characteristics would affect the array gain performance. In the uneven bottom environment, attention is confined to those ranges that endure significant transmission loss differences when compared with the flat bottom environment. In summary, when the correlation coefficients grow smaller, it is observed that the array gains of different beamformers decrease, along with the energy drifting away from the first few eigenvalues and dispersing on many other eigenvalue elements. At the same time, the gap between the array gain results of eigenvalue beamforming and optimal quadratic beamforming would grow wider and the effective rank of signal covariance matrix would sprawl as well. The study is of great significance to analyze and enhance vertical sonar array detection performance at different ranges under various environmental conditions in deep water.

Ray-based blind deconvolution with maximum kurtosis phase correction.

Ray-based blind deconvolution (RBD) is a method that estimates the source waveform and channel impulse response (CIR) using the ray arrival in an underwater environment. The RBD estimates the phase of the source waveform by using beamforming. However, low sampling, array shape deformation, and other factors can cause phase errors in the beamforming results. In this paper, phase correction is applied to the beamforming estimated source phase to improve RBD performance. The impulsiveness of the CIR was used as additional information to correct the initially estimated source phase. Kurtosis was used to measure impulsiveness, and the phase correction that maximized the kurtosis of the CIRs was calculated through optimization. The proposed approach is called ray-based blind deconvolution with maximum kurtosis phase correction (RBD-MKPC) and is based on a single-input multiple-output system. The RBD-MKPC was tested with several CIRs and source waveform combinations in the shallow-water acoustic variability experiment 2015 using broadband high-frequency pulses (11-31 kHz) as the source and a sparse vertical 16-element line array as receivers. The results indicate that the RBD-MKPC improves the estimation performance. In addition, from an optimization point of view and compared with other initialization methods, the proposed method showed superior convergence speed and estimation performance.

Wideband Receive Beamforming Based on 4-D Antenna Arrays With Postmodulation

A wideband receive beamforming configuration and method based on four-dimensional (4-D) antenna arrays with postmodulation is proposed. Two pairs of single-pole-triple-throw switches are utilized for beamforming at the center frequency. Postmodulation is introduced to increase the degree of freedom of 4-D antenna arrays and achieve a deep null point at the steering direction of sidebands power pattern. The reception of 16 quadrature amplitude modulation signal, whose bandwidth is larger than the time modulation frequency, is implemented by a 16-element 4-D dipole array. The results of wideband beamforming show that the sidebands power at the steering direction can be eliminated ideally, whereas the sidelobes level of averaged radiated power pattern is suppressed to a low value. The 4-D array with postmodulation shows obviously improved bit error rates performance as compared to the 4-D array with conventional beamforming method and phased arrays, which confirms that the 4-D array with postmodulation has potential advantages in the application of wideband communication systems.

Reflection imaging of complex geology in a crystalline environment using virtual-source seismology: case study from the Kylylahti polymetallic mine, Finland

Abstract. For the first time, we apply a full-scale 3D seismic virtual-source survey (VSS) for the purpose of near-mine mineral exploration. The data were acquired directly above the Kylylahti underground mine in Finland. Recorded ambient noise (AN) data are characterized using power spectral density (PSD) and beamforming. Data have the most energy at frequencies 25–90 Hz, and arrivals with velocities higher than 4 km s−1 have a wide range of azimuths. Based on the PSD and beamforming results, we created 10 d subset of AN recordings that were dominated by multi-azimuth high-velocity arrivals. We use an illumination diagnosis technique and location procedure to show that the AN recordings associated with high apparent velocities are related to body-wave events. Next, we produce 994 virtual-source gathers by applying seismic interferometry processing by cross-correlating AN at all receivers, resulting in full 3D VSS. We apply standard 3D time-domain reflection seismic data processing and imaging using both a selectively stacked subset and full passive data, and we validate the results against a pre-existing detailed geological information and 3D active-source survey data processed in the same way as the passive data. The resulting post-stack migrated sections show agreement of reflections between the passive and active data and indicate that VSS provides images where the active-source data are not available due to terrain restrictions. We conclude that while the all-noise approach provides some higher-quality reflections related to the inner geological contacts within the target formation and the general dipping trend of the formation, the selected subset is most efficient in resolving the base of formation.

Combination Complex-Valued Bayesian Compressive Sensing Method for Sparsity Constrained Deconvolution Beamforming

Several deconvolution methods have been proposed to reduce the mainlobe width and sidelobe intensity of conventional beamforming results without increasing the array aperture; however, most of them cannot perform well in the face of coherent targets. Therefore, it is discerning to deconvolve the complex-valued beamforming result rather than the beamforming intensity. However, conventional deconvolution methods focus on the beam intensity, and only a few studies have investigated complex-valued deconvolution beamforming (CDB). Considering the sparse property of the targets in practice, the CDB can be converted to a complex-valued inverse compressive sensing problem and put into the Bayesian framework. To solve it efficiently, a complex-valued Relevance-Vector-Machine (RVM) tool is used to build the complex-valued Bayesian compressive sensing (C-BCS) method that has excellent performance in terms of recovery accuracy and operating speed. However, the C-BCS method is not stable for the CDB because the point spread function is a rank deficiency matrix. To overcome this problem, we propose the combination C-BCS method that combines the block-sparse and C-BCS methods to improve the performance of solving the CDB. The simulation results proved that the proposed method performed better than intensity-based deconvolution methods for the beamforming results generated by the coherent targets. A beamforming image of a pool scene captured by a narrowband forward-looking sonar system was adopted to test various deconvolution methods, and the proposed method exhibited superiority in sidelobe suppression.

Two-station analysis of passive surface waves with continuous wavelet transform and plane-wave-based beamforming

Using the cross-correlation or cross-coherence method to extract the traveltime information of surface waves between two stations from the ambient noise seismic data has become a popular method, which is widely utilized in shallow, regional, and global-scale geophysical surveys. Different from the common-used narrow-band filter (NBF), we adopt the continuous wavelet transform (CWT) as an alternative method to measure the phase velocity from the interstation cross-correlation function (CCF). On account of the distribution of urban noisy sources it is hard to satisfy the requirement of random, stable, uncorrelated, and uniform, which usually makes the measured phase-velocity uncertain. For those surveys with an ultra-short recording time of noise, the adverse effect would be more severe. Hence, we propose to adopt the plane-wave-based beamforming (PWBB) to scan the incoming direction of surface waves based on the hypothesis of plane-wave propagation. To suppress the incoherent components during the stack of CCFs, the phase-weighted stack (PWS) technique is also included in the proposed workflow. Several synthetic tests have verified the good performance of the new method. Especially when only a few seismic sensors are arranged in the research area, the advantages of our method would be more obvious. Then, the workflow is applied to the analysis of the field noise data, which were collected at Fengman hydropower station, Jilin province, China. The beamforming result indicates that the main component of the signals is produced by the effects of river scouring under the reservoir gate. Finally, the S-wave velocity tomogram of the research area and its geological interpretation are given. All data tests demonstrate that the proposed CWT with PWBB can achieve the stable dispersion measurement from the recorded seismic data of two station.

Beamforming for measurements under disturbed propagation conditions using numerically calculated Green’s functions

Beamforming methods for sound source localization are usually based on free-field Green’s functions to model the sound propagation between source and microphones. This assumption is known to be incorrect for many industrial applications and the beamforming results can suffer from this inconsistency regarding both, main lobe width and dynamic range. The aim of this paper is to investigate whether the use of numerically calculated Green’s functions, which include the diffraction and reflection of the sound path between source and microphones, can improve the results of beamforming measurements.The current test cases of numerical and experimental investigations consist of a source placed in a short rectangular duct. The measurements are performed outside the duct in a semi-anechoic chamber. A typical example for this kind of installation is a fan with a heat exchanger.The Green’s functions for this test case are calculated numerically using the boundary element method. These tailored Green’s functions are used to calculate the corresponding beamforming steering vectors.Beamforming measurements are performed in this paper using a loudspeaker mounted in a disc as a reference source in the heat exchanger duct. The measurements are performed both with stationary and rotating disc. The stationary measurements are evaluated in the frequency domain. For the evaluation of the rotating measurements, a new beamforming method in the time domain is presented. This method also uses the stationary Green’s functions, which were calculated numerically in the frequency domain. It is also shown how the weighting of these tailored Green’s functions can be done for time domain beamforming.By means of different validation criteria it can be shown that the results with the numerical calculated Green’s functions are improved compared to free field beamforming. This is true both in the stationary and rotating case.

On the mechanisms of jet-installation noise reduction with flow-permeable trailing edges

This paper investigates the mechanisms by which flow-permeable materials provide noise reduction in an installed jet configuration. Numerical simulations are carried out with a flat plate placed in the near field of a single-stream subsonic jet (Ma=0.3 and Ma=0.5). The trailing-edge region of the plate is replaced by three different permeable structures, with different properties: a metal foam, a perforated plate and a diamond-shaped structure. Due to its complex geometry, the metal foam is modeled with an equivalent region governed by Darcy’s law. The perforated plate has the highest resistivity among all investigated configurations, whereas the metal foam and diamond inserts have similar properties. Far-field spectra show significant noise reduction when the solid trailing edge is replaced with the permeable materials, with a maximum decrease of 12 dB at St=0.12, for Ma=0.5. Beamforming results show that the dominant acoustic source is located at the solid–permeable junction for the metal foam and diamond structures, whereas the perforated one has the source positioned near the trailing edge, similarly to the solid case. A breakdown of the far-field noise generated by the plate is also performed, where the contributions from the solid and permeable sections are computed separately. The former has distinct regions in the noise spectrum, which are dominated either by surface pressure fluctuations or trailing-edge scattering. However, for the permeable region, the results point to a significant mitigation of the noise due to scattering, which is no longer the dominant mechanism in any frequency range. This is confirmed by lower values of spanwise coherence, computed from the surface pressure, for the permeable trailing edge, compared to the solid case. Therefore, the clear dominant mechanism in the permeable region of the plate is the unsteady loading to pressure wave impingement. This is verified for all investigated configurations so that even with a low permeability structure, significant noise reduction can still be achieved.

Sound localization and quantification analysis of an automotive engine cooling module

Sound emissions of an automotive engine cooling system are studied using both single-microphone directivity measurements and a rotating beamforming technique. These measurements provide reference acoustic data on such a system and some new understanding of the effect that the radiator induces on the distribution of sound sources. Indeed, the beamforming results indicate that, above the frequency limit allowed by the Rayleigh criterion, it is possible to localize and quantify the noise sources even through the heat-exchanger core. Moreover, for the investigated operating points along the fan performance curve, the sources are always distributed at the tip of the blades and, in particular, at the leading edge. The present evidence, confirmed by the similar trends of the frequency spectra with and without the heat exchanger, leads to the conclusion that the dominant sound mechanism is the turbulence-interaction noise. Nevertheless, this turbulence is produced within the gap between the fan ring and its casing rather than generated by the radiator core. The latter appears to induce negligible acoustic transmission losses but, more significantly, is found to have a minimal influence on the aerodynamic modification of sound sources for all the analyzed operating conditions.

Selection of noise sources and short-time passive surface wave imaging——A case study on fault investigation

As a comprehensive resource, geothermal energy plays an important role in local economic development. Faults that control the distribution of geothermal resources are often delineated by geophysical methods. Aiming at a geophysical task of detecting local faults, we used the multichannel analysis of passive surface-wave method and deployed three survey lines with 178 three-component seismic nodal stations in Qingtian town, Zhejiang Province, China, to record ambient noise for imaging local shear (S)-wave velocity structures. Results of time-frequency analysis and beamforming determined the periodic distribution of noise sources. Artificial noise generated around array stations during the daytime greatly reduced the quality of imaging results, while useful ambient noise for imaging came from the flowing river out of the array area at nighttime. We performed cross-coherence operation on the data recorded during nighttime. The signal of surface waves appeared clearly in the anti-causal part of virtual shot gathers, which was chosen for dispersion measurements. After inversion, totally 32 1-D S-wave velocity profiles were combined and interpolated to reveal the 2-D subsurface structure down to a depth of 1.5 km. Two main faults are observed and correspond well with the previous geological maps. Even with two-hour-long noise recordings during nighttime, the similar results are achievable. Our results demonstrated the accuracy and efficiency of passive surface wave methods in delineating local faults. In addition, the imaging test suggests that the stable and reliable result can be obtained using short-time noise recordings by choosing proper distribution of sources.

On the aeroacoustic characterization of a robust trailing-edge serration

This paper presents an experimental study on the aeroacoustics of a flat plate rig with a highly instrumented serrated trailing-edge. The role of near-field flow properties, namely, surface pressure fluctuations and spanwise coherence, in the noise suppression capability of serration is not properly understood. The results from this test rig aim to provide additional insight into the effects of the serration on the hydrodynamic field (flow field) and the scattering of the pressure waves along the trailing-edge. Despite its unconventional size, beamforming results showed a significant reduction of far-field noise over a broadband frequency range. The associated flow field is characterized by mean and spectral analyses of static and dynamic surface pressure measurements as well as hot-wire measurements. The mean pressure coefficient results and the boundary layer velocity profiles over the serrated trailing-edge showed minute differences compared to the baseline straight trailing-edge. However, the frequency-dependent energy content of the unsteady surface pressure fluctuations demonstrates an elevated energy region around the serration edges at low frequencies. Although there is an increase in the energy content of the low frequency pressure fluctuations on the serrated trailing-edge, a significant phase difference of the pressure waves is observed, which may be indicative of destructive interference. The temporal studies regarding the unsteady surface pressure fluctuations corroborate the presence of quasi-periodic large scale structures emanating from the serration edges.

Instantaneous Beam Prediction Scheme against Link Blockage in mmWave Communications

Millimeter wave (mmWave) bands formulate the standalone (SA) operation mode in the new radio (NR) access technology of 5G systems. These bands rely on beamforming architectures to aggregate antenna array gains that compensate for dynamic channel fluctuations and propagation impairments. However, beamforming results in directional transmission and reception, thus resulting in beam management challenges, foremost initial access, handover, and beam blockage recovery. Here, beam establishment and maintenance must feature ultra-low latencies in the control and data planes to meet network specifications and standardization. Presently, existing schemes rely on arrays redundancy, multi-connectivity, such as dual-beam and carrier aggregation, and out-of-band information. These schemes still suffer from prolonged recovery times and aggregated power consumption levels. Along these lines, this work proposes a fast beam restoration scheme based on deep learning in SA mmWave networks. Once the primary beam is blocked, it predicts alternative beam directions in the next time frame without any reliance on out-of-band information. The scheme adopts long short-term memory (LSTM) due to the robust memory structure, which uses past best beam observations. The scheme achieves near-instantaneous recovery times, i.e., maintaining communications sessions without resetting beam scanning procedures.

Evaluating seismic beamforming capabilities of distributed acoustic sensing arrays

Abstract. The versatility and cost efficiency of fibre-optic distributed acoustic sensing (DAS) technologies facilitate geophysical monitoring in environments that were previously inaccessible for instrumentation. Moreover, the spatio-temporal data density permitted by DAS naturally appeals to seismic array processing techniques, such as beamforming for source location. However, the measurement principle of DAS is inherently different from that of conventional seismometers, providing measurements of ground strain rather than ground motion, and so the suitability of traditional seismological methods requires in-depth evaluation. In this study, we evaluate the performance of a DAS array in the task of seismic beamforming, in comparison with a co-located nodal seismometer array. We find that, even though the nodal array achieves excellent performance in localising a regional ML 4.3 earthquake, the DAS array exhibits poor waveform coherence and consequently produces inadequate beamforming results that are dominated by the signatures of shallow scattered waves. We demonstrate that this behaviour is likely inherent to the DAS measurement principle, and so new strategies need to be adopted to tailor array processing techniques to this emerging measurement technology. One strategy demonstrated here is to convert the DAS strain rates to particle velocities by spatial integration using the nodal seismometer recordings as a reference, which dramatically improves waveform coherence and beamforming performance and warrants new types of “hybrid” array design that combine dense DAS arrays with sparse seismometer arrays.

Beamforming based extension of semi-empirical noise modelling for low-speed axial flow fans

The application of the turbulent boundary layer trailing edge (TBL-TE) noise component of the semi-empirical Brooks-Pope-Marcolini (BPM) model in an axial flow fan case study is presented herein. The spanwise distribution of the strength of the emitted TBL-TE noise was estimated using the model for various rotational speeds, taking inlet axial velocity profile measurements and two-dimensional (2D) empirical aerodynamic cascade correlations providing input data to the model. The calculated source strength distributions were compared to corrected beamforming results from phased array microphone measurements. In the frequency ranges dominated by the TBL-TE noise, the applicability of the BPM model has been confirmed to circular-arc cambered plate blades, over extensive ranges of geometrical and aerodynamic parameters.

Robust and Efficient DOA-Steered Adaptive MVDR-FROST Beamforming Model for Multi-source Low SNR Environment

In the last few years, the demand of robust beamforming techniques has been increased significantly to serve numerous purposes. However, beamforming under low Signal to Noise Ratio (SNR) condition has always been a challenging task, which becomes more tedious in case of multiple sources. On the other hand, there are numerous factors such as steering vector error or similar estimation error problems that confine the efficiency of major beamforming techniques. Classical methods employ Eigen-Value Decomposition (EVD) and Singular Value Decomposition (SVD) over covariance matrix of the received signal; however their efficiency is limited under low SNR and multi-source condition, and perform inferiorly in case of steering vector errors. Such approaches are limited to achieve optimal Direction-of-Arrival (DOA) estimation that degrades the overall performance of the beamformer. Considering all these limitations, in this research, the focus is made on designing a robust DOA estimation model, followed by a novel beamformer for 8-element Uniform Linear Array (ULA). The simulation work consists two parts DOA estimation and beamforming. Unlike classical MUSIC and ESPRIT algorithms popular for DOA estimation our proposed model exploits the propagation method based subspace method where at first covariance matrix is obtained for the received signal, which is followed by normalization and Cross-Correlation matrix estimation. The obtained correlation matrix is processed for Generalized Eigen-Value Decomposition (GEVD) that efficiently obtained (orthogonal) subspace and SOI separation to yield DOA information. This approach enables more efficient DOA estimation even under low-SNR and steering vector error conditions. After obtaining DOA information, a novel adaptive beamformer is designed by using MVDR and FROST in parallel. DOA information from proposed model is given as input to the adaptive MVDR FROST beamforming model. Exploiting dynamic Signal-to-Interference ratio (SINR) by each beamformer our proposed method introduces an adaptation model that intends to achieve higher SINR value. MATLAB 2018a based simulation confirmed the robustness of the proposed model in terms of DOA estimation and beamforming results.

The spectrogram, method of reassignment, and frequency-domain beamforming.

A smeared spectrogram is a result of the smoothing kernel in the short-time Fourier-transform (STFT). Besides the smeared energy, time and frequency phase information is also smeared, i.e., spectral components may contain imprecise phase information. The STFT is also used as the basis for more advanced signal processing techniques such as frequency-domain beamforming and cross correlation (CC). Both methods seek the delay time between signals by exploring phase-shifts in the frequency domain. Due to the inexact phase information in some of the time-frequency elements, their phase shifts are incorrect. This study re-introduces the reassigned spectrogram (RS) as a measure to fix the STFT artifacts. Moreover, it is shown that by using the RS, phase shifts can be optimized and improve beamforming and CC results. Synthetic and recorded data are used to show the advantage of using the RS in time-frequency analysis, CC, and beamforming. Results show that, subject to certain constraints, the RS provides exact time-frequency representation of deterministic signals and significantly improve CC and beamforming results. Array analysis of infrasonic signals shows that better results are obtained by either the RS- or STFT-based analysis depending on the signals' spectral components and noise levels.

Adaptive Beamforming Using Steering Vector Correction for Phased-Array Weather Radar

In December 2017, a dual-polarized (DP) phased-array weather radar (PAWR) was deployed to observe precipitation in Tokyo, Japan. The DP-PAWR has the following characteristics: high-temporal-resolution observations for a volume scan of 30 s in a 60 km range, high-density observations below a 15 km altitude, improved rain rate estimation using dual-polarimetric observations, and hydrometer classification abilities. To achieve high-temporal-resolution observations, wide transmitted waves with a beam width up to 5° are used for elevation angles. Although Fourier-domain digital beamforming can be used for receiving waves, the high sidelobe level of the antenna pattern using this type of beamforming results in substantial errors (e.g., overestimation of received power) because of ground clutter echoes. To solve this problem, an adaptive beamforming method based on the minimum mean square error (MMSE) was developed for a single-polarization phased-array radar. In this study, signal processing procedures, including the steering vector correction of real measurement data, are developed to apply the MMSE method to the DP-PAWR. The effect of phase errors and ground clutter on the dual-polarimetric parameters is evaluated via numerical simulations. Subsequently, the proposed method is applied to real measurement data of the DP-PAWR. Consequently, it is found that the clutter suppression achieved using the proposed method is clearly superior to that achieved using Fourier-domain digital beamforming.

Spatial coherence of pipe vibrations induced by an internal turbulent flow

Whereas the spatial coherence of wall pressure and vibratory fields induced by turbulent boundary layers (TBLs) on flat plates have been studied at extent, their equivalents for cylindrical structures still need further investigation. To that end, this work develops a semi-analytical model which is valid for infinite cylindrical shells filled with a heavy fluid and excited by an internal TBL. The cylindrical shell can be also coupled to two ring stiffeners that account for the flanges generally used to connect a pipe to other portions of a circuit. The cross-spectrum density (CSD) function of the shell radial accelerations is estimated from the system circumferential sensitivity functions and the CSD of the wall pressure field induced by the TBL. The spatial coherence of the pipe vibration field is therefore analysed for a pipe with and without flanges. This is of critical importance for applications such as non-intrusive techniques for detecting acoustic sources inside pipes, like beamforming using arrays of accelerometers. If the pipe conveys a flow, the beamforming efficiency can strongly deteriorate because of the background noise induced by the TBL, which pollutes the coherence signal between sensors. The effects that the spatial coherence could have on the beamforming results of a line of point sensors (accelerometers) and a ring of wire sensors (piezoelectric coiled wires) are also investigated in this paper.

Detection of Direction-Of-Arrival in Time Domain Using Compressive Time Delay Estimation with Single and Multiple Measurements.

The compressive time delay estimation (TDE) is combined with delay-and-sum beamforming to obtain direction-of-arrival (DOA) estimates in the time domain. Generally, the matched filter that detects the arrivals at the hydrophone is used with beamforming. However, when the ocean noise smears the arrivals, ambiguities appear in the beamforming results, degrading the DOA estimation. In this work, compressive sensing (CS) is applied to accurately evaluate the arrivals by suppressing the noise, which enables the correct detection of arrivals. For this purpose, CS is used in two steps. First, the candidate time delays for the actual arrivals are calculated in the continuous time domain using a grid-free CS. Then, the dominant arrivals constituting the received signal are selected by a conventional CS using the time delays in the discrete time domain. Basically, the compressive TDE is used with a single measurement. To further reduce the noise, common arrivals over multiple measurements, which are obtained using the extended compressive TDE, are exploited. The delay-and-sum beamforming technique using refined arrival estimates provides more pronounced DOAs. The proposed scheme is applied to shallow-water acoustic variability experiment 15 (SAVEX15) measurement data to demonstrate its validity.