Beam Pattern Of Array Research Articles

Task-driven Flexible Array Beampattern Synthesis for Self-organized Drone Swarm

Task-driven Flexible Array Beampattern Synthesis for Self-organized Drone Swarm

Comments on “Frequency Diverse Array Beampattern Synthesis With Taylor Windowed Frequency Offsets”

In recent years, frequency diverse array (FDA) has been actively studied due to its extended capabilities over phased arrays [1]–[3]. Unlike phased arrays whose transmit elements radiate fixed frequencies and generate an angle-dependent beampattern, FDA applies an element-wise tiny incremental frequency shift to provide additional degrees-of-freedom in angle as well as in range dimension [4]–[6]. In a traditional FDA, the element-to-element incremental frequency offset applied is progressive, which results in a time-periodic and S-shaped range-angle coupled beampattern [1]–[6]. However, it is difficult to accurately estimate the target parameters in the presence of such range-angle ambiguity [6]. Consequently, various solutions have been proposed in an effort to avoid such ambiguity in the FDA beampattern. Among them, employing nonlinear frequency offsets, and using nonuniform array configuration are the two prominent solutions to achieve a decoupled range-angle-dependent beampattern [7], [8].

Statistical analysis of the causes of excess variance in the 21 cm signal power spectra obtained with the Low-Frequency Array

Context.The detection of the 21 cm signal of neutral hydrogen from the Epoch of Reionization (EoR) is challenging due to bright foreground sources, radio frequency interference (RFI), and the ionosphere as well as instrumental effects. Even after correcting for these effects in the calibration step and applying foreground removal techniques, the remaining residuals in the observed 21 cm power spectra are still above the thermal noise, which is referred to as the “excess variance.”Aims.We study a number of potential causes of this excess variance based on 13 nights of data obtained with the Low-Frequency Array (LOFAR).Methods.We focused on the impact of gain errors, the sky model, and ionospheric effects on the excess variance by correlating the relevant parameters such as the gain variance over time or frequency, local sidereal time (LST), diffractive scale, and phase structure–function slope with the level of excess variance.Results.Our analysis shows that the excess variance, at the current level, is neither strongly correlated with gain variance nor the ionospheric parameters. Rather, excess variance has an LST dependence, which is related to the power from the sky. Furthermore, the simulated StokesIpower spectra from bright sources and the excess variance show a similar progression over LST with the minimum power appearing at LST bin 6h to 9h. This LST dependence is also present in sky images of the residual StokesIof the observations. In very-wide sky images based on one night of observation after direction-dependent calibration, we demonstrate that the extra power comes exactly from the direction of bright and distant sources Cassiopeia A and Cygnus A with the array beam patterns.Conclusions.These results suggest that the level of excess variance in the 21 cm signal power spectra is related to sky effects and, hence, it depends on LST. In particular, very bright and distant sources such as Cassiopeia A and Cygnus A can dominate the effect. This is in line with earlier studies and offers a path forward toward a solution, since the correlation between the sky-related effects and the excess variance is non-negligible.

On the design of linear sparse arrays with beampattern shift invariant properties

We investigate the design of linear sparse arrays and multiple-input multiple-output (MIMO) linear sparse arrays with beampattern shift invariant property (BSIP) and determine the necessary and sufficient conditions needed to achieve BSIP. Moreover, we show how to theoretically calculate the precise peak sidelobe level (PSL) values of their array beampatterns. We also establish the relationship between the number of antennas and the beampattern of a linear sparse array with BSIP. Furthermore, built on our theoretical analysis, we devise computationally efficient cyclic algorithms to design linear sparse arrays with BSIP and their MIMO counterparts by minimizing the PSL values of their beampatterns. In addition, we introduce a design method to avoid angle ambiguities even when the pointing direction of the linear array beampattern is the extreme case of 90∘ or -90∘. Numerical examples are provided to support our theoretical analysis and demonstrate that our proposed algorithms can be used to obtain linear sparse arrays with 3-dB main beam widths narrower while simultaneously PSL values lower than those of the existing arrays.

Range–Angle Transceiver Beamforming Based on Semicircular-FDA Scheme

Incontrast to the steady angle-dependent transmit beampattern of the conventional phased array, the counterpart of a frequency diverse array (FDA) is basically time variant and range–angle coupled, which limits its potential application in many scenarios. In this article, we consider the beamforming in joint transmit and receive domains to handle the time-variant problem and propose a novel range–angle transceiver beamforming approach based on the semicircular-FDA scheme. In particular, the transceiver scheme of semicircular-FDA is first established.In the sequel, the periodicities of its transceiver beampattern in range and angle dimensions are briefly analyzed. Based on this analysis, a semicircular-FDA applied with nonlinearly increasing frequency offset (NIFO), termed as NIFO semicircular-FDA, is proposed to achieve the beampattern with a single mainlobe peak in range–angle space. Then, an optimization problem is constructed based on an advanced bat algorithm to further reduce the sidelobe level (SLL) of the NIFO semicircular-FDA. Numerical results show that focused time-invariant beampattern with low SLL in both range and angle dimensions can be achieved with the proposed approach.

Biogeography-based optimization with adaptive migration and adaptive mutation with its application in sidelobe reduction of antenna arrays

Biogeography-based optimization (BBO) is a swarm intelligence optimization algorithm based on migration and mutation operations, which is usually used to solve the complex optimization problems. However, it is also a challenging task for conventional BBO to solve some complex and diversified optimization problems with a perfect balance between the performance of exploration and exploitation. In this paper, we propose a variant of BBO approach called BBO with improved migration and adaptive mutation (BBOIMAM) to improve the performance of conventional BBO for dealing with different optimization problems. First, BBOIMAM introduces an improved migration strategy which includes the generalized sinusoidal migration model and immigration strategy based on elite-learning mechanism for the improvement of the local search ability. Second, we propose an adaptive mutation strategy based on the spring vibration to further enhance the population diversity, so that improving the global search ability of the algorithm. By the combination of the proposed improved migration and adaptive mutation strategies, the exploration and exploitation performance of the algorithm can be balanced. We make a large number of experiments on a set of various kinds of benchmark functions, and the experimental results demonstrate that the proposed BBOIMAM approach achieves better performance than several state-of-the-art peer algorithms on CEC 2017 and CEC 2020 test function sets and three cases of the antenna array beam pattern optimization problems.

Design and implementation of a beam-steering antenna array using butler matrix feed network for X-band applications

This article proposes the design, simulation, fabrication and testing of a beam steerable antenna array using a 4 × 4 Butler Matrix feed network technique. The proposed antenna is developed to operate at the X band frequency range. The integrated antenna array and the Butler Matrix feed network operating at 10 GHz has a bandwidth of approximately 2 GHz with an achieved gain of 12 dBi. The main beam pattern of the antenna array is switched between four directions (+10°, −38°, +38°, −10°) providing an effective coverage of over 100°. The proposed antenna has the advantages of low cost, easy fabrication, and simplicity.

Fast Beampattern Synthesis Algorithm for Flexible Conformal Array

This letter first outlines a flexible conformal array geometric model on variable airborne wings, which can undergo complete shape change according to different combat situations, whereas the deformation may result in array beampattern distorted. In order to realize fast beampattern synthesis for a flexible conformal array, we propose a real-time beampattern optimization algorithm, where we split the protoproblem into two sub-problems based on the alternating direction method of multipliers (ADMM). In the first sub-problem, we transform the quadratic inequality constrained problem into a linear equality constrained problem, and then get the iterative update expression for the variables. Unlike the traditional interior point method, the simulation results demonstrate that the proposed algorithm can efficiently solve large-scale convex optimization problems and greatly reduce the computational complexity.

BA-Based Low-PSLL Beampattern Synthesis in the Presence of Array Errors

In practical scenarios, there are always array errors, which would increase the sidelobe level (SLL) of the array and distort the performance of the electronic devices consequently. Nevertheless, most of the reported works do not take these unavoidable errors into consideration when implementing array beampattern synthesis. To remedy this problem, a low sidelobe beampattern synthesis approach is proposed in the presence of array errors based on the bat algorithm (BA). In particular, the covariance matrix of the sidelobe region in the presence of array errors is incorporated into the optimization problem. Generally, there are many factors that would contribute to array errors in practical scenarios. Therefore, to reduce the influence of the uncertainty characteristic of the errors on the low-SLL beampattern synthesis, the statistical mean method is utilized to obtain a robust calculation of the covariance matrix in the presence of array errors. Theoretical analysis using signal processing technique and electromagnetic simulation using Ansoft HFSS workbench are combined to testify the effectiveness of the proposed approach. Numerical results show that peak SLLs (PSLLs) of around −22dB and −20dB can be respectively achieved in the above two simulation situations with the obtained weight vectors.

Optimal Algorithm of Full Focus Array Based on Sparse Matrix

Ultrasonic phased array all-focus imaging algorithm has the advantages of high accuracy and full range dynamic focusing, but the existing imaging time-consuming problem limits its practical industrial application. In order to meet the requirements of real-time imaging and clear and distinguishable image defects in all-focus array ultrasound scanning. In this paper, a sparse optimization model of TFM phased array is established. Based on the Fermat principle, the delay time of each element under two layers of media is calculated, and a two-layer media phased array all-focus imaging algorithm is established, using minimal redundancy. The sparse design of the MRLA is carried out, and the all-focus imaging and sparse all-focus imaging experiments of the two-layer medium are carried out, and the influence of the sparse emission array on the defect quantitative accuracy and the calculation efficiency of the all-focus algorithm is discussed. The final optimized sparse array is compared with the sound field beam pattern of the full array, the smallest redundant array, and the genetic algorithm optimized array, and an all-focus scanning environment is established based on the array. Scanning images can not only obtain the maximum amount of information under minimum redundancy, but also have good sidelobe characteristics. At the same time, the array is sparse, which greatly improves the efficiency of all-focus scanning, and provides a certain reference value for the research of all-focus imaging technology.

An improved multiobjective evolutionary algorithm based on decomposition approach and its application in antenna array beam pattern synthesis

AbstractAntenna arrays can enhance the performance and reduce the overhead of the wireless communication systems. However, the beam pattern synthesis of antenna arrays are difficult problems since the optimization properties are usually trade‐offs that affect each other. In this paper, we formulate a multiobjective beam pattern optimization problem (MBPOP) to simultaneously reduce the maximum sidelobe level (SLL) and achieve the nulls of the antenna array beam pattern. The multiobjective evolutionary algorithm based on decomposition (MOEA/D) is a general and effective algorithm to solve the MOPs. However, it may be easy to lose population diversity and converge to local optimum. To overcome the issues above, we propose an improved MOEA/D (IMOEA/D) to deal with the formulated MBPOP. IMOEA/D introduces the normal distribution crossover operator (NDX), Lévy flight strategy and Euclidean distance‐based solution selection mechanism to enhance the performance of conventional MOEA/D to make it more suitable to solve the formulated MBPOP. Experiments are conducted and the results indicate that the proposed IMOEA/D has a better performance in terms of the convergence rate and population diversity compared to other algorithms for solving the formulated MBPOP.

MULTIPLE DIRECTION INTERFERENCE SUPPRESSION BY UNIFORM LINEAR PHASED ARRAY SIDELOBE EFFICIENT CANCELLER

Background. For radar systems, the beam pattern of a uniform linear array (ULA) is synthesized to ensure signal selectivity by direction. A specific ULA sidelobe is cancelled by rescaling the beam weights. In particular, this is done by increasing the number of sensors and shortening the scanning step. However, a noticeable limitation is a loss of the transmitted power. Therefore, the problem is to optimally balance the number of sensors versus effective ULA sidelobe cancellation.
 Objective. In order to ensure multiple direction interference suppression, the goal is to find an optimal number of ULA radar sensors for the beam pattern synthesis. The criterion is to determine such a minimum of these sensors at which mainlobes towards useful signal directions are evened as much as possible.
 Methods. To achieve the said goal, the ULA sidelobe cancellation is simulated. The simulation is configured and carried out by using MATLAB® R2020b Phased Array System ToolboxTM functions based on an algorithm of the sidelobe cancellation.
 Results. By increasing the number of ULA sensors, the beam pattern lobes are not only thinned but also change in their power. In particular, the interference direction sidelobes become relatively stronger. The number of sensors is limited by the three influencing factors: the thinned-array curse transmitted power loss, the aperture size, and the sidelobes intensification.
 Conclusions. An optimal number of ULA radar sensors for the beam pattern synthesis can be found when the scanning step is equal to the least distance between adjacent interference directions. At the start, the number of sensors is set at the number of useful signal directions. If the mainlobes towards useful signal directions are not evened enough, the set of interference directions is corrected.
 Keywords: radar phased array; beam pattern; interference direction; sidelobe cancellation; aperture size.

Robust Range Ambiguous Deceptive Target Suppression Based on Covariance Matrix Reconstruction

When the deceptive targets are in the ambiguious range bin but are received at the same range gate with the desired target by the array, the traditional multiple-input multiple-output (MIMO) radar is not able to discriminate between them. Based on the unique range-dependent beampattern of the frequency diverse array (FDA)-MIMO radar, we propose a novel robust mainlobe deceptive target suppression method based on covariance matrix reconstruction to form nulls at the frequency points of the transmit–receive domain where deceptive targets are located. First, the proposed method collects the deceptive targets and noise information in the transmit–receive frequency domain to reconstruct the jammer-noise covariance matrix (JNCM). Then, the covariance matrix of the desired target is constructed in the desired target region, which is assumed to already be known. The transmit–receive steering vector (SV) of the desired target is estimated to be the dominant eigenvector of the desired target covariance matrix. Finally, the weighting vector of the receive beamformer is calculated by combining the reconstructed JNCM and the estimated desired target SV. By implementing the weighting vector at the receiving end, the deceptive targets can be effectively suppressed. The simulation results demonstrate that the proposed method is robust to SV mismatches and provides a signal-to-jamming-plus-noise ratio (SJNR) output that is close to the optimal.

An improved biogeography‐based optimization approach for beam pattern optimizations of linear and circular antenna arrays

AbstractAntenna array makes an increasingly valuable contribution to various fields of communications. The beam pattern synthesis is one of the significant properties of antenna array. In this article, suppressing the maximum sidelobe levels (SLLs) of different antenna arrays is our main objective. Specifically, we first formulate the beam pattern optimization problems of the linear antenna array (LAA) and circular antenna array (CAA), respectively, and propose an improved biogeography‐based optimization (IBBO) approach to tackle the issue. IBBO introduces the hybrid migration and hybrid mutation operators by adopting several improved factors to strengthen the effect of conventional biogeography‐based optimization (BBO) algorithm. Emulate experiments are built to evaluate the performance of the IBBO for dealing with the formulated antenna array beam pattern optimization problems comprehensively.

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

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

An Effective Artificial Neural Network-Based Method for Linear Array Beampattern Synthesis

The beampattern synthesis of antenna array is always known as a computationally cost task that needs efficient strategies to deal with. In this article, a novel artificial neural network (ANN)-based array synthesis method is proposed. By establishing an encoder–decoder-based ANN framework, the mask-constrained beampattern in terms of focused or shaped beam for linear arrays with arbitrary given array geometry is successfully synthesized. More in detail, the encoder serves as an array synthesizer, while the decoder behaves as an array analyzer. Thanks to the designed pretrained decoder, such an approach is computationally efficient so that real-time array synthesis can be potentially achieved. Moreover, the proposed method allows one to consider both ideal and actual linear arrays with mutual coupling effects and nonidealities. The results of a wide numerical validation involving amplitude-only, phase-only, and amplitude–phase excitation syntheses are presented to assess the flexibility and the versatility of the proposed method also in comparison to the competitive state-of-the-art synthesis techniques.

ADMM-based array antenna synthesis algorithm with reconfigurable pattern element selection

The paper considers the array beam pattern synthesis (BPS) problem with reconfigurable pattern elements (RPE). Both the array weight and the array pattern are optimized, which further suppresses the peak sidelobe level (PSLL) compared with the fixed pattern array. For the array pattern optimization, the conventional selecting of appropriate N elements from K radiation patterns requires to evaluate all possible KN choices, resulting in the non-deterministic polynomial-hard RPE selection problem. In this work, this problem is solved through investigating different element pattern combinations with randomly arranged pattern locations. In such way, the possible solutions to the RPE selection problem has an overall choices of CN+K−1K−1=(N+K−1)!N!(K−1)!, which extremely shrinks the solution space. An algorithm with the RPE selection and array weight optimization is proposed for the BPS problem. Furthermore, the alterative direction method of multipliers (ADMM) framework is introduced to accelerate the computation speed. The proposed algorithm provides an effective scheme for generating appropriate RPE combinations for PSLL suppression, resulting in a wider-angular scanning ability for array antenna. Simulation results demonstrate 0 dB to 4 dB lower PSLL can be obtained compared with the algorithms based on the fixed element pattern.

A calibration and imaging strategy at 300 MHz with the Murchison Widefield Array (MWA)

AbstractAt relatively high frequencies, highly sensitive grating sidelobes occur in the primary beam patterns of low frequency aperture arrays (LFAA) such as the Murchison Widefield Array (MWA). This occurs when the observing wavelength becomes comparable to the dipole separation for LFAA tiles, which for the MWA occurs at${\sim}300$MHz. The presence of these grating sidelobes has made calibration and image processing for 300 MHz MWA observations difficult. This work presents a new calibration and imaging strategy which employs existing techniques to process two example 300 MHz MWA observations. Observations are initially calibrated using a new 300 MHz sky-model which has been interpolated from low frequency and high frequency all-sky surveys. Using this 300 MHz model in conjunction with the accurate MWA tile primary beam model, we perform sky-model calibration for the two example observations. After initial calibration a self-calibration loop is performed by all-sky imaging each observation. We mask the main lobe of the all-sky image, and perform a sky-subtraction by estimating the masked image visibilities. We then image the main lobe of the sky-subtracted visibilities, which results in high dynamic range images of the two example observations. These images have been convolved with a Gaussian to a resolution of$2.4$arcminutes, with a maximum sensitivity of${{\sim}}31\,\textrm{mJy/beam}$. The calibration and imaging strategy demonstrated in this work opens the door to performing science at 300 MHz with the MWA, which was previously an inaccessible domain. With this paper we release the code described below and the cross-matched catalogue along with the code to produce a sky-model in the range 70–1 400 MHz.

Pencil and Shaped Beam Patterns Synthesis Using a Hybrid GA/l₁ Optimization and Its Application to Improve Spectral Efficiency of Massive MIMO Systems

The synthesis of pencil beam and arbitrarily shaped beam patterns of linear antenna arrays (LAA) using reduced number of antenna elements attracts the attention of researchers in recent years. In this paper, a hybrid beamforming technique based on the combination of the genetic algorithm (GA) optimization technique and the l <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sub> minimization method denoted as (GA/l <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sub> ) is introduced for LAAs synthesis. The proposed GA/l <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sub> beamforming technique optimizes both the elements excitations and interelement spacing to synthesize the desired LAA pattern with a minimum number of antenna elements. The GA/l <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sub> technique provides an excellent approximation to the desired radiation pattern with high accuracy and low complexity (less number of iterations and computational time) compared to the other synthesis approaches introduced in the literature. In addition, as an application of this work, the proposed GA/l <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sub> technique is used to build up a proposed hybrid precoding and beamforming (HP-BF) structure for Massive Multi-input Multi-output (M-MIMO) systems. In this structure, the transmit antenna array is synthesized for maximum gain realization using the existing number of antenna elements. In the HP-BF structure, the proposed GA/l <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sub> technique is used to make full use of the existing transmit array elements to synthesize the radiation pattern of much larger size and higher gain arrays without the need for additional elements. Thereby, significant savings in the number of antenna elements and their corresponding radio frequency (RF) chains are achieved, which reduces the system complexity. In addition, the array gain maximization will maximize the received signal to noise ratio (SNR) giving rise to higher system performance in terms of spectral efficiency (SE) and power utilization.

A Partition Spatial Filtering Method for Acoustic Array Configuration

Acoustic array is a ubiquitous tool for locating and quantifying sound sources. However, its effectiveness depends greatly on the array configuration. This paper presents an array configuration method to enhance array performance, especially on the spatial resolution and the Doppler effect correction. The problem of array configuration is formulated into a position matrix determined by introducing partition spatial filtering. Irregular coaxial ring grid spacings and partition filtering conditions are suggested to control array spatial resolution. Geometrical parameters and performance indicators are constructed to quantify the relationships between the array configuration and performance. Based on these quantitative relations, the spatial variation of the array beam pattern and the Doppler effect has got adaptive adjustment. In particular, an adaptive partition algorithm is proposed to reduce computation time. The performance of the method is examined numerically and experimentally, which is compared with the other methods. The results provide the method to guide the design of a 64‐microphone optimized array with high performance (1.8° spatial angle resolution and 40% Doppler frequency correction over the bandwidth from 800 Hz to 3000 Hz) and fast computing speed (18 s array generated time for 2000 arrays). Furthermore, an unusual feature of the method is that it can be utilized in the case when the source moves at a nonconstant velocity.