Field Transformation Algorithm Research Articles

Antenna pattern reconstruction for mid-band massive antenna array based on a single-cut field transformation algorithm in a compact multi-probe anechoic chamber setup

ABSTRACT It has become a common challenge on how to measure radiation patterns of massive antenna arrays working at high frequency with high efficiency and accuracy, which has attracted huge interest from both academia and industry. In this paper, a highly accurate and efficient far field (FF) pattern reconstruction strategy through conducting single cut near field (NF) to FF transformation algorithm based on spherical wave expansion (SWE) is proposed for fast measurements of large base stations (BSs) operating at mid-band. Our objective is to design a compact multi-probe setup to measure key radiation parameters of the massive array, with low-cost and high-efficiency. A BS of 16 × 16 elements operating at mid-band is adopted as the device under test (DUT) in this paper. Analysis is conducted on the impact of measurement distance, sampling range and sampling density on the reconstruction accuracy of the algorithm in the compact multi-probe anechoic chamber setup, demonstrating that the required key information of the main lobe of the DUT can be accurately reconstructed when the measurement range R = 1/20 FF distance, sampling resolution ∆θ = 3°, and sampling range θ ∈ [75°, 105°] are selected, respectively. The impact of phase center offset on the accuracy of FF pattern reconstruction is analyzed when only one sub-array is enabled, demonstrating the effectiveness of the algorithm for sub-array measurements.

Failure analysis of photovoltaic strings by constructing a digital multi-twin integrating theory, features, and vision

Timely and accurate failure analysis of photovoltaic (PV) systems is crucial forensuring the stable operation of power grids. However, existing failure analysis and diagnosis algorithms based on deep neural networks excessively rely on high-quality failure state data collected by sensors. This is extremely difficult to achieve in real photovoltaic power plants that are commonly equipped with self-protection mechanisms. To address this issue, we propose a Digital Multi-Twin integrating Theory, Features, and Vision (TFV-DMT) for failure analysis of PV strings in PV systems. This method first constructs theoretical simulation twins, feature twins, and visual twins based on the concept of digital twins, specifically tailored for actual PV systems, and designs a multi-twin collaborative model for model updating and failure diagnosis. Secondly, to better construct the visual twin, we introduce a Two-Dimensional Gram Angle Field Transformation Algorithm (TDGAF) to achieve targeted two-dimensional mapping of PV feature data, facilitating a more direct expression of failure characteristics. Furthermore, by constructing a Swish-activated Deep Convolutional Generative Adversarial Network (SDCGAN) to achieve balanced augmentation of mapping data, the model bias of theoretical simulation twins can be reduced. Finally, we propose a Swin-LT network that incorporates a Lightweight Dual-Channel Attention Module (LDAM) to better analyze the features of the visual twin, enabling more precise fault diagnosis. The algorithm has been validated on a real 250 kW grid-connected PV system, with results indicating that the proposed digital twin model is effective, achieving a diagnosis accuracy rate of 98.8 % for string failures.

Teaching the process of free throw action in basketball course based on motion vector field transformation

Abstract In order to improve the teaching quality of the free throw action process in basketball courses, this paper proposes research on the teaching of free throw action by integrating motion vector field transformation. Starting from the actual situation of the player’s free throw action, it describes the problems in the teaching process of free throw action. It elaborates on the structure and principle of the motion vector field transformation algorithm in depth. In video analysis teaching of free-throw shooting action processes, the player’s motion vectors can easily be interfered with by random noise, which needs to be optimized using smoothing processing and compensation models. Combined with the teaching objectives of free throw action, the design and development of the “basketball free throw action” microteaching by integrating the motion vector field transformation through the analysis of a university sports college basketball class of 2021 students found that from the seventh week and the eighth week of the experimental group and the control group, respectively, there is a difference of 7.8% and 13%. The ball-hitting rate is significantly different from that of the control group (<0.5). A significant difference occurred (<0.05). Although both methods have improved the free throw shooting rate of the athletes, the teaching of free throw shooting action in the basketball course integrating the motion vector field transformation performs better compared to the traditional free throw shooting action teaching mode. This study provides technical support and diversified media presentation methods for the design and development of basketball micro-courses. It constructs a feasible way to develop and innovate college basketball teaching.

전기적 대형 물체 RCS 해석을 위한 근거리-원거리장 변환 알고리즘 연구

Preliminary analyses of radar cross section (RCS) in the design process of military weapon systems are very important. Recently, weapon systems such as missiles and fighter jets are adapted for large-size electrical objects in preparation for the wavelengths used in radar. Therefore, it is difficult to pre-analyze the RCS through commercial simulation programs unless a high-performance computing power is provided. To solve these problems, we propose a near to far field transformation algorithm that can be applied to domain decomposition analyses. First, we analyzed the theoretical equation and the physical meaning of the algorithm and matricized the integral equation to a constant part and a scattering part. Then, the Moore-Penrose pseudo-inverse matrix method was used to solve the scattering characteristics. We have also studied the possibility of extracting the far field RCS from near field data.

Setup and Characterization of a Volumetric <inline-formula> <tex-math notation="LaTeX">$\boldsymbol{W}$ </tex-math> </inline-formula>-Band Near-Field Antenna Measurement System

A volumetric $W$ -band near-field (NF) antenna measurement system is presented and evaluated. The system supports measurements at arbitrary locations within the measurement volume with high positioning accuracy together with corresponding field transformations. The measurement performance of the system is carefully investigated with respect to accuracy and efficiency, e.g., by a comprehensive evaluation of room scattering and by laser scanner measurements. The fast irregular antenna field transformation algorithm (FIAFTA) is utilized to perform the necessary NF to far-field transformations. Due to the flexibility of FIAFTA, so-called nonredundant planar measurements become possible, which overcome the classical half-wavelength sampling requirement entailed by the fast Fourier transform-based transformation approaches. Thus, with a time-factor of about 35, accelerated planar measurement results are achieved by projecting angularly uniform sample grids on the minimum sphere around the antenna under test (AUT) onto the measurement plane, resulting in irregularly thinned planar measurement grids. The error levels between two completely independent measurements employing full and thinned grids are found at a level below −40 dB. Moreover, such measurements allow decreasing mutual interactions between the AUT and the probe by increasing the measurement distance, but without the need to collect more measurement samples.

Phaseless Near-Field Far-Field Transformation Utilizing Combinations of Probe Signals

Phaseless near-field far-field transformations based on nonconvex optimization suffer from local stationary points. In order to avoid the corresponding suboptimal solutions, the incorporation of combinations of probe signals into the cost functional is proposed and investigated. The nonconvex optimization based on the Wirtinger Calculus relies on forward and adjoint radiation operator evaluations via the fast irregular antenna field transformation algorithm (FIAFTA) and is performed by a memory-limited Quasi-Newton method. This allows the solution of large scale problems with utilization of the full flexibility of the FIAFTA in terms of measurement probe correction and arbitrary sample locations. Results for synthetic and measured near-field data reveal significant improvements when the knowledge of probe signal combinations is utilized, especially in applications with a large number of unknowns.

Comparison of non-convex cost functionals for the consideration of phase differences in phaseless near-field far-field transformations of measured antenna fields

Abstract. This work introduces two methods which extend the non-convex minimization problem arising in phaseless (NF) far-field (FF) transformations. With the new extensions, knowledge about phase differences between measurement points can be incorporated into the minimization problem. The additional information helps to avoid stationary points of the minimization cost functional which would otherwise compromise the result of the near-field far-field transformation. The methods are incorporated into the Fast Irregular Antenna Field Transformation Algorithm (FIAFTA), analyzed and compared. Their effectiveness is shown by transforming synthetic near-field data sets with partial knowledge of phase differences to the far-field.

A Propagating Plane-Wave-Based Near-Field Transmission Equation for Antenna Gain Determination from Irregular Measurement Samples

In order to accurately determine the far-field gain of an antenna under test from near-field measurements, a general transmission equation between the ports of a transmitting and a receiving antenna is derived. The formulation is based on a propagating plane-wave expansion of the electric field and allows one to use a derivation based on far-field concepts separately for all entries of the plane-wave spectrum. It is shown that the equation is a generalization of the Friis transmission equation to the near-field case and the equation is compared with spherical multipole-based transmission equations for single and multiple antenna systems. The new transmission equation is integrated into the Fast Irregular Antenna Field Transformation Algorithm, which now allows one to determine the antenna gain pattern not only from canonical measurement surfaces as planes and spheres but also from highly irregular sample distributions. Examples using near-field data from both simulations and measurements are given to prove the validity of the formulation and to illustrate the capabilities of the implementation. In particular, it is also shown that accurate gain determination is possible from incomplete near-field measurements and that appropriate probe correction is important.

Ear Recognition by Feature Extraction Using Force Field Transformation

Biometrics is the study of automatic techniques for recognizing human beings based on physical or behavioral traits. Among several biometric features, ear is quite stable because it does not vary with age and emotion. It is an important means to guarantee the quality of teaching by the standard and the optimization of the teaching process. Large amounts of data which generated in the process of teaching such as attendance, class performance, homework and testing results and so on are used to process manually. At the same time, there is quite randomness. And it is difficult to accurately reflect the teachers' working condition. This study explores the use of an Ear Visual Biometric as a measure of identification unit for the Teaching Management System in Universities and Colleges. It is significantly reduces the workload of teachers' teaching process and improved the credibility and controllability of data by the data acquisition equipment and the whole system. Ear detection and recognition is achieved through the use of Feature Extraction approaches like Force Field Transformation and Chord Point Detection Algorithm is used for better performance than the method to other algorithm.

Fast Inverse Equivalent Source Solutions With Directive Sources

A fast inverse equivalent source technique is presented for the fully probe-corrected transformation of measured radiation or scattering fields utilizing directive sources. The directivity of the expansion sources is either obtained by combining electric and magnetic surface current densities in a directive Huygens radiator or by shifting the source locations into complex space. The latter approach is known to generate Gaussian-beam-like directive radiators. These two techniques can be used separately or in combination to obtain three different solutions that approximately satisfy the null-field condition (also known as the Love condition) outside the solution domain, i.e., inside the volume of the original device under test. The directive sources lead to a better conditioning of the inverse problem and especially the Huygens radiator concept leads to good conditioning for a small number of unknowns. Thus, considerable reduction in computation times and better solution accuracies are achieved. Moreover, antenna diagnostics is promoted by the improved localization of the directive equivalent sources. The directive sources are implemented together with Rao–Wilton–Glisson basis functions and the new concepts are utilized within the fast irregular antenna field transformation algorithm with its hierarchical propagating plane wave-based radiation operator representation. This algorithm has recently been augmented with Gaussian beam-based translation operators which lead to considerably reduced computation times and lower memory requirements. The algorithmic capabilities are demonstrated with synthetically generated near-field data as well as with real spherical measurements of a double-ridged waveguide antenna.

ELECTROMAGNETIC FIELD TRANSFORMATIONS FOR MEASUREMENTS AND SIMULATIONS (Invited Paper)

Electromagnetic field transformations are important for electromagnetic simulations and for measurements. Especially for field measurements, the influence of the measurement probe must be considered, and this can be achieved by working with weighted field transformations. This paper is a review paper on weighted field transformations, where new information on algorithmic properties and new results are also included. Starting from the spatial domain weighted radiation integral involving free space Green's functions, properties such as uniqueness and the meaning of the weighting function are discussed. Several spectral domain formulations of the weighted field transformation integrals are reviewed. The focus of the paper is on hierarchical multilevel representations of irregular field transformations with propagating plane waves on the Ewald sphere. The resulting Fast Irregular Antenna Field Transformation Algorithm (FIAFTA) is a versatile and efficient transformation technique for arbitrary antenna and scattering fields. The fields can be sampled at arbitrary irregular locations and with arbitrary measurement probes without compromising the accuracy and the efficiency of the algorithm. FIAFTA supports different equivalent sources representations of the radiation or scattering object: 1) equivalent surface current densities discretized on triangular meshes, 2) plane wave representations, 3) spherical harmonics representations. The current densities provide for excellent spatial localization and deliver most diagnostics information about the test object. A priori information about the test object can easily be incorporated, too. Using plane wave and spherical harmonics representations, the spatial localization is not as good as with spatial current densities, but still much better than in the case of conventional modal expansions. Both far-field based expansions lead to faster transformations than the equivalent currents and in particular the orthogonal spherical harmonics expansion is a very attractive and robust choice. All three expansions are well-suited for efficient echo suppression by spatial filtering. Various new field transformation and new computational performance results are shown in order to illustrate some capabilities of the algorithm.

Fast near-field far-field transformation for phaseless and irregular antenna measurement data

Abstract. The characterization of antenna radiation patterns by transformed near-field measurements requires accurate amplitude and phase data. This represents a problem since expensive measurement equipment is required, especially at millimeter and submillimeter wavelengths (Isernia et al., 1996). Amplitude-only antenna field measurements are theoretically sufficient for the unique determination of antenna far-fields. Therefore, phaseless techniques are of special interest. However, the required field transformations are extremely challenging, since they are nonlinear and strongly ill-posed. In this work, the amplitude-only or phaseless near-field far-field transformation problem is formulated as a nonlinear optimization problem. The linear radiation operator within the nonlinear formulation is evaluated using the fast irregular antenna field transformation algorithm (FIAFTA). A hybrid solution procedure is described which combines a genetic algorithm with an iterative conjugate gradient (CG) search method. Numerical results prove the efficiency and flexibility of the formulation and it is shown that the algorithm remains stable when the noise level in the measurements is moderate. Nevertheless, regularization techniques might be beneficial to further improve the robustness of the algorithm.

Adaptive Sampling in Spherical and Cylindrical Near-Field Antenna Measurements

An adaptive approach for optimized sampling in cylindrical and spherical near-field antenna measurements is described. The presented technique applies higher sampling density in rapidly varying near-field regions, and skips data points in the smoother regions. Abrupt changes in the near field are detected by comparing the extrapolated and the measured near-field values at coarser sampling points during the measurements. A decision function, based on the signal-to-noise ratio of the measured value, is used to determine the threshold difference between the extrapolated and the measured near-field values for skipping the sampling point. The reduced near-field data collected is processed using the fast irregular antenna field transformation algorithm (FIAFTA). FIAFTA is computationally efficient, and capable of handling data on irregular grids with full probe correction. Several test cases are then presented related to the applicability of the given approach. A significant reduction in the number of measurement points was observed, thereby reducing measurement time and the computational effort.

NEAR-FIELD ERROR ANALYSIS FOR ARBITRARY SCANNING GRIDS USING FAST IRREGULAR ANTENNA FIELD TRANSFORMATION ALGORITHM

An extensive error analysis for arbitrary near-fleld antenna measurements is performed. Expressions are derived to estimate the far-fleld uncertainty using the available near-fleld data together with the measurement inaccuracy but, most importantly, without the knowledge of the reference far fleld. Error analysis techniques presented so far either assume a speciflc set of antennas or a speciflc measurement surface and are di-cult to generalize. We present a generalized approach providing realistic error estimates using the recently developed Fast Irregular Antenna Field Transformation Algorithm (FIAFTA). FIAFTA utilizes equivalent plane wave sources to represent radiated antenna flelds and is able to process near- fleld data collected on arbitrary measurement grids. The unknown plane wave coe-cients are determined by solving a linear system of equations. The error model is applied to planar, cylindrical, and spherical near-fleld measurements and is also valid for arbitrary measurement grids. The estimated far-fleld uncertainties show good agreement with the reference far-fleld errors.