Large Planar Arrays Research Articles

Analysis of Performance Improvement of Planar Antenna Arrays With Optimized Square Rings for Massive MIMO Applications

The power pattern of the conventional fully optimized planar arrays can be properly reshaped according to the required user-defined constraints. However, the practical implementation of such fully optimized large planar arrays is complex and expensive. This paper introduces a new and efficient technique that is capable of providing better performance and almost the same power pattern shapes as that of the conventional fully optimized planar arrays by optimally adjusting the element amplitude and phase excitations of the outer-square rings instead of all elements' excitations. The proposed technique starts with a massive fully planar array then divides it into two contiguous sub-planar arrays which are both symmetric about the original array center. The elements excitation amplitudes or phases of the outer sub-planar array are only adjusted to form the desired power pattern shapes, while the amplitudes or phases of the central sub-planar array elements which have usually higher weights than the outer elements are made constants (i.e., they made ones for the case of amplitude-only control and zeros for the phase-only control). The results demonstrate the capability of the proposed planar array to form the required power patterns with far less number of the adjustable elements.

Synthesis of Large Ultra-wideband Sparse Circular Planar Arrays Based on Rotationally Symmetric Structure

This article aims to improve the synthesis efficiency and radiation performance of large ultra-wideband (UWB) rotationally symmetric sparse circular planar arrays by using a modified differential evolution algorithm (MDEA). In the proposed MDEA, we adopt a new encoding mechanism in which an individual represents an element position expressed in polar coordinates. Importantly, such an encoding mechanism can facilitate the multiplication calculation for the array factor in the individual being updated while making it easier to meet the given minimum element spacing constraint. Moreover, to cater to the new encoding mechanism, some low-dimensional evolution operators are introduced to avoid the prematurity. In particular, the UWB rotationally symmetric sparse planar array synthesis problem is transformed into the sidelobe suppression problem of the array pattern at the highest frequency under the given array aperture, and the minimum spacing constraints is used to guarantee enough space to place physical UWB antenna elements. Two synthesis examples of UWB sparse planar arrays based on rotationally symmetric structures are presented. The results show that the peak sidelobe level (PSL) obtained by the proposed MDEA is significantly lower than the results obtained by some existing algorithms in an acceptable CPU time, which proves the effectiveness and superiority of the proposed MDEA.

Enhanced Effective Aperture Distribution Function for Characterizing Large-Scale Antenna Arrays

Accurate characterization of large-scale antenna arrays is growing in importance and complexity for the fifth-generation (5G) and beyond systems, as they feature more antenna elements and require increased overall performance. The full 3D patterns of all antenna elements in the array need to be characterized because they are in general different due to construction inaccuracy, coupling, antenna array's asymmetry, etc. The effective aperture distribution function (EADF) can provide an analytic description of an antenna array based on a full-sphere measurement of the array in an anechoic chamber. However, as the array aperture increases, denser spatial samples are needed for EADF due to large distance offsets of array elements from the reference point in the anechoic chamber, leading to a prohibitive measurement time and increased complexity of EADF. In this paper, we present the EADF applied to large-scale arrays and highlight issues caused by the large array aperture. To overcome the issues, an enhanced EADF is proposed with a low complexity that is intrinsically determined by the characteristic of each array element rather than the array aperture. The enhanced EADF is validated using experimental measurements conducted at 27-30 GHz frequency band with a relatively large planar array.

An Efficient Bias Correction Method for Large Planar Polarimetric Phased Array Radar

For a large planar polarimetric phased array radar, a bias correction matrix obtained from array pattern measurements needs to be applied when the beam is pointed off broadside. To avoid measuring all possible beam directions while ensuring the correction accuracy, an efficient bias correction method using polynomial surface fitting is proposed. After dividing the entire scan area into several subregions, merely dozens of beam directions are measured in each subregion. Through the polynomial surface model, the correction matrices of unmeasured beam directions can be well predicted. The simulated results show that the proposed method can effectively achieve accurate bias correction in two-dimension <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\pm 45^{\circ }$</tex-math></inline-formula> scanning. Under the same relative error level for antenna pattern measurement, the results of Monte Carlo simulations verify that the proposed method has a more stable performance than directly beam-by-beam measurement due to its least square process.

Chasing the bird: 3D acoustic tracking of aerial flight displays with a minimal planar microphone array

ABSTRACT Tracking the flight patterns of birds and bats in three-dimensional space is central to key questions in evolutionary ecology but remains a difficult technical challenge. For example, complex aerial flight displays are common among birds breeding in open habitats, but information on flight performance is limited. Here, we demonstrate the feasibility of using a large ground-based 4-microphone planar array to track the aerial flight displays of the cryptic Jack Snipe Lymnocryptes minimus. The main element of male display flights resembles a galloping horse at a distance. Under conditions of sufficient signal-to-noise ratio and of vertical alignment with the microphone array, we successfully tracked male snipe in 3D space for up to 25 seconds with a total flight path of 280 m. The ’gallop’ phase of male snipe dropped from ca. 141 to 64 m above ground at an average velocity of 77 km/h and up to 92 km/h. Our project is one of the first applications of bioacoustics to measure 3D flight paths of birds under field conditions, and our results were consistent with our visual observations. Our microphone array and post-processing workflow provides a standardised protocol that could be used to collect comparative data on birds with complex aerial flight displays.

A Novel 3D Beam Domain Channel Model for Massive MIMO Communication Systems

Massive multiple-input multiple-output (MIMO) channels are distinctly characterized by their array non-stationarity, which has not been considered in the existing beam domain channel models (BDCMs). In this paper, the array non-stationarity of massive MIMO channels is modeled by the spatially consistent visibility regions (VRs) over a large uniform planar array (UPA) in terms of individual multipath components (MPCs). Based on this, a novel three-dimensional (3D) BDCM incorporating the effects of array non-stationarity is proposed. Statistical properties of the proposed BDCM including channel power, power leakage, space-time-frequency correlation function (STF-CF), and beam spread are derived. The ergodic and outage capacities are evaluated. The impacts of array non-stationarity on those statistics and channel capacity are analyzed. Results suggest that the beamwidths or spatial resolutions of the BDCM for different directions are not equal due to the array non-stationarity. This in turn increases the power leakage and correlation between channel elements and reduces the beam domain channel capacity.

Preparation and imaging properties of coherent chalcogenide glass fiber bundles with large planar array for far-infrared transmission (invited)

Preparation and imaging properties of coherent chalcogenide glass fiber bundles with large planar array for far-infrared transmission (invited)

An Inhomogeneous Plane-Wave Based Single-Level Fast Direct Solver for the Scattering Analysis of Extremely Large Antenna Arrays

A semianalytic single-level fast direct solver (FDS) is presented for the method-of-moments (MoM) analysis of large planar antenna arrays with up to few thousands of complex elements on current desktop computers. Assuming a partition of the impedance matrix, the proposed scheme factorizes the near-field blocks via a singular value decomposition (SVD)-based low-rank approximation and the intermediate-field blocks via an analytical inhomogeneous plane-wave (IPW) expansion. The near- and intermediate-field bases are then unified to leverage the Woodbury formula for the inversion. The solutions for the excitation of each array ports are obtained at once with <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$O(N^{15/7} \ln ^{3} N)$ </tex-math></inline-formula> computational cost and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$O(N^{11/7} \ln N)$ </tex-math></inline-formula> memory for array problems with <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$N$ </tex-math></inline-formula> basis functions. The complexities are traced precisely and the error is controlled by means of analytical formulas for the required number of IPWs. The FDS is also combined with a macrobasis function (MBF) approach to deal with antenna geometries containing many subwavelength details. This article includes simulations of regular arrays of about <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$169^{2}~3$ </tex-math></inline-formula> -D dipoles and an irregular array composed of seven stations of the low-frequency square kilometer array (SKA) telescope comprising each 256 log-periodic (LP) antennas. The proposed FDS allows the analysis of the coupling effect both within any one station but also between the stations of the telescope, a size and complexity of problem which has not been possible with existing published techniques.

Phase-Only Synthesis for Large Planar Arrays via Zernike Polynomials and Invasive Weed Optimization

A synthesis method for the design of large planar array antennas with phase-only control is here presented. The synthesis is based on the use of Zernike polynomials, as global basis function for the phase, to reduce the number of optimization variables with respect to the number of elements of the array. Invasive weed optimization (IWO) is applied to polynomial coefficients&#x2019; optimization to circumvent nonlinearity and local trapping issues typical of phase-only problems. The periodicity of the array factor is exploited to reduce the optimization to a Voronoi cell of the grating-lobes&#x2019; lattice and nonuniform meshing is introduced to best adapt the control stations to the beam shape requirements. The technique is applied to the design of shaped beams for continental coverage from geostationary satellites.

Gain and Phase Calibration of Uniform Rectangular Arrays Based on Convex Optimization and Neural Networks

A calibration method based on convex optimization (CVX) and neural networks is proposed for the large planar arrays of phased array three-dimensional imaging sonar systems. The method only needs an acoustic calibration source at an unknown position in the far field, and the direction of arrival (DOA) and gain and phase error are jointly estimated. The method uses a CVX algorithm to solve an optimization problem and initially estimates the DOA of the calibration source robustly. Subsequently, according to the estimation results, a neural network is used for fitting to obtain off-grid DOA estimation of the calibration source. Thereafter, spatial matched filtering is performed to obtain the gain and phase residual estimations. The root mean square error (RMSE) of the beam pattern calibrated by the method for uniform planar arrays can reach a value of 4.9542 × 10−5. The experimental results demonstrate the efficiency of the proposed method for gain and phase calibration.

3-D Acoustic Image Denoising for a Sonar System With Sparse Planar Arrays

The development of three-dimensional (3-D) underwater imaging systems is restricted by the high hardware costs associated with the use of a large number of transducers, as well as poor image quality due to degrading noise. This report presents the design of a low-complexity 3-D underwater imaging system that can generate high-quality images. In particular, a complex-weight sparse synthesis method for a large planar array is presented to reduce the number of active elements. Then, a denoising network referred to as an asymmetric-pyramid globe residual network is proposed to enhance the acoustic images generated by the sparse planar arrays. This method can perceive the entirety of the 3-D acoustic images for denoising and effectively reduce the degradation effects due to speckle noise and sidelobes. The simulation results demonstrate that the resulting image quality is higher than that achieved using previously developed networks in terms of the peak signal-to-noise ratio and structural similarity index. To validate the proposed system further, an actual system based on the proposed methods was devised and tested via lake-based trials. The experimental results demonstrate the notable improvements obtained considering the sparsity rate and image quality relative to those presented in previous literature.

Pruned Distributed and Parallel Subarray Beamforming for 3-D Underwater Imaging With Fine-Grid Sparse Arrays

The development of real-time 3-D underwater imaging systems with large planar arrays involves high hardware costs and great computational burden. This study proposes the concept of fine-grid sparse arrays and the pruned distributed and parallel subarray (P-DPS) beamforming algorithm to achieve 3-D narrowband underwater imaging systems with low complexity. Fine-grid sparse arrays refine traditional half-wavelength grids to improve the freedom of the sparse optimization process and reduce the number of active elements. However, grid refinement increases the computational load of conventional fast beamforming algorithms. To solve this problem, a new pruned fast Fourier transform is proposed to eliminate all the redundant operations in the P-DPS beamforming, which is suitable for fine-grid sparse arrays. The computational load of the P-DPS beamforming seldom increases with grid refinement. The validity of the proposed method is verified with a fine-grid sparse planar array designed in the study. The computational load is then analyzed and compared with those of other methods. Results show the notable improvements in array sparsity rate and computational efficiency relative to those in the literature.

Two‐dimensional adaptive beamforming for large planar array antennas based on weight matrix reconstruction

Adaptive beamformers at the element level usually require a great number of training samples and the computational cost for calculating the weight vector for large phased array antennas is very high, which make it difficult for real-time applications. To address this problem, a two-dimensional (2-D) adaptive beamformer applicable to large planar array antennas that have low computational complexity and low training sample requirement is proposed. In the proposed method, the weight matrix is first reconstructed as a matrix that has the same or close columns and rows by utilising the special Kronecker property of the array steering matrix. Then, the weight vector is determined by adopting a bi-quadratic cost function and a bi-iterative algorithm. Experimental results show that the proposed method can achieve fairly good performance even when the training samples are small.

Millimeter Wave Massive MIMO Downlink Per-Group Communications With Hybrid Linear Precoding

We address the problem of analyzing and classifying into groups the downlink channel environment in a dense millimeter-wavelength cell, accounting for path loss, multipath fading, and User Equipment (UE) blocking, by employing a hybrid propagation and multipath fading model, thus using accurate inter-group interference modeling. The base station (BS) employs a large Uniform Planar Array (UPA) to facilitate massive Multiple-Input, Multiple-Output (MIMO) communications with high efficiency. UEs are equipped with a single antenna and are distributed uniformly within the cell. The key problem is analyzing and defining groups toward efficient precoding. Because balanced throughput is desired between groups, up to four separate frequency sub-carriers are employed in an Orthogonal Frequency Division Multiple Access (OFDMA) system. We show that by employing three or four OFDMA subcarriers, depending on the number of UEs in the cell and the cell range, the UEs can be efficiently separated into <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">high-throughput</i> groups, with each group employing Virtual Channel Model Beams (VCMB) based inner precoding, followed by efficient Multi-User Multiple-Input Multiple-Output (MU-MIMO) outer precoders. For each group, we study two different sub-grouping methods offering different advantages. We show that the improvement offered by Zero-Forcing Per-Group Precoding (ZF-PGP) over Matched Filter Precoding (MFP) and Zero-Forcing Precoding (ZFP) is very high when finite-alphabet inputs are used. We also show ZF-PGP with finite-alphabet inputs significantly outperforms MFP with Gaussian inputs in certain realistic setups. Finally, a new technique for power allocation among different UEs is proposed, called Optimized Per-Group Power Allocation (OPGPA), which achieves much higher power efficiency jointly with equal throughput among all UEs in each group.

Pattern Synthesis of Subarrayed Large Linear and Planar Arrays Using $K$-Means Solution

In this letter, a new algorithm is presented for synthesizing large linear and planar arrays. To reduce the system cost and implementation complexity, the large array is partitioned into multiple disjoint subarrays and is only weighted at subarray level. By the approximation of the optimization objective, the pattern synthesis problem is first formulated as a weight matching problem. Subsequently, a clustering methodology named $K$ -means approach is adopted to solve this problem. The proposed algorithm can produce a good-shaped pattern, which has lower peak sidelobe level than that synthesized by the state-of-the-art method. Numerical results demonstrate the effectiveness of the proposed algorithm.

Active Vibration Control of a Large Space Antenna Structure Using Cable Actuator

A large space antenna structure will inevitably vibrate due to the space thermal environment and maneuver actions of the satellite. Such vibration will last continuously and affect normal function of the antenna. Therefore, a proper vibration control method is vital to keep the shape accuracy of the structure within an acceptable range. The research object of this paper is a large deployable planar phased array antenna that uses cables as active actuators. Research contents include the optimization of actuator position and the design of control law: both of which have considered the unilateral and saturated constraints of the cable actuator. First, the finite element method is used to obtain the modal information of the structure. Then the actuator position optimization method is established by using the controllability principle and the particle swarm optimization algorithm. Second, a piecewise cost function is adopted to design the control law by combining a linear quadratic regulator with a bang–bang regulator. In the numerical simulation, the vibration control process of an antenna structure consisting of 18 lattices is simulated and analyzed. The results prove that the proposed actuator position optimization method and the control law could effectively suppress the vibration and maintain the shape accuracy of the antenna structure.

An infrared energy harvesting device using planar cross bowtie nanoantenna arrays and diode-less rectification based on electron field emission

ABSTRACT In this paper, we present a rectification process through electron emission from sharp tips under a high electric field of 109–1010 V/m based on the Fowler–Nordheim theory. A large planar array of 104–105 nanoantennas is proposed to achieve the required electric field for electron emission in the nanoantenna gap. Spatial coherence of the incident wave is a prohibitive issue in using large antenna arrays, and it is overcome by choosing proper size for the array. The design starts with a single-element nanoantenna, for which, five different types are considered, namely dipole, spiral, cross bowtie, sinuses and square spiral. Full-wave simulations show that cross bowtie has the highest field enhancement. Moreover, two array configurations, i.e. series and parallel feed networks, are considered and their field enhancement are compared. Moreover, field enhancement in large array configurations is predicted using proposed equations based on curve fitting.

Optimization of Sparse Cross Array Synthesis via Perturbed Convex Optimization.

Three-dimensional (3-D) imaging sonar systems require large planar arrays, which incur hardware costs. In contrast, a cross array consisting of two perpendicular linear arrays can also support 3-D imaging while dramatically reducing the number of sensors. Moreover, the use of an aperiodic sparse array can further reduce the number of sensors efficiently. In this paper, an optimized method for sparse cross array synthesis is proposed. First, the beamforming of a cross array based on a multi-frequency algorithm is simplified for both near-field and far-field. Next, a perturbed convex optimization algorithm is proposed for sparse cross array synthesis. The method based on convex optimization utilizes a first-order Taylor expansion to create position perturbations that can optimize the beam pattern and minimize the number of active sensors. Finally, a cross array with 100 + 100 sensors is employed from which a sparse cross array with 45 + 45 sensors is obtained via the proposed method. The experimental results show that the proposed method is more effective than existing methods for obtaining optimum results for sparse cross array synthesis in both the near-field and far-field.

Adaptive Learning of Probability Density Taper for Large Planar Array Thinning

This article presents a novel optimization algorithm to design a probability density taper for large array thinning. This novel algorithm is based on the iterative Fourier technique (IFT) integrated with an innovative adaptive learning mechanism and denoted as the probability learning IFT (PLIFT) here. With successive forward and backward Fourier transforms, the traditional IFT can be capable of thinning large arrays with high convergence rates, but easily get trapped in local optima. The proposed PLIFT utilizes the probability estimation to describe the elements with possible states of “ON” and “OFF” in a thinned array. A probability model is then adopted to determine the locations of elements in the thinned array featuring minimum sidelobe level. In this PLIFT, on the one hand, the probability model of density taper is learned in optimization process and gradually trained to approach the global optima. With the previous information being honored, the probability model taper proves to be reliable and effective in generating diverse competitive seeds, which, in turn, helps training an optimal probability distribution to best-fit the design goal. Several representative examples of large planar arrays thinning are provided to demonstrate the validity, highlighted global searching ability and increased robustness of the PLIFT.

Efficient Procedure to Design Large Finite Array and Its Feeding Network With Examples of ME-Dipole Array and Microstrip Ridge Gap Waveguide Feed

An efficient procedure to design a large planar array and its corporate feeding network is presented. The procedure is verified by $8 \times8$ and $16\times16$ arrays of magnetoelectric dipoles (ME dipole) fed by microstrip ridge gap waveguide (MRGW) through a narrow slot. This procedure is based on using the frequency-dependent effective input impedance at the port of each element, which includes the effect of the mutual coupling between the antenna elements, which is used to design the corporate feeding network. In addition, the far-field characteristics of the array parameters such as directivity, gain, and the radiation patterns are predicted using the pattern multiplication method including the mutual coupling. The results are verified with the full-wave numerical solution. The procedure requires limited resources and speed up the design cycle. In the presented examples, the array elements are directly excited by the MRGW, which provides more flexibility to design complicated feeding networks and allow for distances between the elements less than a wavelength. Therefore, grating lobes are avoided. To accommodate such constraints, special designs of the power dividers are performed to provide the symmetric location of MRGW lines to avoid coupling between the feeding network lines. Furthermore, a transition from waveguide WR-15 to the MRGW is proposed to differential feed of the array antenna. The $16 \times 16$ array of ME dipoles has been fabricated. The measurement results show a 19% matching bandwidth ( $\vert \text{S}11\vert dB) and measured gain above 30 dBi with radiation efficiency better than 71%, all within a common bandwidth of 56–66 GHz.