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This study presents a novel optimization method based on the sand cat swarm optimization (SCSO) algorithm for the pattern synthesis of linear antenna-array (LAA), aiming to obtain the high gain and low sidelobe level (SLL). The innovation of the proposed method consists in efficiently regulating the radiation characteristics of the LAA by optimizing the geometric and electrical parameters including the phase, amplitude, rotation and position based on the SCSO algorithm to achieve the desired radiation performances. The full-wave method of moments (MoM) is adopted to rigorously consider the mutual coupling effect among the array elements to guarantee the design accuracy. To demonstrate the feasibility and effectiveness of the SCSO algorithm, the proposed method is compared with three typical algorithms, including the Genetic Algorithm (GA), the Gray Wolf (GWO) algorithm, and the Particle Swarm Optimization (PSO). The results show that the SCSO algorithm demonstrates superior convergence capabilities while maintaining the high gain and low SLL, highlighting the potential as a robust method for the LAA. [ABSTRACT FROM AUTHOR]

Abstract Time-modulated array antenna (TMAA) is a new type of array antenna based on time modulation technology. By introducing "time" as the fourth dimensional design freedom into the design of conventional array antennas in three-dimensional space, the array antenna has time modulation characteristics, which better controls the radiation characteristics of the array antenna and achieves the best far-field radiation pattern synthesis. This paper designs a Time-modulated linear array (TMLA) with low sidelobe level (SLL) and low sideband level (SBL) based on the chaotic exchange nonlinear dandelion optimization (CENDO) algorithm. Three optimization methods are studied: firstly, determining the optimal on-time (τ nn ) for each array element; The second is to determine the optimal on-time (τ nn ) and optimal uniform array element spacing (d) for each array element; The third is to determine the optimal opening time (t on ), closing time (t off ), and optimal uniform array element spacing (d) for each array element. To achieve simultaneous reduction of sidelobe level and suppression of harmonic interference. The same array model contains different harmonic frequency radiation. In this article, we only considered two harmonic frequencies, namely the first sideband frequency and the second sideband frequency. Because the harmonic of other sideband frequencies has a very small impact on the radiation of the fundamental wave, it can be ignored. To demonstrate the stronger ability of the CENDO algorithm in optimizing Time-modulated array antennas, and in line with the principle of fairness and impartiality, this paper also simulates different Time-modulated array models and compares the results of the CENDO algorithm with other published literature. It is concluded that this study shows lower SLL and lower SBL in different models. This provides a more scientific and accurate explanation of the superiority of the CENDO algorithm compared to other algorithms in the field of antenna optimization in electromagnetics. At the same time, this also provides great research value and fundamental support for designing high-performance Time-modulated array antennas in subsequent engineering applications.

In this paper, we develop a new algorithm for pattern synthesis of large linear arrays. In our algorithm, the large linear array is divided into multiple disjoint nonuniformly-spaced subarrays and is only weighted at subarray level. Unlike the existing methods, the subarray synthesis is implemented in two stages. Firstly, the optimization of subarray partition and subarray weights are performed by using the K-means approach. Based on the determined subarray partition and subarray weights, the subarray element positions are further optimized by the iterative convex programming method. Compared with the state-of-the-art methods, the proposed algorithm can synthesize lower peak sidelobe level and yield smaller pattern matching error. Numerical results demonstrate the effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

The design of an effective antenna array is a major challenge encountered in most communication systems. A much-needed requirement is obtaining a directional and high-gain radiation pattern. This study deals with the design of a linear antenna array that radiates with reduced peak-side lobe levels (PSLL), decreases side-lobe average power with and without the first null beamwidth (FNBW) constraint, places deep nulls in the desired direction, and minimizes the close-in-side lobe levels (CSLL). The nature-inspired metaheuristic algorithm multi-verse optimization (MVO) is explored with other state-of-the-art algorithms to optimize the parameters of the antenna array. MVO is a global search method that is less prone to being stuck in the local optimal solution, providing a better alternative for beam-pattern synthesis. Eleven design examples have been demonstrated, which optimizes the amplitude and position of antenna array elements. The simulation results illustrate that MVO outperforms other algorithms in all the design examples and greatly enhances the radiation characteristics, thus promoting industrial innovation in antenna array design. In addition, the MVO algorithm's performance was validated using the Wilcoxon non-parametric test. [ABSTRACT FROM AUTHOR]

This paper introduces an application of the dandelion optimization (DO) algorithm in antenna arrays. This is the first time that the DO algorithm has been used for optimizing antenna arrays. For antenna array optimization, sidelobe level (SLL) and deep nulls are key technical indicators. A lower SLL can improve the signal-to-noise ratio and reduce the impact of clutter signals outside the main beam. Deep nulls need to be aligned with the direction of interference to eliminate the influence of interference sources. The combination of the two can effectively improve the anti-interference ability of the entire system. Therefore, antenna arrays with ultra-low sidelobes and ultra-deep nulls are currently hot in the field of antenna array design and are also some of the key technologies needed to achieve modern high-performance radar systems. As a new type of evolutionary algorithm inspired by nature, the DO algorithm is inspired by the wind propagation behavior of dandelions in nature. This algorithm iteratively updates the population from three stages of ascent, descent, and landing, ultimately finding the optimal position. It has good optimization ability in solving complex problems such as those involving nonlinearity, discreteness, and non-convexity, and the antenna array pattern synthesis optimization problem belongs to multivariate nonlinear problems. Therefore, the DO algorithm can be effectively applied in the field of antenna array optimization. In this work, we use the following method to obtain an optimized pattern of a linear array with the lowest sidelobe level (SLL), null placement in particular directions, and a lower notch in particular directions: by controlling the antenna array's element spacing and leaving the phase unchanged to optimize the current amplitudes and by controlling the excitation current and phase fixation of the antenna array and changing the element spacing. In the first and second examples, different algorithms are used to reduce the SLL of the antenna. In the first example, the DO algorithm reduces the SLL to −33.37 dB, which is 2.67 dB, 2.67 dB, 3.77 dB, 2.74 dB, and 2.52 dB lower than five other algorithms. In the second example, the SLL optimized by the DO algorithm is −42.56 dB, which is 5.04 dB and 1.48 dB lower than two other algorithms. In both examples, the DO algorithm reduces the SLL lower than other algorithms when the main lobe of the antenna is not significantly widened. Examples 3, 4, and 5 use the DO algorithm to optimize the amplitude of the current, generating deep nulls and deep notches in specific directions. In Example 3, the DO algorithm obtains a depth of nulls equal to −187.6 dB, which is 66.7 dB and 44.3 dB lower than that of the flower pollination algorithm (FPA) and the chaotic colony predation algorithm (CCPA), respectively. In Example 4, the deep null obtained by the DO algorithm is as low as −98.69 dB, which is 6.67 dB lower than the deep null obtained by the grey wolf optimization (GWO) algorithm. In Example 5, the deep notch obtained by the DO algorithm is as low as −63.1 dB, which is 6.4 dB and 1.9 dB lower than the spider monkey optimization (SMO) algorithm and the grasshopper optimization algorithm (GOA), respectively. The data prove that the DO algorithm produces deeper nulls and notches than other algorithms. The last two examples involve reducing sidelobe levels and generating deep nulls by optimizing the spacing between elements. In Example 5, the SLL obtained using the DO algorithm is −22.8766 dB, which is 0.1998 dB lower than the lowest SLL of −22.6768 dB among other algorithms. In Example 6, the SLL obtained using the DO algorithm is −20.1012 dB, and the null depth is −125.1 dB, which is 1.592 dB lower than the SLL obtained by the cat swarm optimization (CSO) algorithm and 19.1 dB lower than the deep null obtained by the GWO algorithm, respectively. In summary, the results of six simulation experiments indicate that the DO algorithm has better optimization ability in linear array optimization than other evolutionary algorithms. [ABSTRACT FROM AUTHOR]

This work introduces a novel approach for predicting the complex element weights of a rectangular planar phased array for a desired beam pattern using physics-aware convolutional neural networks (PA-CNN). An image representation of the desired radiation pattern is provided as input to the proposed network architecture, where PA-CNN learns to recognize spatial features and map input patterns to the amplitude and phase of the antenna element weights. In addition to the classical mean squared error (MSE) loss for regression to true weights, a novel physics-aware loss function is designed to jointly force the PA-CNN to estimate true weight while generating physically consistent beam patterns. The performance of the proposed model is evaluated using metrics such as MSE of estimated weights and traditional radiation pattern metrics such as accuracy of peak direction. The obtained results demonstrate that the models successfully learn the nonlinear relation between antenna parameters and desired beam patterns, where the physics-aware approach outperforms the base CNN cases with an improvement of 6.2% in the MSE between radiation patterns. This approach provides a promising solution for learning complex weights of arrays for synthesizing desired patterns while ensuring physical consistency.

A novel approach is presented for synthesizing radiation patterns of substrate-integrated waveguide leaky wave antennas in two stages. In the first stage, the antenna is considered an equivalent rectangular waveguide with slots, and a comprehensive equivalent circuit model is constructed. Varying slot configurations are accommodated by the developed equivalent circuit model. Each slot section is represented as an admittance with the incorporation of Elliott’s slot theory. Computations of the relative aperture fields are performed using circuit theory, and the far-field pattern is estimated through array theory. In the second stage, the circuit model is utilized for genetic algorithm-based optimization, enabling customization of the radiation pattern to meet specific requirements. The methodology has a computational advantage over full-wave simulations, resulting in a significantly faster and more efficient design process. Numerical verification through simulation of various examples and experimental validation through antenna fabrication are presented, affirming agreement between calculated and measured results. Remarkable effectiveness in antenna engineering can be attained for future wireless communication systems by using the proposed technique.

A single-feed broadband quasi-isotropic antenna was designed for non-line-of-sight (NLOS) wireless sensor networks. The proposed antenna is based on a combination of fork-shaped crossed dipoles. It shows the broadband of quasi-isotropic radiation characteristics with high radiation efficiency. The electrical size ka of the proposed antenna is 0.94 with respect to its lower operating frequency. Its profile is also extremely thin at 0.0015λ. The impedance is matched from 1.8 to 4.3 GHz, or an 81.9% fractional bandwidth, whereas the maximum gain deviation ranging from 6.2 to 9.2 dB for the quasi-isotropic radiation is achieved from 1.8 to 3.6 GHz with a 10 dB criterion, which is close to the impedance bandwidth. The performance from the computed expectations is verified, as it shows a gain deviation of 8.4–9.8 dB from 1.9 to 3.3 GHz with an 80% fractional impedance bandwidth. The proposed antenna also shows good spatial coverage of circular polarization at high frequencies. Lastly, the received power level performance of the proposed antenna is tested under the NLOS condition, which shows a higher level compared to the linearly polarized, broadband omni-directional monopole antenna. [ABSTRACT FROM AUTHOR]

High-performance beamforming incorporating multiple objectives for large-scale antenna arrays becomes increasingly important to improve the capacity and efficiency of wireless communication systems. The speed of synthesizing a desired beam pattern is critical in wireless communications systems to adapt to highly dynamic wireless channels. A modified particle swarm optimization (PSO) algorithm for synthesizing array beam patterns is proposed in this study. The initial positions of particles in PSO are designated following a Taylor distribution instead of being given uniformly distributed random values as in the classical PSO algorithm. The fitness functions are defined to include multiple objectives represented by producing multiple main lobes with customized deep and broadened nulls. Several scenarios have been established to examine the feasibility of the proposed algorithm. Moreover, the performance of the proposed algorithm is compared with those of the ones based on the classical PSO. A significant performance improvement for obtaining beamforming coefficients has been achieved. The robustness of the proposed algorithm is demonstrated further by applying it to a finite array on a curved surface for beamforming. [ABSTRACT FROM AUTHOR]

The grey wolf optimization (GWO) algorithm is a new nature-inspired meta-heuristic algorithm inspired by the social hierarchy and hunting behavior of grey wolves. In this paper, the GWO algorithm is improved to overcome previous shortcomings of being easily trapped in local optima and having a low convergence rate. The proposed enhancement of the GWO algorithm utilizes logistic-tent double mapping to generate initialized populations, which enhances its global search capability and convergence rate. This improvement is called the nonlinear chaotic grey wolf optimization (NCGWO) algorithm. The performance of the NCGWO algorithm was evaluated with four representative benchmark functions. Then, the NCGWO algorithm was applied to perform an optimal pattern synthesis of linear array antennas (LAAs) using two distinct approaches: optimizing the amplitudes of the antenna currents while preserving uniform spacing and optimizing the positions of the antennas while assuming uniform excitation. To validate the effectiveness of the proposed approach, the results obtained by the NCGWO algorithm were compared with those obtained by other intelligent algorithms. Additionally, the NCGWO algorithm was applied to a more complex planar antenna array to further validate its performance. Our results demonstrate that the NCGWO algorithm exhibits superior performance regarding electromagnetic optimization problems compared to widely recognized algorithms. [ABSTRACT FROM AUTHOR]

This paper introduces an application of the dandelion optimization (DO) algorithm in antenna arrays. This is the first time that the DO algorithm has been used for optimizing antenna arrays. For antenna array optimization, sidelobe level (SLL) and deep nulls are key technical indicators. A lower SLL can improve the signal-to-noise ratio and reduce the impact of clutter signals outside the main beam. Deep nulls need to be aligned with the direction of interference to eliminate the influence of interference sources. The combination of the two can effectively improve the anti-interference ability of the entire system. Therefore, antenna arrays with ultra-low sidelobes and ultra-deep nulls are currently hot in the field of antenna array design and are also some of the key technologies needed to achieve modern high-performance radar systems. As a new type of evolutionary algorithm inspired by nature, the DO algorithm is inspired by the wind propagation behavior of dandelions in nature. This algorithm iteratively updates the population from three stages of ascent, descent, and landing, ultimately finding the optimal position. It has good optimization ability in solving complex problems such as those involving nonlinearity, discreteness, and non-convexity, and the antenna array pattern synthesis optimization problem belongs to multivariate nonlinear problems. Therefore, the DO algorithm can be effectively applied in the field of antenna array optimization. In this work, we use the following method to obtain an optimized pattern of a linear array with the lowest sidelobe level (SLL), null placement in particular directions, and a lower notch in particular directions: by controlling the antenna array’s element spacing and leaving the phase unchanged to optimize the current amplitudes and by controlling the excitation current and phase fixation of the antenna array and changing the element spacing. In the first and second examples, different algorithms are used to reduce the SLL of the antenna. In the first example, the DO algorithm reduces the SLL to −33.37 dB, which is 2.67 dB, 2.67 dB, 3.77 dB, 2.74 dB, and 2.52 dB lower than five other algorithms. In the second example, the SLL optimized by the DO algorithm is −42.56 dB, which is 5.04 dB and 1.48 dB lower than two other algorithms. In both examples, the DO algorithm reduces the SLL lower than other algorithms when the main lobe of the antenna is not significantly widened. Examples 3, 4, and 5 use the DO algorithm to optimize the amplitude of the current, generating deep nulls and deep notches in specific directions. In Example 3, the DO algorithm obtains a depth of nulls equal to −187.6 dB, which is 66.7 dB and 44.3 dB lower than that of the flower pollination algorithm (FPA) and the chaotic colony predation algorithm (CCPA), respectively. In Example 4, the deep null obtained by the DO algorithm is as low as −98.69 dB, which is 6.67 dB lower than the deep null obtained by the grey wolf optimization (GWO) algorithm. In Example 5, the deep notch obtained by the DO algorithm is as low as −63.1 dB, which is 6.4 dB and 1.9 dB lower than the spider monkey optimization (SMO) algorithm and the grasshopper optimization algorithm (GOA), respectively. The data prove that the DO algorithm produces deeper nulls and notches than other algorithms. The last two examples involve reducing sidelobe levels and generating deep nulls by optimizing the spacing between elements. In Example 5, the SLL obtained using the DO algorithm is −22.8766 dB, which is 0.1998 dB lower than the lowest SLL of −22.6768 dB among other algorithms. In Example 6, the SLL obtained using the DO algorithm is −20.1012 dB, and the null depth is −125.1 dB, which is 1.592 dB lower than the SLL obtained by the cat swarm optimization (CSO) algorithm and 19.1 dB lower than the deep null obtained by the GWO algorithm, respectively. In summary, the results of six simulation experiments indicate that the DO algorithm has better optimization ability in linear array optimization than other evolutionary algorithms.

In order to solve the design problem of wideband wide-angle low sidelobed phased array antenna caused by factors such as large loss, manufacturing process, T/R component size, number of channels and location, a wideband type horn antenna unit in the frequency range of 80~110 GHz is designed in this study, and the antenna standing wave ratio is less than 1.8. Considering the space limitation of T/R components, a 64-element high-gain, low-sidelobe, wide-band and wide-angle scanning array antenna is designed by optimizing the array position, and a small low-profile air waveguide feeding network is designed for the array. The simulation results show that the designed 64 element sparse array has the advantages of wide bandwidth, wide angle, low sidelobes, high gain, easy fabrication and realization, and the gain is higher than 22.6 dB, the sidelobes level is lower than -6.2 dB, and the active VSWR of each element is less than 2 under the scanning range of ±40°. [ABSTRACT FROM AUTHOR]

A deep learning neural network model in conjunction with a method to incorporate auxiliary surface waves is developed for the macroscopic design of transmitting metasurfaces. The main input to the neural network model is the user-defined desired far-field specifications. This network is used to calculate the required tangential electromagnetic fields on the metasurface. These fields will then be augmented by incorporating auxiliary surface waves along the metasurface for power redistribution to satisfy the requirement for having lossless and passive metasurfaces. The designs will then be evaluated using full-wave simulations of metasurfaces with three-layer unit cell topology in both 2D and 3D scenarios.

Despite playing a central role in antenna design, aperture efficiency is often disregarded. Consequently, the present study shows that maximizing the aperture efficiency reduces the required number of radiating elements, which leads to cheaper antennas with more directivity. For this, it is considered that the boundary of the antenna aperture has to be inversely proportional to the half-power beamwidth of the desired footprint for each ϕ -cut. As an example of application, it has been considered the rectangular footprint, for which a mathematical expression was deduced to calculate the aperture efficiency in terms of the beamwidth, synthesizing a rectangular footprint of a 2:1 aspect ratio by starting from a pure real flat-topped beam pattern. In addition, a more realistic pattern was studied, the asymmetric coverage defined by the European Telecommunications Satellite Organization, including the numerical computation of the contour of the resulting antenna and its aperture efficiency. [ABSTRACT FROM AUTHOR]

A single-feed broadband quasi-isotropic antenna was designed for non-line-of-sight (NLOS) wireless sensor networks. The proposed antenna is based on a combination of fork-shaped crossed dipoles. It shows the broadband of quasi-isotropic radiation characteristics with high radiation efficiency. The electrical size ka of the proposed antenna is 0.94 with respect to its lower operating frequency. Its profile is also extremely thin at 0.0015λ. The impedance is matched from 1.8 to 4.3 GHz, or an 81.9% fractional bandwidth, whereas the maximum gain deviation ranging from 6.2 to 9.2 dB for the quasi-isotropic radiation is achieved from 1.8 to 3.6 GHz with a 10 dB criterion, which is close to the impedance bandwidth. The performance from the computed expectations is verified, as it shows a gain deviation of 8.4–9.8 dB from 1.9 to 3.3 GHz with an 80% fractional impedance bandwidth. The proposed antenna also shows good spatial coverage of circular polarization at high frequencies. Lastly, the received power level performance of the proposed antenna is tested under the NLOS condition, which shows a higher level compared to the linearly polarized, broadband omni-directional monopole antenna.

We present a new deep learning framework for removing honeycomb artifacts yielded by optical path blocking of cladding layers in fiber bundle imaging. The proposed framework, HAR-CNN, provides an end-to-end mapping from a raw fiber bundle image to an artifact-free image via a convolution neural network (CNN). The synthesis of honeycomb patterns on ordinary images allows conveniently learning and validating the network without the enormous ground truth collection by extra hardware setups. As a result, HAR-CNN shows significant performance improvement in honeycomb pattern removal and also detailed preservation for the 1961 USAF chart sample, compared with other conventional methods. Finally, HAR-CNN is GPU-accelerated for real-time processing and enhanced image mosaicking performance. [ABSTRACT FROM AUTHOR]

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.

Compared with the traditional antenna array, the time-modulated array can increase the flexibility of the array by adding time switches. However, due to the introduction of time switches, the time-modulated array antenna is more sensitive to random errors than the traditional array. Besides random errors caused by unavoidable factors such as array deformation and defects of processing and assembly in the traditional array, time-modulation parameter errors will be introduced by time switches. As errors in the traditional array can degrade the performance of the array, time-modulation parameter errors can lower the performance of the array pattern as well, which will lift the side-lobe and increase the dynamic range of the side-lobe. Aiming at the time-modulation parameter errors in the time-modulated array, an anti-error robust pattern synthesis algorithm (AERPS) based on the convex optimization (CVX) is proposed in this paper. In the algorithm, the optimization model for the pattern synthesis of the time-modulated array is established and analyzed. Then the model is divided into two sub-models of the center frequency and the first sideband, and the convex optimization solution is first performed on the center frequency model. After the center frequency model is solved, the convex optimization solution is used to solve the first-order sideband model to obtain the final results. The simulation results of the time-modulated array in this paper show that the algorithm can reduce the average value and the dynamic range of the normalized side-lobe level, thus verifying the effectiveness and the robustness of the algorithm.

A beam-changeable concentric annular Leaky-Wave Antenna (LWA) array is proposed, which contains two annular LWAs with constant-interval slots. By changing the excitations of the two LWAs, the radiation beam can be changed to different shapes and in different directions i.e. single beam to normal direction, conical beam to 40° and a synthetic beam. A theoretical model for analyzing the radiation properties of the LWA array is put forward, and a prototype of the array with the radius of 42.6 mm and the height of 4 mm is fabricated. By comparing simulation and the measurement results, it is found that the proposed LWA array exhibits a very well expected performance. The proposed antenna array is then applied to construct a self-sensing smart antenna which can provide flexible radio wave coverage according to the positions of users. Image-aware function is integrated into the smart antenna, and a series of tests including received power and Error Vector Magnitude (EVM) measurements are carried out in indoor scenarios. The results verify the effectiveness of the design.

For the anti-interference/denoise purpose, it usually requires minimizing the sidelobe level (SLL) of a wide-beam pattern with a desired low nulling level (NL) in the nulling region. To realize such an objective, the shaped-beam pattern synthesis (SBPS) is the most commonly used approach. However, since the SBPS problem focuses on synthesizing a predetermined beam shape, the minimum SLL via this approach cannot ensure to obtain the maximum power gain. Conversely, it cannot obtain the lowest SLL with a certain power gain requirement. Based on such consideration, this paper tries to further minimize SLL of a wide-beam pattern with a desired low NL nulling region, by solving the power gain pattern synthesis (PGPS) problem. The PGPS problem selects the array excitation by directly optimizing the power gain. Hence, it has the potential to reduce SLL, when achieving the equal mainlobe power gain constraint via SBPS. An iterative algorithm which converts the primal optimization problem into convex sub-problems is proposed, resulting in an effective problem-solving scheme. Numerical simulations demonstrate the proposed algorithm can obtain about 10-dB lower SLL than the existing algorithms.

In this article, a gradient-based phase-only synthesis approach for solving the Q-N clustering problem of planar clustered phased arrays (CPAs) for sidelobe suppression is presented. Through establishing an appropriate parameterization scheme, the synthesis problem is transformed to an unconstrained continuous problem which is suitable for solving with the gradient-based algorithm. The synthesis is carried out through simultaneously optimizing the clustering variables and the phase variables, and the $Q$ - $N$ problem is addressed without reducing the feasible region of the problem. Typical examples are provided to validate the effectiveness of the proposed approach. In addition, by considering several steering angles in the proposed synthesis approach, the scanning issue in the clustering problem is clarified and discussed. [ABSTRACT FROM AUTHOR]

In this paper, we devise a new hybrid method for pattern synthesis of large linear arrays. To simplify the beamforming network, the uniform linear array is divided into multiple non-overlapped subarrays with contiguous elements and is only weighted at subarrays. Unlike previous approaches, the proposed method introduces a special vector to specify the subarray partition and converts the subarray pattern synthesis to the problem of finding the optimal subarray partition and subarray weighting vectors simultaneously. To solve this problem efficiently, the genetic algorithm is utilized to find the optimal partition scheme from all possible subarray partitions. For the fixed subarray partition, the optimal subarray weighting vector is obtained by solving the convex sub-problem. Numerical results demonstrate the superiority of our method over the state-of-the-art algorithm. [ABSTRACT FROM AUTHOR]

In this paper, a novel approach for synthesizing multiple radiation patterns with reduced hardware complexity in the feed network by exploiting the additional degree of freedom ‘time’ in time modulated unequally spaced linear array (TMUSLA) is presented. In the proposed approach, with a suitable common set of element position of TMUSLA, the desired dual-beam pattern with low sidelobe level (SLL) is obtained by simply controlling the ON-OFF time sequence of the RF switches connected to the array elements. To show the effectiveness of the proposed array synthesis method, two dual beam patterns - first one as pencil (sum) beam (PB) and flat-topped beam (FTB) pattern, and the second one as sum and difference pattern with different constraints have been synthesized. For the successful generation of the desired power patterns, differential evolution (DE) algorithm is employed to obtain the optimum possible solution in terms of common element position, time-modulation, switching sequences and applicable excitation phase for the desired shape beam patterns. The superiority of the proposed approach with the favourable improved performance have been demonstrated by comparing the realized patterns with the state-of-the-art relevant reported works.

Despite playing a central role in antenna design, aperture efficiency is often disregarded. Consequently, the present study shows that maximizing the aperture efficiency reduces the required number of radiating elements, which leads to cheaper antennas with more directivity. For this, it is considered that the boundary of the antenna aperture has to be inversely proportional to the half-power beamwidth of the desired footprint for each ϕ-cut. As an example of application, it has been considered the rectangular footprint, for which a mathematical expression was deduced to calculate the aperture efficiency in terms of the beamwidth, synthesizing a rectangular footprint of a 2:1 aspect ratio by starting from a pure real flat-topped beam pattern. In addition, a more realistic pattern was studied, the asymmetric coverage defined by the European Telecommunications Satellite Organization, including the numerical computation of the contour of the resulting antenna and its aperture efficiency.

We present a cylindrical dual-polarization phased array antenna for weather surveillance radars that features high isolation, matched copolar beams, low sidelobe levels, and adaptive null steering. We present a crossed dipole antenna element to replace the patch antenna on the currently deployed cylindrical polarimetric phased array radar (CPPAR). The crossed dipole element offers suppressed surface wave and lower coupling between adjacent elements of an array. As a result, we achieved lower backlobe and sidelobe levels, and a higher match between copolar beams of CPPAR compared to the currently deployed multi-layer patch antenna. Further reduction of the sidelobe level and adaptive null steering are obtained using a modified particle swarm optimization. The proposed null steering mitigates the interference among the four concurrent beams of a cylindrical phased array radar. The improvement in CPPAR radiation characteristics has been verified by comparing the presented crossed dipole antenna’s radiation patterns and the existing aperture coupled patch antenna. The proposed crossed dipole phased array can benefit national weather radar networks to provide accurate multiparameter measurements enabling reliable observation of severe weather phenomena.

Various methods have been proposed to control the electromagnetic fields in the near-or far-field region, one of which is to use antenna arrays. This paper reviews a technique, called the method of maximum power transmission efficiency (MMPTE), for the design of antenna arrays and wireless power transmission (WPT) systems. The method is motivated by the fact that all wireless systems aim to maximize the power transmission efficiency (PTE) between the transmitter and receiver and the PTE can thus be considered as a performance index for the design of WPT system and antenna as well. The MMPTE makes use of the PTE as the performance index to be optimized, and reduces a field synthesis problem into a circuit analysis problem, and is therefore easy to master and implement. It overcomes all the challenges associated with conventional array design methods, and is applicable to the design of any type of antenna array in any environment. This paper summarizes the basic theory of MMPTE and demonstrates MMPTE through a number of near- and far-field applications, including focused antennas, smart antennas, shaped beam antennas, end-fire antennas, multi-beam antennas, polarization-reconfigurable antennas, and wireless power transmission systems.

A low-profile transmissive metasurface is proposed to synthesize contour beam pattern for a European region. A slot array feed is used to illuminate same size metasurface aperture with a plane wave at a near field distance of 24 mm. A two step optimization process is proposed to solve asymmetric and complicated pattern synthesis problem for transformation of plane wave to contour beam pattern using modified Alternating Projection Method (APM). A new subwavelength 4-arm spiral element is proposed to achieve desired performance for contour beam pattern synthesis in $Ku$ band centered at 12.5 GHz. A prototype of low profile transmissive metasurface is also fabricated and measured to verify its gain and bandwidth performance for contour beam pattern synthesis for the European region.

Pattern synthesis is a significant research focus in smart antennas due to its extensive use in several radar and communication systems. To improve the optimization performance of pattern synthesis of uniform and sparse linear antenna array, this paper presents an optimization method for solving the antenna array synthesis problem using the Mayfly Algorithm (MA). MA is a new heuristic algorithm inspired by the flight behavior as well as the mating process of mayflies, it has a unique velocity update system with great convergence. In this work, the MA was applied to linear antenna arrays (LAA) for optimal pattern synthesis in the following ways: by optimizing the antenna current amplitudes while maintaining uniform spacing and by optimizing the antenna positions while assuming a uniform excitation. Constraints of inter-element spacing and aperture length are imposed in the synthesis of sparse LAA. Sidelobe level (SLL) suppression with the placement of nulls in the specified directions is also implemented. The results gotten from this novel algorithm are validated by benchmarking with results obtained using other intelligent algorithms. In the synthesis of uniform 20-element LAA with nulls, MA achieved an SLL of −31.27 dB and the deepest null of −101.60 dB. Also, for sparse 20-element LAA, an SLL of −18.85 dB was attained alongside the deepest null of −87.37 dB. MA obtained an SLL of −35.73 dB and −23.68 dB for the synthesis of uniform and sparse 32-element LAA respectively. Finally, electromagnetism simulations are conducted using ANSYS Electromagnetics (HFSS) software, to evaluate the performance of MA for the beam pattern optimizations, taking into consideration the mutual coupling effects. The results prove that optimization of LAA using MA provides considerable enhancements in peak SLL suppression, null control, and convergence rate with respect to the uniform array and the synthesis obtained from other existing optimization techniques.

This article presents an electromagnetic inversion algorithm for the design of cascaded metasurfaces that enables the design process to begin from more practical output field specifications, such as a desired power pattern or far-field (FF) performance criteria. Thus, this method combines the greater field transformation support of multiple metasurfaces with the flexibility of the electromagnetic inverse source framework. To this end, two optimization problems are formed: one associated with the interior space between two metasurfaces and the other for the exterior space. The cost functionals corresponding to each of these two optimization problems are minimized using the nonlinear conjugate gradient (CG) algorithm with analytic expressions for the gradient operators. The numerical implementation of the developed design procedure is presented in detail, including a total variation (TV) regularizer that is incorporated into the optimization procedure to favor smooth field variations from one unit cell to the next. The capabilities of the method are demonstrated by converting the produced surface susceptibilities into three-layer admittance sheet models, which are simulated in several 2-D examples. [ABSTRACT FROM AUTHOR]

A gradient-based optimization algorithm that is capable of directly designing a metasurface at the circuit parameter level for a desired field (amplitude and phase) pattern or a desired power (phaseless) pattern on some region of interest (ROI) external to the metasurface boundary is presented. Specifically, the inversion algorithm designs the microwave admittance profile of each subwavelength element of the metasurface when a three-layer admittance model is assumed. To this end, a forward model that maps the admittance profile of each layer of the metasurface to the desired field on the ROI is developed. Then, for the inverse design problem, a data misfit cost functional is defined and minimized over the unknown admittance profile using analytically derived gradients and step lengths. The developed inversion algorithm is then utilized to design metasurfaces capable of beam forming in the far-field zone. [ABSTRACT FROM AUTHOR]

A two-dimensional (2-D) discrete dielectric lens antenna is designed to radiate fan-shaped multi-beam patterns for gain stability in beam switching. The target is to minimize adjacent-beam overlapping transition regions and provide sufficient and similar gains for all field angles when the antenna is employed in a mobile device. This design starts with a conventional 2-D Luneburg lens antenna, and distorts its dielectric permittivity and the sizes of discrete dielectric rings to defocus the pencil beam patterns into shaped ones with a relatively flat pattern for uniform field distribution. The design is realistically implemented at 38 GHz with both simulation and measurement results shown to validate the concept. Successful validation of feasibility in beam synthesis is achieved. Fabrication discrepancy to result in slight radiation degradation is also discussed.

In this paper, a novel approach for synthesizing multiple radiation patterns with reduced hardware complexity in the feed network by exploiting the additional degree of freedom 'time' in time modulated unequally spaced linear array (TMUSLA) is presented. In the proposed approach, with a suitable common set of element position of TMUSLA, the desired dual-beam pattern with low sidelobe level (SLL) is obtained by simply controlling the ON-OFF time sequence of the RF switches connected to the array elements. To show the effectiveness of the proposed array synthesis method, two dual beam patterns - first one as pencil (sum) beam (PB) and flat-topped beam (FTB) pattern, and the second one as sum and difference pattern with different constraints have been synthesized. For the successful generation of the desired power patterns, differential evolution (DE) algorithm is employed to obtain the optimum possible solution in terms of common element position, time-modulation, switching sequences and applicable excitation phase for the desired shape beam patterns. The superiority of the proposed approach with the favourable improved performance has been demonstrated by comparing the realized patterns with the state-of-the-art relevant reported works. [ABSTRACT FROM AUTHOR]

We present a new deep learning framework for removing honeycomb artifacts yielded by optical path blocking of cladding layers in fiber bundle imaging. The proposed framework, HAR-CNN, provides an end-to-end mapping from a raw fiber bundle image to an artifact-free image via a convolution neural network (CNN). The synthesis of honeycomb patterns on ordinary images allows conveniently learning and validating the network without the enormous ground truth collection by extra hardware setups. As a result, HAR-CNN shows significant performance improvement in honeycomb pattern removal and also detailed preservation for the 1961 USAF chart sample, compared with other conventional methods. Finally, HAR-CNN is GPU-accelerated for real-time processing and enhanced image mosaicking performance.

Abstract Pattern synthesis of non-uniform elliptical antenna arrays is presented in this paper. Only the element positions of the antenna arrays are optimized by the combination of differential evolution (DE) and invasive weed optimization (IWO) to reduce the peak side lobe level (PSLL) of the radiation pattern. In order to avoid the overlap of the array elements, the minimum spacing of the adjacent elements is constrained. Also, the beam width of the radiation pattern can be constrained effectively. Three elliptical antenna arrays that have 8, 12, and 20 elements are investigated. The synthesis results show that the introduced method can present a good side lobe reduction for the radiation pattern. Compared with other optimization methods, the method proposed in this paper can obtain better performance.

In this paper, a multi-shell spherical dielectric lens antenna is synthesized to radiate multi-beams with optimum shaped patterns for radio coverage at millimeter wave (mmW) frequencies. In particular, the design considers the composing characteristics of discrete multi-shell Luneburg lens antenna as an initial structure, and synthesizes its permittivity and sizes of dielectric shells to produce relatively shaped main beam patterns rather than conventional pencil-shapes. It targets to minimize inter-beam overlapping transition regions with slowly varying power density in the coverage boundary, and therefore reduce the ping-pong effect of inter-sector handovers to potentially minimize the inter-cell interferences arising from the over-large gain of pencil beam when the user equipment (UE) is at near the sector boundary far-off the beam peak. After the synthesis, the antenna is implemented at 38 GHz with both numerical simulation and measurement results shown to validate the concept. Successfully validation on the feasibility of beam synthesis in comparison to that of Luneburg lens antennas has been achieved. Discrepancy in fabrication to potentially result in slight radiation degradation is also discussed.

Deceptive jamming may not only induce a large amount of false alarms and deteriorate the target detection performance, but also lead to degraded space-time adaptive processing (STAP) performance in an airborne radar. To tackle these issues, this paper proposes a cognitive transmitting scheme to counter the deceptive jamming for airborne array radar. The proposed approach is composed of two steps. The first step is the deceptive jamming perception. A specially designed high pulse repetition frequency (PRF) waveform is transmitted, and then the deceptive jamming is identified according to the angle clustering feature of the false targets. In the second step, the phase-only transmit pattern with notches at the jammers' directions is designed. The encountered pattern synthesis problem is nonconvex due to the fixed excitations constraint. To solve this problem, a nested alternating direction method of multipliers (N-ADMM) is proposed. With the developed approach, the radiated power at the jammers' directions is attenuated significantly. Therefore, the probing signal possesses the characteristic of low probability of intercept (LPI). Numerical examples are given to demonstrate the effectiveness of the proposed approach.

The generation process of difference beam is analyzed from the perspective of beam superposition. By analyzing the continuous linear source, a differential beam synthesis method, which can control the sidelobes level, is proposed with a simple form. The sidelobes level of the difference pattern is determined by controlling the direction of the subbeam and applying the traditional synthesis method, such as Chebyshev method and Taylor method. The proposed synthesis method is theoretical and explicit. Examples are presented for assessing the capabilities of the synthesis of difference patterns. The general distribution function is given. [ABSTRACT FROM AUTHOR]

Diversity of test patterns is important for many lithography applications. It is however difficult to achieve with sample layouts or by using a popular pattern generator. We propose a synthesis method of lithography test patterns. Each pattern is represented by a map of IPS (image parameter space) values, called IPS map. A key in the proposed method is to guarantee that the center of the synthesized pattern corresponds to the IPS values given as input. The synthesis consists of three steps: a new IPS map is generated using an adversarial auto-encoder (AAE) with given IPS values; the IPS map is converted to its corresponding layout through an auto-encoder (AE); the layout goes through the final processing to remove any unrealistic shapes. Both AAE and AE are trained beforehand by using a few sample layouts. The synthesis method is applied to lithography modeling. The RMSE of lithography model is reduced by 30% when the model is calibrated with synthesized patterns, compared to the model based on test patterns from a pattern generator. A machine learning-based lithography simulation is taken as a second application. When the synthesized patterns are used to train the machine learning model, the accuracy of lithography simulation improves by 7%. [ABSTRACT FROM AUTHOR]

This article presents an optimization method for pattern synthesis of sparse planar arrays considering mutual coupling and nonoverlapping constraint. The design optimization is carried out through simultaneously optimizing the rotation and position parameters of each array element within a given array aperture. To prevent the overlaps among multiple coupled array elements, a single level-set-based constraint is constructed, which can deal with the difficulty of large numbers of nonoverlapping constraints. In order to guarantee the design precision, the full-wave method of moments (MoM) simulation is well integrated in the optimization method for rigorously considering the mutual coupling among the coupled array elements. The design sensitivity of the optimization problem is analytically derived and the pattern synthesis is actualized by using gradient-based algorithm. Several examples are provided to demonstrate the validity and effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

In this article, a systematic and generally applicable method to synthesize patterns for single antennas is proposed based on characteristic mode analysis (CMA). Both the theoretical analysis and real implementations are taken into consideration. To obtain a desired pattern, we first calculate the weighting coefficient of each mode using the correlation between the characteristic field and the desired pattern. Afterward, the synthesized current and the feeding vector are solved using CMA, providing feeding information, such as feeding numbers, locations, amplitude, and phase. The feeding vector is nonsparse, making practical feeding impossible. In this circumstance, the theory of compressed sensing is applied so that the number of ports can be greatly reduced, and the synthesized pattern is still highly correlated with the desired one. The method is applied to 2-D and 3-D structures, where a mobile handset and a scaled model of the shipboard are utilized as representatives. The prototype of the handset antenna was fabricated and measured, with the desired pattern achieved, having null in the boresight direction and being almost omni-directional on the plane of the chassis. The measured results agree well with the simulated ones. With the synthesized pattern, the handset antenna is robust to the user effects. The method can be generally applied to pattern synthesis for planar and 3-D antennas. [ABSTRACT FROM AUTHOR]

A planar angled-dipole antenna is investigated in this communication. The angled dipole has an intersection angle of 60°, radiating quasi-isotropic pattern with a gain difference of about 6.4 dB over the entire spherical radiating surface. To improve the isotropy of the antenna, two near-field parasitic elements (NFPEs) are further introduced. The NFPEs function as supplementary radiators and they help to enhance the radiation in the weak region, decreasing the gain difference significantly to 1.57 dB. For demonstration, a prototype operating at 2.4 GHz is fabricated and measured. The prototype shows a high efficiency of 90%, and the roundness is less than 2.59 dB across the entire impedance passband (2376–2526 MHz). [ABSTRACT FROM AUTHOR]

Reconfigurable array radiates multiple patterns with only a single array via designing multiple excitation vectors with common magnitudes for the same element-index excitation elements, so as to guarantee phase-only control. To tackle this problem, this article proposes a new reconfigurable array beampattern synthesis method. First, we borrow the concept of sensor network consensus computation and model the synthesis problem as a sensor network computation problem via imitating a virtual (conceptual) multinode sensor network, where each “node” corresponds to an individual beampattern synthesis task. More specifically, these “nodes” with the same number as those of radiated patterns share a set of common excitation magnitudes, which results in a special magnitude-consensus computation problem in the imitated sensor network. Then, via locally computing the excitation in each “node” and exchanging current computation results with neighboring “nodes,” all “nodes” obtain the magnitude-consensus excitations after the “network” is stable. Numerical examples are provided to demonstrate the validity and faster convergence speed of the proposed method. [ABSTRACT FROM AUTHOR]

Pattern synthesis from array antennas has become a commonly problem to address. Several standard and conventional techniques are available in the literature for the above purpose. Depending on the desired shape of the pattern, the methods are chosen for example, Taylor considered a continuous line sources and generated narrow beams with the desired sidelobe levels of equal height close to the main beam. Elliot has reported a method to generate unsymmetrical patterns. There are some applications where the restricted sidelobes in the mid of the sidelobe region are required. To generate such patterns, no work is available in the literature. In view, of this intensive investigations are carried out to generate such patterns. Accelerated Particle Swarm Optimization is applied to optimize the above patterns. The simulated patterns are presented for both small and large arrays. [ABSTRACT FROM AUTHOR]

The aim of this paper is to demonstrate the application of Unequally Spaced Arrays (USAs) in decreasing side lobe level (SLL) in linear arrays. As well known, solving of a nonlinear equation is needed in USA antenna pattern synthesis. In this paper, an improved algorithm for USA antenna pattern synthesis is presented. This method is based on converting the array factor into a triangular system of equations capable to be solved using a recursive algorithm. This method has more accuracy and speed than reported similar analytical methods based on simulation results, which leads to lower SLL and simulation time. In addition, an improvement of 3dB beamwidth in comparison with uniform spaced array can be observed.

A hybrid approach to the synthesis of sparse arrays radiating shaped or focused beampattern is presented in this paper. Specifically, an iterative scheme is used where the prescribed pattern response in the mainlobe peak direction is cast as a multi-convex problem at each step that the non-convex lower bound constraint is relaxed while including a reweighted l(1)-norm minimisation based on the magnitudes of the elements. Numerical tests, referred to benchmark problems, show that the proposed method achieves improved radiation performance by using fewer number of radiating elements.

This paper presents a low-cost architecture that allows for beamforming with antenna arrays installed onto unmanned aerial vehicles (UAVs). Beam switching is proposed to improve the antenna gain towards the ground station with two three-element arrays installed below the wings of the UAV. The electromagnetic modeling of the complete structure (UAV and integrated antennas) was performed with commercial electromagnetic simulator Ansys HFSS. The radiation patterns were synthesized with particle swarm optimization (PSO). By employing lumped surface-mount device (SMD) components and switches, the design of the feeder to deliver proper excitation coefficients to the antennas is presented, and its performance was assessed by simulations. The proposed approach is demonstrated to be very effective with low-cost production.

A hybrid approach to the synthesis of sparse arrays radiating shaped or focused beampattern is presented in this paper. Specifically, an iterative scheme is used where the prescribed pattern response in the mainlobe peak direction is cast as a multi-convex problem at each step that the non-convex lower bound constraint is relaxed while including a reweighted l1-norm minimisation based on the magnitudes of the elements. Numerical tests, referred to benchmark problems, show that the proposed method achieves improved radiation performance by using fewer number of radiating elements. [ABSTRACT FROM AUTHOR]