Limited Aperture Research Articles

Acoustic Gaussian-Airy beams

Acoustic Airy beams as non-diffractive beams possess self-bending, self-healing, and non-diffraction virtues and are expected to have great potential in applications like ultrasonic imaging. Here an analytical theory is provided for Gaussian modulated Airy (gAiry) acoustic beams. It is revealed through numerical calculations and finite element simulations that gAiry beams inherit the merits mentioned above of standard Airy beams. In theoretically predicted and more practical cases where sources of limited apertures generate beams, reduction of side lobes is found in gAiry fields, while bilateral focusing using a pair of beams shows improved field features when compared with focused Airy fields. The theories and observations here can help deploy gAiry beams in applications.

Conceptual design and performance predictions for 2D beam emission spectroscopy turbulence measurements at Wendelstein 7-X

A conceptual design for a 2D beam emission spectroscopy diagnostic system to measure ion gyro-scale plasma turbulence at Wendeslstein 7-X is described. The conceptual design identifies field-aligned viewing geometries and ports for cross-field turbulence measurements in the neutral beam volume. A 2D sightline grid covers the outer plasma region, and the grid configuration provides sufficient k-space coverage in radial and poloidal directions for ion temperature gradient and trapped-electron mode turbulence measurements. Emission intensity estimates, optical transmission losses, and detector noise levels indicate that the measurements will be sensitive to plasma density fluctuations as small as δn/n ≈ 0.5% with a bandwidth of 1MHz. Implementation challenges include a small beam emission Doppler shift due to nearly radial heating beams and reduced optical throughput due to collection aperture limitations.

High‐Resolution Programmable Metasurface Imager Based on Multilayer Perceptron Network

AbstractIn the data‐driven society, fidelity and accuracy of automatic decisions behind the scene rely fundamentally on a solid data or imaging acquisition system. However, conventional microwave imagers are inadequate relating to their resolution and noise capability, mainly due to the limited aperture size and rigid working principle. Here, a programmable metasurface imager with high‐resolution and anti‐interference performance is proposed. By implementing the structure of multilayer perceptron network in the analog domain, the metasurface‐based microwave imager intelligently adapts to different datasets through illuminating a set of designed scattering patterns that mimic the feature patterns. A prototype imager system working at microwave frequency is designed and fabricated. The accuracy rate rises by 18% under the classification task of MNIST dataset, with a decline in the reconstruction imaging error. The authors experimentally demonstrate that the resolution to distinguish strip patterns goes beyond to one‐fifth of the equivalent wavelength on the target plane.

Downhole microseismic data interpretation for media anisotropy evaluation with limited acquisition geometry in Western Siberia

We have evaluated the results of processing and interpretation for one of the first projects in Russia for downhole microseismic monitoring of hydraulic fracturing in Western Siberia. The data are characterized by large distance to the acquisition array and noisy recordings. We illustrate that preliminary quality control of microseismic array installation is a useful tool that may predict some of the issues and help to promote better acquisition quality. Therefore, it is important to reiterate the significance of the supervision for microseismic field measurements, especially when the technology is tested in new regions. Despite limited acquisition aperture and a comparatively small number of observed microseismic events, it is possible to derive valuable interpretation results from the data set. The geometry of the event locations suggests significant unplanned development of the hydraulic fractures, including a significant shift of the fracture from the initiation point. Records with clear S-wave splitting allowed us to determine arrival times of P waves and two S waves for several microseismic events. Arrival times were then used for simultaneous kinematic inversion for microseismic-event location and anisotropic velocity-model update (layered transversely isotropic with the vertical axis of symmetry model). We estimate significant anisotropy from microseismic data. Thomsen parameters [Formula: see text] and [Formula: see text] are well constrained, whereas parameter [Formula: see text] is constrained only for one of the layers.

Tensor‐based direction of arrival estimation with array virtual translation technique

The tensor-based spatial smoothing is a good algorithm for the direction of arrival (DOA) estimation, but it cannot make good use of the physical aperture of the array, so the paper proposes a tensor-based array virtual translation DOA estimation algorithm to solve the problem. Under the framework of tensor-based DOA estimation algorithm, the factor matrix obtained by tensor decomposition is extended to a signal subspace with Vandermonde structure by using array virtual translation technology. In addition, the algorithm expands the available array aperture, breaks through the limitation of physical array aperture on multi-target estimation ability, and further improves the estimation accuracy. Since the processing technique proposed in this paper has nothing to do with the construction of tensors, this technique is suitable for conventional DOA estimation algorithms based on tensors. Theoretical analysis and simulation experiments verify the effectiveness of the algorithm proposed in this paper.

An extension of least-squares redatuming: Simultaneous reconstruction of overburden reflectivities and virtual data

In a controlled-source seismology scenario, scattered wavefields from deep targets, e.g., the petroleum reservoirs, are often distorted by strong heterogeneities of the overburden media, complex topography and irregular acquisition. It is key for target-oriented seismic imaging to accurately reconstruct the scattering wavefields from the deep structures. Recent studies have promoted seismic redatuming for removing the imprint of the overburden through reconstructing virtual data just above the target area. Among the model-based redatuming approaches, least-squares inversion has advantages in mitigating the artifacts due to limited recording aperture and irregular spatial sampling, and allowing for the introduction of appropriate constraints to the reconstructed data. However, conventional least-squares redatuming (LSR) suffers from the spurious events and noises associated with the wavefield interaction of the overburden reflectivities close to the datum. To overcome this problem, we establish an efficient double-parameter LSR method that simultaneously updates the overburden reflectivities and the virtual data through a constrained optimization. Synthetic and field data examples demonstrate that this extended LSR method can effectively retrieve the scattering wavefields from the deep part and improve the target-oriented prestack depth migration below the datum.

Sound source localization of non-synchronous measurements beamforming based on the truncated nuclear norm regularization

Due to the size and aperture limitations of the microphone array, poor resolution and limited working frequency range are challenging for acoustic imaging with beamforming methods. In this work, two fast iteration algorithms, alternating direction method of multipliers (ADMM) and accelerated proximal gradient line search method (APGL) based on truncated nuclear norm regularization (TNNR), are proposed to complete the cross-spectral matrix for non-synchronous measurements beamforming. Compared with current matrix completion algorithm based on nuclear norm minimization (NNM), TNNR is regarded as a better approximation to the rank function, which means it can approach the real solution better and restore the sound sources accurately at a low signal-to-noise ratio (SNR) environment. Among the TNNR-APGL and TNNR-ADMM, the TNNR-APGL algorithm has a lower matrix completion error and a shorter calculation time. The localization results of TNNR-ADMM method are more robust to the number of measurements. The experiment results show that TNNR methods greatly improve the resolution of conventional beamforming (CBF) and suppress the sidelobes under low SNR conditions, which indicates that the non-synchronous measurements beamforming based on TNNR methods has the potential to be applied in the industrial scene and low SNR environment.

Design of a Polarization-Selective EM Transparent Mesh-Type E-Shaped Antenna for Shared-Aperture Radar Applications

In this paper, we propose a polarization-selective electromagnetic (EM) transparent mesh-type E-shaped antenna unit-cell in a shared aperture. The proposed antenna unit-cell, which can be expanded to a larger array in a modular way, has one S-band antenna on the upper layer and nine X-band antennas on the lower layers. The simple E-shaped structure, which has a low profile with a good bandwidth, is used for the antenna elements. However, due to the limited aperture size of the stacked configuration, the lower-layer elements can be physically blocked by the upper-layer element. To reduce this blockage effect, the S-band element is rotated 90 degrees with respect to X-band elements so that the polarizations between the S- and X-band elements are perpendicular to each other. Moreover, to minimize performance degradation due to the blockage effect, a mesh structure is applied for S-band elements for EM transparent characteristics, thereby improving EM transparency from −30 dB to −1.5 dB. The extended via cavity wall is also employed outside the nine X-band elements to minimize the mutual coupling and to reduce antenna size. To confirm the effectiveness of the proposed design, the proposed antenna unit-cell is fabricated, and the radiation characteristics are measured, in a full anechoic chamber. The average bore-sight gains in the S- and X-band are 5 dBi and 4.5 dBi, respectively. The results confirm that the proposed design is suitable for shared-aperture radar applications.

DOA Estimation Method of Weak Signal under the Compound Background of Strong Interference and Colored Noise

The traditional algorithm performing direction of arrival (DOA) estimation under the background of strong interference and colored noise has the problems of low estimation accuracy and small measurement targets. Based on the construction of a fourth-order cumulant (FOC) matrix to suppress colored noise, this paper adopts the extended noise subspace (ENS) algorithm and the fixed projection blocking (FPB) algorithm to estimate the DOA of weak targets. Firstly, a FOC matrix of the received signal vector is established to curb the noise component, and the eigenvalue decomposition is performed. Then, two approaches of weak signal DOA estimation are proposed. One approach is to merge the space where the strong interference steering vector lies into the noise subspace to construct an extended noise subspace, and then, the multisignal classification (MUSIC) algorithm is used to obtain the DOA estimation of the weak signal on the basis of the extended noise subspace. Another approach is to build the orthogonal projection matrix of the interference subspace as the interference blocking matrix, and the receiving array signal is preprocessed, and on the basis of it, the eigen decomposition is performed again to obtain the DOA information of the weak signal. Both algorithms make breakthroughs in the aperture limitation of the traditional algorithm, effectively expand the aperture, and promote the accuracy of estimation. The simulation tests the effectiveness of the proposed method.

Study on observation system of seismic forward prospecting in tunnel: A case on tailrace tunnel of Wudongde hydropower station

Abstract Seismic method is a major approach for detecting the seismic geological features ahead of the tunnel, understanding the distribution of unfavorable geology, and ensuring the safety of tunnel construction. Observation system is the key for seismic detection, many studies have been conducted to optimize the observation system; however, most of them focused on the surface seismic investigation and numerical simulation rather than in tunnel field environment (limited aperture and full space environment). How to obtain better wavefield information with limited observation aperture is a great challenge. In this study numerical simulation and instrumental techniques (GPR, DC, etc.) were implemented to further check the result of seismic detection at the 1# tailrace tunnel at the Wudongde hydropower station. In the field case, observation detectors were arranged spatially in the tunnel and source points were placed in four ways: linearly along a single side, on the tunnel face, in front of the detectors, and behind the detectors. Then, after data acquisition, the data processing is conducted to carry out the migration results. The imaging results indicate that the observation system with sources and detectors in liner arrangement (with equal interval) helps to suppress artifacts, further supporting the advantages of spatial observation system with liner observation line (detectors). Moreover, the study provides suggestions for geological prospecting in similar tunnel projects.

Reconstruction of Subsurface Objects by LSM and FWI From Limited-Aperture Electromagnetic Data

This article presents a hybrid 3-D electromagnetic (EM) full-wave inversion (FWI) method for the reconstruction of subsurface objects illuminated by an antenna array with the limited aperture. The 3-D linear sampling method (LSM) is first used to qualitatively reconstruct the rough shapes and locations of the subsurface objects. Then, the 3-D convolutional neural network (CNN) U-Net is used to further refine the images of the unknown objects. Finally, the Born iterative method (BIM) is implemented to quantitatively invert for the dielectric parameters of subsurface inhomogeneous objects or multiple homogeneous objects in the restricted image regions. Numerical simulations show that, compared with the pure FWI method BIM, the proposed hybrid method can reconstruct subsurface 3-D objects from limited-aperture EM data with both higher accuracy and lower computational cost. In addition, the proposed hybrid method also shows a strong antinoise ability for the reconstruction of multiple subsurface objects.

A Foldable Tightly Coupled Crossed Rings Antenna Array of Ultrawide Bandwidth and Dual Polarization

Low-profile foldable array antennas are becoming increasingly more important for a wide range of applications such as satellite communications and wearable electronic devices. The conventional arrays formed by patch-like antennas have been extensively studied on surfaces with a curvature but they have exhibited limited bandwidth and polarization performance. This study investigates a coupling enhanced crossed rings antenna array with two typical configurations for dual polarization, which inherently produces ultrawide bandwidth, dipole-like polarization characteristics and a fully curved array (FCA) eventually. The fractional bandwidth of the array is over 100% on a planar surface and expanded to approximately 140% on the curved surface. For the bent array of slant polarization, the beamwidth increases by over 20° compared to the planar array and cross polarization discrimination (XPD) maintains above 15 dB. The effects of curvature on the impedance matching and polarized radiation patterns for such arrays are investigated by measuring the performance of the fabricated prototype arrays. The results revealed that the tightly coupled crossed rings antenna array on a curved surface has a potential to form multiple beams on a limited aperture size through smaller subarrays which can yield ultrawide bandwidth due to concentrated mutual coupling mechanism. This characteristic is promising in applications where traditional flat panel arrays are difficult to implement such as in mobile stations, moving platforms and for satellite communication on-the-move.

A Fast Sparse Hyperbolic Radon Transform Based on Convolutional Neural Network and Its Demultiple Application

The hyperbolic Radon transform (RT) is a widely used demultiple method in the seismic data processing. But this transformation faces two major defects. The limited aperture of acquisition leads to the scissor-like diffusion in the Radon domain, which introduces separation difficulties between primaries and multiples. In addition, the computation of large matrices inversion involved in hyperbolic RT reduces the processing efficiency. In this letter, a specific Convolutional Neural Network (CNN) is designed to conduct a Fast Sparse Hyperbolic Radon Transform (FSHRT). Two techniques are incorporated into CNN to find the sparse solution. One is the coding-decoding structure, which captures the sparse feature of Radon parameters. The other is the soft threshold activation function followed by the end of neural networks, which suppresses the small parameters and further improves the sparsity. Thus, the network realizes the direct mapping between the adjoint solution and the sparse solution. Furthermore, synthetic and field demultiple experiments are carried out to demonstrate the rapidity and effectiveness of the proposed method.

Super-Resolution and Large Depth of Field Model for Optical Microscope Imaging

Due to the limitation of numerical aperture (NA) in a microscope, it is very difficult to obtain a clear image of the specimen with a large depth of field (DOF). We propose a deep learning network model to simultaneously improve the imaging resolution and DOF of optical microscopes. The proposed M-Deblurgan consists of three parts: (i) a deblurring module equipped with an encoder-decoder network for feature extraction, (ii) an optimal approximation module to reduce the error propagation between the two tasks, and (iii) an SR module to super-resolve the image from the output of the optimal approximation module. The experimental results show that the proposed network model reaches the optimal result. The peak signal-to-noise ratio (PSNR) of the method can reach 37.5326, and the structural similarity (SSIM) can reach 0.9551 in the experimental dataset. The method can also be used in other potential applications, such as microscopes, mobile cameras, and telescopes.

First “Skin Depth” estimations using GEANT4 and FLUKA based simulations for CERN secondary beamlines

In order to have highly flexible secondary beamlines collimation is crucial. Collimators are blocks of material placed along the beamline that let the main beam pass within the collimator aperture limits, while most of the particles beyond it interact in the material and gets absorbed or loses enough energy to be deflected away from the beam core by the magnets placed downstream. Some particles can interact at the edge of the collimators and be accepted within the main beam, creating background for the experiments downstream. The thickness of the layer contributing to this potential background is called Skin Depth. It depends on the material of the collimator, on the beam momentum as well as the acceptance of the beamline in terms of momentum band and divergence. This article presents the first studies with GEANT4 and FLUKA based simulations on the effects of such interactions at the CERN secondary beamlines.

Single-shot phase reconstruction based on beam splitting encoding and averaging

Coherent modulation imaging (CMI) can effectively improve the convergence performance of coherent diffraction imaging by introducing a pre-characterized wave modulator. However, traditional CMI algorithms suffer from a low signal-to-noise ratio (SNR), with insufficient information redundancy inheriting from a single diffraction pattern. Additionally, the strong modulation capability of the modulator with a small basic pitch is preferred; however, it leads to the difficulty of fabrication and measurement with a limited aperture size of the detector. To overcome those obstacles, this study proposes a revised CMI algorithm based on beam splitting encoding and averaging. A diffraction pattern array was recorded after the incident wave was split by grating and modulated by a weak scattering modulator simultaneously. This approach differed from the previous grating-based single-shot phase retrieval algorithm because the diffraction array was not segmented and used integrally during the iteration process, which guarantees the capability of diffraction-limited resolution in theory. Additionally, an average process was employed in the image plane of the object to improve SNR significantly. The performance of the revised algorithm was demonstrated by simulations and experiments and can be applied as a universal single-shot phase retrieval algorithm to various fields practically with fast convergence speed and high SNR.

Laser heterodyne based stress measurement technology for optical elements

Common stress measurement methods of optical elements often suffering from complex process and limited aperture. To meet this challenge a new method based on laser heterodyne technology is proposed. In this method the stress measurement is transformed into the measurement of optical path difference induced by birefringence according to the stress birefringence effect, and the signal light is demodulated by laser heterodyne detection. This method has simple measurement process, and solves the problem of large-aperture measurement by combining with MEMS scanning technology. The basic structure of the measurement system is established, and its theoretical model is derived in detail. The experiment result of a fused silica sample with thickness of 2 mm reach an accuracy as high as 1.8 kPa, and the relative error is less than 0.01%.

Localizing a target inside an enclosed cylinder with a single chaotic cavity transducer augmented with supervised machine learning

Ultrasound is employed in, e.g., non-destructive testing and environmental sensing. Unfortunately, conventional single-element ultrasound probes have a limited acoustic aperture. To overcome this limitation, we employ a modern method to increase the field-of-view of a commercial transducer and to test the approach by localizing a target. In practice, we merge the transducer with a chaotic cavity to increase the effective aperture of the transducer. In conventional pulse-echo ultrasound signal analysis, location estimation is based on determining the time-of-flight with known propagation speed in the medium. In the present case, the dispersing field induces complexity to this inverse problem, also in 2D. To tackle this issue, we use a convolutional neural network-based machine learning approach to study the feasibility of employing one single chaotic cavity transducer to localize an object in 2D. We show that we indeed can localize an inclusion inside a water-filled cylinder. The localization accuracy is one diameter of the inclusion. The area that we can infer increases by 49% in comparison to using the same transducer without applying the proposed chaotic cavity method.

Computational Bayesian inference of range and depth of a mobile scatterer in a refractive ocean waveguide with a limited vertical aperture array

A computational Bayesian method is presented for inference from a limited vertical aperture regarding the range, depth and speed of a submerged large mobile object. Closely spaced multipath arrivals in Doppler and vertical angle off of the target in a refractive environment are addressed in the presence of uncertainty in the ambient acoustic noise power. Vertical angles and Doppler frequencies of the arrival structure are jointly inferred and their posterior density is mapped to the object’s range, depth, and speed through acoustic ray interpolation. A case study with the classic Munk sound speed profile is presented to lend credence to the approach.

Wavefront Detection and Compensation Technology Based on Signal Light Nutation Under Atmospheric Turbulence

The Shack-Hartmann wavefront sensor restricts the dynamic range and detection accuracy of wavefront detection due to the limitation of the lens array aperture. This study proposes a system using signal light nutation to detect wavefront distortion, providing high spatial resolution and detection dynamic range. Simulations show that the root mean square (RMS) and mixing efficiency of the compensated wavefront are optimized. In the case of strong turbulence, the mixing efficiency is increased by nearly 105 times, and the RMS is reduced to the original value of 0.048.