Radiation Pattern of a Microstrip Antenna on a Trapezoidal Substrate

This paper deals with a rectangular microstrip antenna on a trapezoidal substrate. It finds radiation pattern of the antenna using the concept of fractional cross product. Results show that as the fraction goes from 1 to 0.1, the direction of null in the H-plane moves from end fire towards broad side. Also, a back-lobe starts to appear in the H-plane.

A Study of QCD Radiation in VBF Higgs Production with Vincia and Pythia

We discuss and illustrate the properties of several parton-shower algorithms available in Pythia and Vincia, in the context of Higgs production via vector boson fusion (VBF). In particular, the distinctive colour topology of VBF processes allows to define observables sensitive to the coherent radiation pattern of additional jets. We study a set of such observables, using the Vincia sector-antenna shower as our main reference, and contrast it to Pythia's transverse-momentum-ordered DGLAP shower as well as Pythia's dipole-improved shower. We then investigate the robustness of these predictions as successive levels of higher-order perturbative matrix elements are incorporated, including next-to-leading-order matched and tree-level merged calculations, using Powheg Box and Sherpa respectively to generate the hard events.

Radiation Pattern Synthesis of the Coupled Almost Periodic Antenna Arrays Using Artificial Neural Network ANN Model

This paper proposes a radiation pattern synthesis of the almost periodic antenna arrays including mutual coupling effects (that extracted by the Floquet analysis according to our previous work), which principally has a high directivity and large bandwidth. For modeling the given structures, the moment method combined with the Generalized Equivalent Circuit (MoM-GEC) is proposed. The artificial neural network (ANN) as a powerful computational model has been successfully applied to the antenna array pattern synthesis. The results showed that the multilayer feedforward neural networks are rugged and can successfully and efficiently resolve various distinctive complex almost periodic antenna patterns (with different source amplitudes) (in particular, both periodic and randomly aperiodic structures are taken into account). However, the artificial neural network (ANN) is capable of quickly producing the synthesis results using generalization with the early stopping (ES) method. A significant time gain and memory consumption are achieved by using this given method to improve the generalization (called early stopping). To justify this work, several examples are developed and discussed.

Акустооптическая многолучевая аксиальная дифракция в парателлурите

To form a multi-beam radiation pattern, it is proposed to use the axial geometry of acousto-optic interaction in paratellurite. In single frequency mode, the use of this geometry for angular scanning is characterized by a dip in the frequency response. Optimization of a multifrequency radio signal makes it possible to effectively divide laser radiation into several beams, while maintaining the fundamental advantages of axial geometry: minimum crystal size and power consumption

Franklin Collinear Antenna 2 Levels Different Sides using Array Method 4 Stacking Units 360ᵒ with Integrated Reflector and Power Combiner for ADS-B S-Receiver Mode

In this study, an antenna system that could cover the 360ᵒ detection area using the microstrip method was created. The antenna design proposed uses the franklin collinear method with the addition of an array of arms to the left and right of the antenna and the addition of reflectors as a gain enhancer. The four antenna array units are combined using a power divider (combiner) as a unifying antenna. Antenna design with end fire radiation pattern cannot be used in receiving the ADS-B antenna system, because it works only in certain sectors with certain beamwidth, so it needs to be modified by adding an array of 4 units that make up 360◦ radiation of directional diagrams. The addition of the reflector is done by testing the optimum width. The most optimum width is obtained by the width of the side addition on the side of the antenna aperture cross section width of 80 mm. Based on the results of experiments that have been carried out for the design of receiver antennas for ADS-B applications that are required in the form of a radiation pattern in all directions using the reflector technique, the most appropriate gain increase is to use a phase difference for the antennas that are closest both left and right by 90o in ¼ λ conditions in the integration process using a 4 way power combiner. Response return loss at frequency 1.0752 GHz and 1.109 GHz is -15 dB, it means antenna has 33.8 MHz bandwidth with maximum response return loss at -23.22 dB and gain of 7.586 dBi, this antenna design is very suitable for use in the ADS-B application. Design and simulation at this antenna used CST software.

Miniaturized Dual-Band Dual-Mode Microstrip Patch Antenna with Defected Ground Structure for Wearable Applications

This work presents the performance of a miniaturized dual-band dual-mode microstrip patch antenna with Defected Ground Structure (DGS) at 2.45 GHz and 5.8 GHz on the stacked substrate configuration in the order of FR-4 – PDMS- FR-4. The antenna offers a promising solution for wearable applications in the ISM bands. The first substrate is a flexible Flame Retardant 4 (FR-4) and the other substrate is a highly flexible Polydimethyl Siloxane (PDMS). The size of the antenna was reduced from 50 × 50 mm2 to 30 × 30 mm2, by introducing DGS on the ground plane. A single U-slot on the rectangular radiating patch was introduced to produce the upper resonant frequency of 5.8 GHz while the existing square patch is to generate the lower resonant frequency of 2.45 GHz. The simulations on the dual-band dual-mode microstrip patch antenna shows the reflection coefficient, S11 at 2.45 GHz is -17.848 dB with a bandwidth of 278.8 MHz and -13.779 dB with a bandwidth of 273 MHz at 5.8 GHz. A unidirectional radiation pattern observed in the E-plane shows that the antenna could be applied for off-body communication while an omnidirectional radiation pattern in the H-plane showed that the antenna can be used for on-body communication. Bending investigation were performed for the antenna over a vacuum cylinder with varying diameters of 50 mm, 60 mm, 70 mm, 80 mm, 90 mm, 100 mm and 120 mm in the CST MWS® software. From the graph of reflection coefficients, the performance of the antenna were not affected in bending condition. The SAR simulations showed that the SAR limits obey the guidelines as stipulated by the Federal Communication Commission (FCC) and the International Commission on Non-Ionizing Radiation Protection (ICNIRP) for 1 mW of input power. The 2.45 GHz SAR limit for 1 g of human tissue is 0.09007 W/kg (FCC standard: < 1.6 W/kg) while for 10 g is 0.01867 W/kg (ICNIRP standard: < 2 W/kg). For 5.8 GHz, the SAR limit for 1 g of human tissue is 0.115 W/kg and for 10 g is 0.03517 W/kg. Based on the performance of the antenna in bending condition and the SAR limits, it is safe to conclude that the antenna can be used for wearable applications at 2.45 GHz and 5.8 GHz of the ISM bands.

An Effective Antenna Array Diagnosis Method via Multivalued Neural Network Inverse Modeling Approach

Failure of element (s) in antenna arrays impair (s) symmetry and lead to unwanted distorted radiation pattern. The replacement of defective elements in aircraft antennas is a solution to the problem, but it remains a critical problem in space stations. In this paper, an antenna array diagnosis technique based on multivalued neural network (mNN) inverse modeling is proposed. Since inverse analytical input-to-output formulation is generally a challenging and important task in solving the inverse problem of array diagnosis, ANN is a compelling alternative, because it is trainable and learns from data in inverse modelling. The mNN technique proposed is an inverse modelling technique, which accommodates measurements for output model. This network takes radiation pattern samples with faults and matches it to the corresponding position or location of the faulty elements in that antenna array. In addition, we develop a new training error function, which focuses on the matching of each training sample by a value of our proposed inverse model, while the remaining values are free, and trained to match distorted radiation patterns. Thereby, mNN learns all training data by redirecting the faulty elements patterns into various values of the inverse model. Therefore, mNN is able to perform accurate array diagnosis in an automated and simpler manner.