Number Of Array Elements Research Articles

Expediting Image Acquisition in Reflection Ultrasound Computed Tomography.

Reflection ultrasound computed tomography (RUCT) attains optimal image quality from objects that can be fully accessed from multiple directions, such as the human breast or small animals. Owing to the full-view tomography approach based on the compounding of images taken from multiple angles, RUCT effectively mitigates several deficiencies afflicting conventional pulse-echo ultrasound (US) systems, such as speckle patterns and interuser variability. On the other hand, the small interelement pitch required to fulfill the spatial sampling criterion in the circular transducer configuration used in RUCT typically implies the use of an excessive number of independent array elements. This increases the system's complexity and costs, and limits the achievable imaging speed. Here, we explore acquisition schemes that enable RUCT imaging with the reduced number of transmit/receive elements. We investigated the influence of the element size in transmission and reception in a ring array geometry. The performance of a sparse acquisition approach based on partial acquisition from a subset of the elements has been further assessed. A larger element size is shown to preserve contrast and resolution at the center of the field of view (FOV), while a reduced number of elements is shown to cause uniform loss of contrast and resolution across the entire FOV. The tradeoffs of achievable FOV, contrast-to-noise ratio, and temporal and spatial resolutions are assessed in phantoms and in vivo mouse experiments. The experimental analysis is expected to aid the development of optimized hardware and image acquisition strategies for RUCT and, thus, result in more affordable imaging systems facilitating wider adoption.

Array Transducer Design: A Vibrant Research Theme in Medical Ultrasonics

Since the 1970s, when portable transducer arrays were first introduced for medical ultrasound imaging, they have undergone substantial technological developments. The development of advanced arrays is often motivated by the need to achieve high diagnostic and therapeutic efficacy and to serve new fields of application. In the past few decades, medical ultrasound array design has been an active research area with challenging technical requirements that continually seek to reduce physical size, improve sensitivity, optimize the number of array elements, realize wide bandwidth, and achieve high output power. The need to devise arrays with increased performance has concurrently stimulated advances in transducer technologies, microelectronics, and array layout design. Nowadays, representative examples can be found for both 2-D and 3-D applications such as high-intensity-focused ultrasound arrays, very-high-frequency or dual-frequency probes, kerf-less arrays, 2-D sparse arrays, and probes with embedded application-specific integrated circuits. The emergence of these advanced arrays has, in turn, stimulated the development of novel, customized transmission and reception approaches, image reconstruction algorithms, and data recovery strategies to exploit or deal with the peculiarities of a specific array.

Effect of The Number of Array Elements from Printed Yagi Antenna Against Power Acquisition Efficiency for Implementation RF Harvesting Energy on Frequency 2.4 GHz

Most low-power electronics, such as remote sensors and embedded devices, are powered by batteries. Replacement is expensive when there are hundreds of sensors in remote locations. RF Energy Harvesting can be used to provide an alternative energy source for these types of embedded devices. This study is to analyze the effect of the number of elements of the yagi print antenna array on the efficiency of receiving power at a frequency of 2.4 GHz. The making of this harvesting energy system is aimed at making the energy around us maximally utilized and used as alternative energy by the community. The highest output voltage of the rectifier antenna at a distance of 10 cm from the access point is 216 mV for a single element yagi print antenna, 96 mV for a 2 element yagi print antenna, and 168 mV for a 4 element yagi print antenna. with no load, the number of array elements affects the output voltage of the rectifier in addition to the number of stage voltage multipliers.

"Conical" Frustum Multi-Beam Phased Arrays for Air Traffic Control Radars.

The design of conical frustum phased array antennas for air traffic control (ATC) radar systems is addressed. The array architecture, which is controlled by a fully digital beam-forming (DBF) network, is composed by a set of equal vertical modules. Each module consists of a linear sparse array that generates on receive multiple instantaneous beams pointing along different directions in elevation. To reach the best trade-off between the antenna complexity (i.e., minimum number of array elements and/or radio frequency components) and radiation performance (i.e., matching a set of reference patterns), the synthesis problem is formulated in the Compressive Sampling (CS) framework. Then, the positions of the array elements and the complex excitations for generating each single beam are jointly determined through a customized version of the Bayesian CS (BCS) tool. Representative numerical results, concerned with ideal as well as real antenna models, are reported both to validate the proposed design strategy and to assess the effectiveness of the synthesized modular sparse array architecture also in comparison with conventional arrays with uniformly-spaced elements.

Anti-Jamming Method and Implementation for GNSS Receiver Based on Array Antenna Rotation

Global navigation satellite system (GNSS) array antenna receivers are effective for suppressing wideband jamming. However, its anti-jamming performance decreases sharply when the number of wideband interference surpasses the number of array elements. Since a large number of jammers are often used in navigation countermeasures, it is crucial to keep array antenna receivers available in such conditions. Aiming at this issue, two main tasks were performed in this research and are presented in this paper: Firstly, the direction sensitivity of the sup-freedom anti-jamming performance is revealed and an anti-jamming method for array antenna receivers based on antenna rotation is proposed. Secondly, in order to determine the optimal rotation angle rapidly, a variable-step iteration algorithm based on gradient descent is proposed. Theoretical analysis and simulation show the effectiveness of the proposed anti-jamming method and the efficiency of the implementation algorithm. In a typical airborne scenario with a maximum azimuth difference of 90°, the anti-jamming ability of the proposed method improved by 21~26 dB and 5~10 dB for arrays adopting the PI (power inversion) and MVDR (minimum variance distortionless response) algorithms, respectively. The iterative efficiency improved by 78.35–99.63% in comparison with a traversal of 0.1° search resolution. The proposed method and algorithm are not limited to airborne scenarios and they might be influential to anti-jamming algorithms in the data domain.

Integrating Communication and Sensor Arrays to Model and Navigate Autonomous Unmanned Aerial Systems

The emerging concept of drone swarms creates new opportunities with major societal implications. However, future drone swarm applications and services pose new communications and sensing challenges, particularly for collaborative tasks. To address these challenges, in this paper, we integrate sensor arrays and communication to propose a mathematical model to route a collection of autonomous unmanned aerial systems (AUAS), a so-called drone swarm or AUAS swarm, without having a base station of communication but communicating with each other using multiple spatio-temporal data. The theories of structured matrices, concepts in multi-beam beamforming, and sensor arrays are utilized to propose a swarm routing algorithm. We address the routing algorithm’s computational and arithmetic complexities, precision, and reliability. We measure bit-error-rate (BER) based on the number of elements in sensor arrays and beamformed output of the members of the swarm to authenticate and secure the routing for the decentralized AUAS networking. The proposed model has the potential to enable future drone swarm applications and services. Finally, we discuss future work on obtaining a machine-learning-based low-cost drone swarm routing algorithm.

Hardware Acceleration of MUSIC Algorithm for Sparse Arrays and Uniform Linear Arrays

Multiple Signal Classification (MUSIC) is a high-performance Direction of Arrival (DOA) estimation algorithm, which has been widely used. The algorithm needs to calculate the covariance matrix, eigenvalue decomposition and spectral peak search. In the paper, the hardware structure of the existing Jacobi algorithm for Hermitian matrices is proposed. On this basis, a novel hardware acceleration of the MUSIC algorithm for sparse arrays and uniform linear arrays is proposed, and the sparse array is a nested array. There are two designs, Design 1 supports 1~10 nested array elements or 1~32 uniform linear array elements, distinguishes 1~32 sources, configures snapshots 1~2048, and the maximum number of iterations and iteration accuracy of the complex Jacobi algorithm. Design 2 only needs <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$101.8~\mu $ </tex-math></inline-formula> s to complete a DOA estimation when the number of array elements is 8, the number of sources is 1, and the snapshots is 128. In more detail, the Root Mean Squared Error (RMSE) of both can reach 0.03°. The logic resources on the Zynq-7000 development board are 14,761 and 28,305 Look-Up Tables (LUTs), respectively.

Near-Field Modeling and Performance Analysis of Modular Extremely Large-Scale Array Communications

This letter studies a new array architecture, termed as <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">modular extremely large-scale</i> array (XL-array), for which a large number of array elements are arranged in a modular manner. Each module consists of a moderate number of array elements and the modules are regularly arranged with the inter-module spacing typically much larger than signal wavelength to cater to the actual mounting structure. We study the mathematical modelling and conduct the performance analysis for modular XL-array communications, by considering the non-uniform spherical wave (NUSW) characteristic that is more suitable than the conventional uniform plane wave (UPW) assumption for physically large arrays. A closed-form expression is derived for the maximum signal-to-noise ratio (SNR) in terms of the geometries of the modular XL-array, including the total array size and module separation, as well as the user’s location. The asymptotic SNR scaling law is revealed as the size of modular array goes to infinity. Furthermore, we show that the developed modelling and performance analysis include the existing results for collocated XL-array or far-field UPW assumption as special cases. Numerical results demonstrate the importance of near-field modelling for modular XL-array communications since it leads to significantly different results from the conventional far-field UPW modelling.

Parameter estimation of multiple frequency-hopping signals based on space-time-frequency analysis by atomic norm soft thresholding with missing observations

In this paper, we address the problem of multiple frequency-hopping (FH) signal parameters estimation in the presence of random missing observations. A space-time matrix with random missing observations is acquired by a uniform linear array (ULA). We exploit the inherent incomplete data processing capability of atomic norm soft thresholding (AST) to analyze the space-time matrix and complete the accurate estimation of the hopping time and frequency of the received FH signals. The hopping time is obtained by the sudden changes of the spatial information, which is implemented as the boundary to divide the time domain signal so that each segment of the signal is a superposition of time-invariant multiple components. Then, the frequency of multiple signal components can be estimated precisely by AST within each segment. After obtaining the above two parameters of the hopping time and the frequency of signals, the direction of arrival (DOA) can be directly calculated by them, and the network sorting can be realized. Results of simulation show that the proposed method is superior to the existing technology. Even when a large portion of data observations is missing, as the number of array elements increases, the proposed method still achieves acceptable accuracy of multi-FH signal parameters estimation.

A 32-element loop/dipole hybrid array for human head imaging at 7T.

To improve whole-brain SNR at 7Tesla, a novel 32-element hybrid human head array coil was developed, constructed, and tested. Our general design strategy is based on 2 major ideas: Firstly, following suggestions of previous works based on the ultimate intrinsic SNR theory, we combined loops and dipoles for improvement of SNR near the head center. Secondly, we minimized the total number of array elements by using a hybrid combination of transceive (TxRx) and receive (Rx) elements. The new hybrid array consisted of 8 folded-end TxRx-dipole antennas and 3 rows of 24 Rx-loops all placed in a single layer on the surface of a tight-fit helmet. The developed array significantly improved SNR in vivo both near the center (∼20%) and at the periphery (∼20% to 80%) in comparison to a common commercial array coil with 8 transmit (Tx) and 32 Rx-elements. Whereas 24 loops alone delivered central SNR very similar to that of the commercial coil, the addition of complementary dipole structures provided further improvement. The new array also provided ∼15% higher Tx efficiency and better longitudinal coverage than that of the commercial array. The developed array coil demonstrated advantages in combining complementary TxRx and Rx resonant structures, that is, TxRx-dipoles and Rx-loops all placed in a single layer at the same distance to the head. This strategy improved both SNR and Tx-performance, as well as simplified the total head coil design, making it more robust.

Double-row dipole/loop combined array for human whole brain imaging at 7T.

Important issues in designing radiofrequency (RF) coils for human head imaging at ultra-high field (UHF; ≥7T) are the inhomogeneity and longitudinal coverage (along the magnet axis) of the transmit (Tx) RF field. Both the homogeneity and coverage produced by Tx volume coils can be improved by means of three-dimensional (3D) RF shimming, which requires the use of multirow Tx-arrays. In addition, according to recent findings of the ultimate intrinsic signal-to-noise ratio (UISNR) theory, the loop-only receive (Rx) arrays do not provide optimal SNR near the brain center at UHF. The latter can be obtained by combining complementary conductive structures carrying different current patterns (e.g., loops and dipole antennas). In this work, we developed, constructed, and evaluated a novel 32-element hybrid array design for human head imaging at 7T. The array consists of 16 transceiver loops placed in two rows circumscribing the head and 16 folded-end Rx-only dipoles positioned in the centers of loops. By placing all elements in a single layer, we increased RF power deposition into the tissue and, thus, preserved the Tx-efficiency. Using this hybrid design also simplifies the coil structure by minimizing the total number of array elements. The array demonstrated whole brain coverage, 3D RF shimming capability, and high SNR. It provided ~15% higher SNR near the brain center and, depending on the RF shim mode, from 20% to 40% higher Tx-efficiency than a common commercial head array coil.

Covering the Combinatorial Design Space of Multiplex CRISPR/Cas Experiments in Plants.

Over the past years, CRISPR/Cas-mediated genome editing has revolutionized plant genetic studies and crop breeding. Specifically, due to its ability to simultaneously target multiple genes, the multiplex CRISPR/Cas system has emerged as a powerful technology for functional analysis of genetic pathways. As such, it holds great potential for application in plant systems to discover genetic interactions and to improve polygenic agronomic traits in crop breeding. However, optimal experimental design regarding coverage of the combinatorial design space in multiplex CRISPR/Cas screens remains largely unexplored. To contribute to well-informed experimental design of such screens in plants, we first establish a representation of the design space at different stages of a multiplex CRISPR/Cas experiment. We provide two independent computational approaches yielding insights into the plant library size guaranteeing full coverage of all relevant multiplex combinations of gene knockouts in a specific multiplex CRISPR/Cas screen. These frameworks take into account several design parameters (e.g., the number of target genes, the number of gRNAs designed per gene, and the number of elements in the combinatorial array) and efficiencies at subsequent stages of a multiplex CRISPR/Cas experiment (e.g., the distribution of gRNA/Cas delivery, gRNA-specific mutation efficiency, and knockout efficiency). With this work, we intend to raise awareness about the limitations regarding the number of target genes and order of genetic interaction that can be realistically analyzed in multiplex CRISPR/Cas experiments with a given number of plants. Finally, we establish guidelines for designing multiplex CRISPR/Cas experiments with an optimal coverage of the combinatorial design space at minimal plant library size.

Deep Learning Piston Aberration Control of Fiber Laser Phased Array By Spiral Phase Modulation

The stochastic parallel gradient descent (SPGD) algorithm is usually employed as the control strategy for phase-locking in fiber laser phased array systems. However, the convergence speed of the SPGD algorithm will slow down as the number of array elements increases. To improve the control bandwidth, the convolutional neural network is introduced to quickly calculate the initial piston aberration in a single step. In addition, the irrationality of the commonly used Mean Square Error (MSE) evaluation function in existing convolutional neural networks is analyzed. A new evaluation function NPCD (Normalized Phase Cosine Distance) is proposed to improve the accuracy of the neural networks. The results show that the piston aberration residual is 0.005 and the power in the bucket (PIB) is 0.993 after accurate preliminary compensation, which means that the system directly enters the co-phase state. We also demonstrate the robustness and scalability by adding additional disturbance and expanding the scale of the array.

Research on factors affecting ultrasonic phased array detection imaging quality for curved component

An in-depth analysis on the beam directivity of ultrasonic phased arrays has been made to solve the problems of low image quality and identification difficulties caused by a suboptimal configuration of array elements. The influence on the number and spacing of array elements on the imaging quality of curved components was studied. The simulation and experimental verification of the phased array sound field for curved components were carried out. The rules governing the influence of phased array transducer parameters on imaging quality were obtained, and an approach to the optimization of parameters was proposed. The results of this study have important significance for transducer design and the phased array detection of curved components.

Failure diagnosis of linear arrays based on deep residual shrinkage network

AbstractA novel array antenna diagnosis method based on a deep residual shrinkage network (DRSN) is introduced in the case of linear arrangements. The failure of array elements often leads to significant changes in the far‐field pattern of an array antenna. Therefore, the failure diagnosis of array antennas can be carried out according to the far‐field pattern data. In this paper, the proposed method based on DRSN can automatically learn useful features from the sampled far‐field patterns of the linear array and find the mapping relationship between different far‐field patterns and failure scenarios, to find the locations and number of faulty array elements. Experimental results show that the proposed method based on DRSN has higher diagnostic accuracy in the noise environment at low signal‐to‐noise ratios by comparing with the traditional machine learning algorithm—support vector machine.

Covariance matrix reconstruction method based on amplitude and phase constraints with application to extend array aperture.

The angular resolution has always been a concern in the underwater direction of arrival (DOA) estimation. The resolution of the uniform linear array will worsen if the array aperture decreases. When the element spacing is determined, increasing the number of array elements (NAE) can improve the resolution. However, the NAE cannot be greatly increased in practical applications. To address this problem, we propose an array aperture extension method. For this method, we design an optimization algorithm to reconstruct the covariance matrix of the extended array by using that of the original array. Moreover, to make the extended array resemble the actual array, the reconstructed covariance matrix is constrained with a pure signal covariance matrix. The solution method of the optimization algorithm is described in detail. The function of this method is to improve the array aperture by increasing the virtual array elements without changing the element spacing. Therefore, when the array elements are insufficient, this method helps to improve the DOA estimation performance, such as the estimation precision and resolution probability of dual targets. Experiments including simulations and real lake experiments are implemented to validate the effectiveness of the proposed method.

Low Sidelobe Orbital Angular Momentum Vortex Beams Based on Modified Bayliss Synthesis Method for Circular Array

Electromagnetic orbital angular momentum (OAM) vortex beam patterns generated by conventional methods are always of high sidelobe level, which severely limits its application. Considering the sidelobe suppression abilities of Bayliss synthesis method for difference beams, we present a modified Bayliss synthesis procedure to obtain low sidelobe OAM vortex beams. The Bayliss synthesis method cannot suppress the sidelobe level of difference pattern to the desired value when the element number of linear array is relatively small. By modifying the original zero locations that need to be removed in Bayliss pattern, we can further suppress the sidelobe level of difference pattern. This can be called the modified Bayliss pattern. Finally, by expanding the proposed synthesis method from linear source to circular array, theoretical results show that sidelobe levels of OAM beams can be suppressed to less than −30 dB when OAM mode number varies from <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">l</i> = 1 to <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">l</i> = 10. The proposed low sidelobe OAM vortex beam can be applied in antijamming communications of near-field in the future.

A STAP clutter suppression algorithm based on sparse representation for small-array HFSWR

ABSTRACT In high-frequency surface wave radar (HFSWR) systems, the main-lobe of the receiving angle spectrum suffers from severe broadening due to a small-array aperture effect. This broadening causes more clutter components to be mixed into the main-lobe, resulting in target vessels more prone to be submerged in the clutter. This problem severely affects the target detection performance. A reduction in the number of array elements decreases the degrees of freedom (DOF), making clutter suppression more difficult. Space-time adaptive processing (STAP) has recently become a crucial tool for clutter suppression in advanced HFSWR systems, using two-dimensional data to increase DOF. Focusing on low DOF and typical nonhomogeneous clutter with high energy, this study proposes a STAP clutter suppression method by estimating clutter components accurately in the space-time domain based on sparse representation in few snapshots. The experimental results verify that the proposed algorithm provides high suppression performance for measured clutter.

An Effective Method for the Synthesis of Wideband and Wide-Scanning Sparse Planar Array

The matrix enhancement and matrix pencil (MEMP) has been used to reduce the number of array elements in the planar array with a shaped-beam pattern. This work extends the MEMP-based synthesis method to the synthesis of pattern reconfigurable sparse planar arrays in wide angle scanning and wide-band, which exploits a necessary restriction on finding the common element positions and individual element excitations for multiple patterns. Moreover, a unitary transformation is exploited into the multiple-composite equivalent Hankel matrix, which converts the complex computations of singular value decomposition (SVD) and eigenvalue decomposition (EVD) courses into real ones and effectively reduces the computation complexity. A new tactic is also restricted on avoiding too small element spacing with the consideration of the size of array antenna element. A set of numerical experiments is provided to validate the effectiveness and advantages of the proposed method.

Design of RFSoC-based Digital Phased Array Feed (PAF) and Hybrid Architecture Beamforming System

As the number of array elements and bandwidth increase, the design challenges of the Phased Array Feed (PAF) front-end and its signal processing system increase. Aiming at the ng-PAF of the 110 m radio telescope, this article introduces the concept of fully digital receivers and attempts to use Radio Frequency System-on-Chip (RFSoC) technology to digitize close to the feed array, reduce the complexity and analog components of the front-end, and improve the fidelity of the signals. The article discusses the digital beamforming topology and designs a PAF signal processing experimental system based on RFSoC+GPU hybrid architecture. The system adopts a ZCU111 board to design RF-direct digitization and preprocessing front-end, which can sample eight signals up to 2.048 GSPS, 12 bit, channelize the signals into 1024 chunks, then reorder into four data streams and select one of the 256 MHz frequency bands to output through four 10 Gb links. A GPU server is equipped with four RTX 3090 GPUs running four HRBF_HASHPIPE instances, each receiving a 64 MHz bandwidth signal for high-throughput real-time beamforming. The experimental system uses a signal generator to emulate Sa-like signals and propagates through rod antennas, which verifies the effectiveness of the beamforming algorithm. Performance tests show that after algorithm optimization, the average processing time for a given 4 ms data is less than 3 ms in the four-GPU parallel processing mode. The RFSoC integrated design shows significant advantages in power consumption and electromagnetic radiation compared with discrete circuits according to the measurement results.