Complicated Electromagnetic Environment Research Articles

Local charge regulation via selenium vacancies engineering in dielectric cobalt diselenide with enhanced microwave absorption

The weak electromagnetic loss capability of the single semiconductor material is difficult to meet the complicated electromagnetic environment nowadays, so vacancy engineering is employed to optimize the dielectric loss capability of CoSe2. Selenium vacancies are introduced into CoSe2 by re-annealing treatment, and the test results show that the selenium vacancies concentration enlarged with annealing temperature. The formation of selenium vacancies introduces a localized state in CoSe2, which enhances the capability of CoSe2 to trap charge carriers, and the increased conductivity contributes to the enhancement of the dielectric loss capability. Density Functional Theory (DFT) calculations demonstrate that the selenium vacancies disrupt the original charge equilibrium distribution of the CoSe2, and the non-recombined positive and negative charge centers induce a strong electric dipole polarization loss. Benefiting from the optimization of CoSe2 dielectric loss by the selenium vacancies engineering, RLmin of CoSe2-600 reaches −30.73 dB and the effective absorption bandwidth reaches 4.00 GHz at 1.8 mm. This study provides a simple and effective solution to optimize the microwave absorption performance of single-component microwave absorption materials.

Current Loss Mechanism of Magnetic Insulation Transmission Line With Helical Inductance Support

Accurate adjustment of long magnetic insulation transmission lines (MITLs) is crucial in high-power pulsed systems, which must guarantee insulation and high transmission efficiency of current under complicated electromagnetic environment. In this study, a spiral inductance-supported insulation structure in a coaxial MITL was designed, which achieved high efficiency of current transmission up to 90%. Moreover, the current transmission efficiency of the MITL under various working states and specific mechanism of the current loss was investigated by combining circuit with particle-in-cell (PIC) simulations. Results show that the current loss of the inductance-supported MITL in the under-matched state is caused by the inductance current on the support structure, as the electron charge layer is strongly constrained by magnetic field. However, the charge constraint among MITL electrodes is relatively weak in self-limited flow. The electrons bombard the supporting rod, which results in charge accumulation and unneglectable current loss in self-limited flow. This work uncovers the mechanism of current loss in the spiral inductance-supported MITL, which provides guidance for engineering design.

Research on electromagnetic coupling characteristics of UAV circuits in the Complex electromagnetic environment

The overall circuit model and Complex electromagnetic environment model of a typical UAV are built to explore the survivability of multirotor in the complex electromagnetic environment. The composite theoretical calculation model of the metal cavity aperture coupling and internal circuit coupling is constructed using the established UAV circuit model, which is based on the equivalent magnetic dipole algorithm and the FDTD algorithm. The terminal coupling voltage in the UAV circuit and the electromagnetic field distribution inside the metal cavity are estimated. CST software is used to simulate the response of UAV circuits in the same condition, and the correctness of the theoretical calculation model is confirmed. Then, the terminal coupling voltage of the PCB is used to create an electromagnetic coupling efficiency model. The findings reveal that the constructed composite theoretical model can accurately characterize the electromagnetic coupling characteristics of UAV circuits in the complex electromagnetic environment, with an error range of 1%~8%. When comparing the terminal coupling voltage of PCB in various complicated electromagnetic environments, the High-power microwave (HPM) has the maximum coupling efficiency. HPM initially causes the UAV circuits to attain the damage threshold under identical event conditions and target specifications. The findings could be used as a guide for multirotor circuit board protection in the complex electromagnetic environment, as well as for the development of high-power electromagnetic pulse weaponry.

Submodule Switching-State Based EMI Modeling and Mixed-Mode EMI Phenomenon in MMC

Modular multilevel converter (MMC) is widely used in high-voltage occasions for its good power qualities and flexible controls. However, the large number of semiconductor switches would lead to an extremely complicated electromagnetic environment. To clarify the detailed conducted electromagnetic interference (EMI) mechanisms of MMC, this article builds an EMI model of MMC considering different submodule switching states. Based on this model, the EMI paths of submodule switching- <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">on</small> and switching- <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">off</small> processes are analyzed. Then, this article analyzes the effects of submodule heatsink connecting patterns on EMI, and explains the mechanisms of mixed-mode (MM) EMI phenomenon that common-mode component brings in extra differential-mode component. Simulation and experiment results verify the proposed EMI mechanisms and MM phenomenon. The conclusions of this article have great reference significance for the EMI research of MMC and other high-voltage converters.

Design and Fabrication of Layered Electromagnetic Interference Shielding Materials: A Cost-Effective Strategy for Performance Prediction and Efficiency Tuning.

The electromagnetic interference (EMI) shielding market is one of the fast-growing sectors owing to the increasingly complicated electromagnetic environment. Recently, priority has been given to improvise the techniques to fine-tune and predict the shielding properties of structures without exhausting raw materials and reduce the expense as well as the time required for optimization. In this article, we demonstrate an effective and precise method to predict the EMI shielding effectiveness (SE) of materials via simulating the performance of composites having alternate layers of conducting and magnetic materials in a virtual waveguide measurement environment based on the finite element method (FEM). The EMI SE of multilayered heterogeneous arrangements (MHAs) is simulated in the K-band region using ANSYS High Frequency Structure Simulator (HFSS) software, which can be extended to all other bands as well. Various simulations carried out by changing the order of the conducting and magnetic layers and the number of layers revealed that the strategic arrangement of electromagnetic (EM) energy-trapping layers inside the impedance-matching layers in the MHAs significantly contributes toward the enhancement of absorption-dominated EMI shielding. Among the MHAs, the conducting-magnetic-conducting (CMC) systems exhibited the highest shielding effectiveness of above 50 dB. The MHAs are realized for testing using poly(vinylidene fluoride)-based composites of low-cost carbon black and barium hexaferrite, an easily accessible ferrite. Through this study, we propose the idea that materials with high production cost and cumbersome fabrication procedures are not necessary to realize highly efficient shielding materials.

A Transparent Tunable Broadband Microwave Absorber Based on Multi-layer Structure by Patterned Graphene

As the increasingly complicated electromagnetic environment, it is crucial to develop the performance of transparent microwave absorbers. Here we proposed a transparent tunable broadband microwave absorber, which is consisted of double-layer graphene rings and metallic grids. The microwave shielding properties can be changed by adjusting the dielectric layer thickness, graphene Fermi energy and relaxation time. Based on the simulated results, the proposed transparent microwave absorber can achieve microwave absorption of over 85% at a frequency range of 4.61–9.75 GHz, indicating a relative absorption bandwidth nearly 71.6% and a normalized transmittance of 88.8% in the visible band.

Specific Emitter Identification Model Based on Improved BYOL Self-Supervised Learning

Specific emitter identification (SEI) is extracting the features of the received radio signals and determining the emitter individuals that generate the signals. Although deep learning-based methods have been effectively applied for SEI, their performance declines dramatically with the smaller number of labeled training samples and in the presence of significant noise. To address this issue, we propose an improved Bootstrap Your Own Late (BYOL) self-supervised learning scheme to fully exploit the unlabeled samples, which comprises the pretext task adopting contrastive learning conception and the downstream task. We designed three optimized data augmentation methods for communication signals in the former task to serve the contrastive concept. We built two neural networks, online and target networks, which interact and learn from each other. The proposed scheme demonstrates the generality of handling the small and sufficient sample cases across a wide range from 10 to 400, being labeled in each group. The experiment also shows promising accuracy and robustness where the recognition results increase at 3-8% from 3 to 7 signal-to-noise ratio (SNR). Our scheme can accurately identify the individual emitter in a complicated electromagnetic environment.

Predictive deadbeat average model control for phase‐shifted full‐bridge DC/DC converter

Digital current control method is the mainstream method for high-power DC/DC converters. However, digital controllers require additional filters for noise suppression to ensure their proper operation in the complicated electromagnetic environment. The filtering processes coupled with the inherent time delays of digital systems significantly degrade dynamic performance. Thus, steady-state performance is improved at cost of dynamic performance in conventional current control. To solve the problems, this paper establishes a deadbeat average control model based on application of the oversampling technique for phase-shifted full-bridge (PS-FB) DC/DC converter and proposes a predictive deadbeat average model control method by incorporating predictive control into the proposed control model. Simulation and experimental results verify the effectiveness of the proposed control method in mitigating the contradiction between steady-state performance and dynamic performance in the digital system.

Intra-Pulse Modulation Recognition of Dual-Component Radar Signals Based on Deep Convolutional Neural Network

In an ever-increasingly complicated electromagnetic environment with explosive radar signals density, accurate and fast recognition of dual-component radar signals has become an urgent problem in the current radar reconnaissance system. This letter proposes a novel multi-class learning framework based on deep convolutional neural network (DCNN) for recognizing eight types of randomly overlapping dual-component radar signals. The framework mainly includes dual-component radar signals preprocessing, DCNN model that aimed to extract more effective dual-component radar signals features, and multi-class classification. The results shown that the average classification accuracy of dual-component radar signals can be up to 96.17% when the signal-to-noise ratio (SNR) is −8 dB, which demonstrates the superior performance over others. The proposed model possesses the larger improvement for 4FSK, BPSK, EQFM, and FRANK, especially at the lower SNR. This work provides a sound guidance for further improving multi-component radar signals recognition.

MR‐DCAE: Manifold regularization‐based deep convolutional autoencoder for unauthorized broadcasting identification

Nowadays, radio broadcasting plays an important role in people's daily life. However, unauthorized broadcasting stations may seriously interfere with normal broadcastings and further disrupt the management of civilian spectrum resources. Since they are easily hidden in the spectrum and are essentially the same as normal signals, it still remains challenging to automatically and effectively identify unauthorized broadcastings in complicated electromagnetic environments. In this paper, we introduce the manifold regularization-based deep convolutional autoencoder (MR-DCAE) model for unauthorized broadcasting identification. The specifically designed autoencoder (AE) is optimized by entropy-stochastic gradient descent, then the reconstruction errors in the testing phase can be adopted to determine whether the received signals are authorized. To make this indicator more discriminative, we design a similarity estimator for manifolds spanning various dimensions as the penalty term to ensure their invariance during the back-propagation of gradients. In theory, the consistency degree between discrete approximations in the manifold regularization (MR) and the continuous objects that motivate them can be guaranteed under an upper bound. To the best of our knowledge, this is the first time that MR has been successfully applied in AE to promote cross-layer manifold invariance. Finally, MR-DCAE is evaluated on the benchmark data set AUBI2020, and comparative experiments show that it achieves state-of-the-art performance. To help understand the principle behind MR-DCAE, convolution kernels and activation maps of test signals are both visualized. It can be observed that the expert knowledge hidden in normal signals can be extracted and emphasized, rather than simple overfitting.

SIMULATION AND MEASUREMENT OF EXTERNAL ELECTROMAGNETIC ENVIRONMENT OF TOKAMAK DEVICE.

Magnetic confinement nuclear fusion is an important way to realize controllable nuclear fusion. Due to the large current and complicated coil arrangement, there is a complicated electromagnetic environment around the fusion device. In this paper, the B-dot sensor is used to measure the magnetic field, the D-dot sensor is used to measure the electric field, the MAXWELL electromagnetic simulation software is used to simulate the electromagnetic field strength; the simulation and measurement of the spherical Tokamak SUNIST device and the measurement of MARX generator are carried out, then we give corresponding electromagnetic protection suggestions.

A Multiagent Reinforcement Learning Solution for Geometric Configuration Optimization in Passive Location Systems

Passive location systems receive electromagnetic waves at one or multiple base stations to locate the transmitters, which are widely used in security fields. However, the geometric configurations of stations can greatly affect the positioning precision. In the literature, the geometry of the passive location system is mainly designed based on empirical models. These empirical models, being hard to track the sophisticated electromagnetic environment in the real world, result in suboptimal geometric configurations and low positioning precision. In order to master the characteristics of complicated electromagnetic environments to improve positioning performance, this paper proposes a novel geometry optimization method based on multiagent reinforcement learning. In the proposed method, agents learn to optimize the geometry cooperatively by factorizing team value function into agentwise value functions. To facilitate cooperation and deal with data transmission challenges, a constraint is imposed on the data sent from the central station to vice stations to ensure conciseness and effectiveness of communications. According to the empirical results under direct position determination systems, agents can find better geometric configurations than the existing methods in complicated electromagnetic environments.

Evaluation of Deceptive Jamming Effect on SAR Based on Visual Consistency

In complicated electromagnetic environments, synthetic aperture radar (SAR) can be threatened by various kinds of malicious interference, of which deceptive jamming is the intentional and efficient one. For jamming effect evaluation on SAR images, traditional methods are mostly based on the change of image quality, while not suitable for evaluating the confusion caused by high-fidelity false targets. In this paper, a novel framework to evaluate the effect of deceptive jamming on SAR is proposed based on visual consistency (VC). Three levels of vision, namely detection, recognition and semantics, are fused for efficient deception evaluation along with the corresponding metrics system. Fully considering the imaging characters of deceptive jamming, specifically designed detection and recognition flows are introduced to quantitatively evaluate the deception. Furthermore, to evaluate whether the generated false targets are with reasonable context, a unprecedent concept named semantic accuracy is proposed via considerations of statistical differences compared with that of the background template. Besides, the cases that deceptive jamming with several common non-ideal issues are considered when evaluating the effects. Sufficient experiments have proved the practicality and superiority of the proposed evaluation framework under different deceptive jamming with various non-ideal factors.

Low Complexity Anti-Interference Transmission Model in Massive MIMO Systems

With the development of wireless communication, wireless communication technology plays an irreplaceable role in modern instrument measurement and communication. However, the complex electromagnetic been an important factor affecting wireless communication quality with the number of devices increasing. Especially in the industrial field and modern city, electromagnetic interference (EMI) is a serious issue in wireless data transmission. Besides, user interference will also reduce the communication performance with the increasing number of equipment users. In this paper, a low-complexity data transmission model is proposed. First, the direct sequence spread spectrum (DSSS) technology is utilized to oppose narrowband electromagnetic interference and noise interference. Nevertheless, the DSSS be affected by multi-user interference (MUI) due to the number of users increasing. Based on DSSS and ZF precoding, the DSSS-ZF structure is proposed to resist interference. The simulation platform utilized the Software Defined Radio (SDR) and channel emulators (CE) to measure our DSSS-ZF model. The results show that the DSSS-ZF structure model can effectively defeat interference and improve the reliability of communication in complicated electromagnetic environment.

High-conversion-gain and deep-image-rejection Brillouin chip-based photonic RF mixer.

In this Letter, we report a chip-based photonic radio-frequency (RF) mixer with a maximum conversion gain of -9dB and image rejection ratio of 50 dB for 3.2 GHz to 13.2 GHz RF frequency range. This is achieved by the combined use of optical carrier suppression modulation and on-chip stimulated Brillouin scattering. These results will stimulate future implementations of integrated photonic RF mixers in complicated electromagnetic environments.

Electromagnetic Disturbed Mechanism of Electronic Current Transformer Acquisition Card under High Frequency Electromagnetic Interference

The electronic current transformer (ECT) acquisition card is widely used in smart grids with many advantages. However, with the continuous improvement of the power grid and localized intelligent electronic devices, the electromagnetic environment under the operating conditions of gas insulated switchgear (GIS) substations is becoming more complicated. The reliability and safety of the ECT acquisition card will be endangered due to the complicated electromagnetic environment. In order to solve these problems, this paper investigates the electromagnetic disturbed mechanism of the ECT acquisition card. The effects of different grounding methods on the electromagnetic interference of the ECT acquisition card were studied. A platform based on IEC 61000-4-4 was built, and the electromagnetic interference (EMI) of the ECT acquisition card with different grounding methods was measured. The results show that the lower grounding impedance of the ECT acquisition system increased the internal EMI. Further, the high frequency electrical fast transient/burst coupling mechanism was analyzed. The parasitic parameters of the acquisition card were extracted based on the critical circuit by using the finite element method. Then, the high-frequency EMI coupling model of the ECT acquisition card was established.

Electromagnetic Shielding Box Design of Radial X-Ray Camera Electronics

In order to ensure the electronics of radial X-ray camera (RXC) system can work normally under the complicated electromagnetic environment of Tokamak system, simulation and analysis of the static magnetic distribution is done in this paper. The electromagnetic shielding box is designed and shielding effort was validated through simulation with software Maxwell. The shielding box designed can reduce the static magnetic flux density from 230 mT to less than 5 mT, meeting the requirements of anti-electromagnetic interference ability of electronics.

Unauthorized Broadcasting Identification: A Deep LSTM Recurrent Learning Approach

Radio broadcasting plays an important role in our daily life. Meanwhile, with the development of wireless communications, the application of software-defined radio platforms gives rise to cheap and easy design of illegal broadcasting stations. These unauthorized broadcasting stations sometimes illegally occupy licensed frequency band, especially associated with amateur radios and unlicensed personal communication devices and services. These unauthorized broadcasting stations may severely interfere with the authorized broadcasting and further disrupt the management of spectrum resource in civil applications, such as emergency services and air traffic control. However, it still remains a challenging task to automatically and effectively identify the unauthorized broadcasting in complicated electromagnetic environments. Aiming at developing an intelligent and efficient unauthorized broadcasting identification system, in this article, a novel identification approach is proposed based on long short-term memory (LSTM) recurrent neural network (RNN), and LabVIEW software. In our approach, first, a series of LabVIEW applications are developed to drive USRP 2930s for the acquisition of broadcasting signals. Then, the LSTM identification network is proposed to recognize unauthorized broadcasting. Through the special gate structure inside, the proposed LSTM framework can effectively extract the distinguishing features, such as channel state information and RF device fingerprinting. Simulation results show that the proposed LSTM-based approach perform better than other contrastive methods, especially in identification accuracy. Implementation results also demonstrate that the proposed method has an outstanding unauthorized broadcasting identification performance with a high accuracy, i.e., identify the unauthorized broadcasting signals with 99.83% accuracy at the licensed frequency of 107.8 MHz, in realistic electromagnetic environments.

Research on Complex Electromagnetic Environment Simulation System

With the battlefield electromagnetic environment become more complex, these also weaken operational effectiveness of information technology equipment. Therefore, to seize the electromagnetic superiority become the key of the war in the information control and then take the initiative. In view of the complicated electromagnetic environment simulation, this paper studies the hardware and software of complex electromagnetic environment simulation system. The system has the function of electromagnetic signal parameters editor, multi-domain real-time monitoring function, parameter real-time control function, test evaluation function, the target database management function and system configuration function. To improve the ability of combat troops in complex electromagnetic environment is of great significance.

Interference Elimination of Wall Fluctuation Pressure Test Signal of High-Speed Train Based on Phase Space Reconstruction and Vibration Interference Model

Because of the complexity of high-speed train operation, the measured wall pressure of high-speed train will be affected by many factors, such as train vibration and environmental changes, which make the test signal inaccurate. The main interferences are the electromagnetic interference caused by the complicated electromagnetic environment and the sensor output interference caused by the train body vibration. In this paper, ensemble empirical mode decomposition (EEMD) combined with singular value decomposition (SVD) and the local projection de-noise algorithm with better effect on non-linear time series noise reduction are used to eliminate electromagnetic interference in test signal. Because of the frequency band aliasing of test signal and interference cause by vibration, it is difficult to eliminate vibration interference by the signal processing method. In this paper, a vibration interference model is established by model-train experiment and computational fluid dynamics (CFD) software to eliminate the vibration interference in the test signal. Moreover, the theoretical guidance for accurately extracting the wall pressure of high-speed train has been put forward.