The method of building equivalent electromagnetic environment

The complex geographical environment and electromagnetic interference environment within the radar deployment position area will seriously degrade the radar detection performance. Focusing on the urgent requirement of optimizing radar deployment in complex geographic and electromagnetic environments, the environment-constrained radar position positioning optimization method is investigated. Firstly, based on the terrain and electromagnetic interference environment of radar positions, a radar position selection method under both geographic and electromagnetic environment constraints is established. Then the propagation loss under complex geographical terrain is calculated by combining the radar equations, and the detection power of target height layer and the coverage power of the focused area are used as the evaluation indicators for the superiority of radar sites. Finally, the detection range of the radar under multiple environmental constraints is visualized. The problem of complex radar operational scenarios in real systems and the single constraint considered in traditional radar equipment deployment methods is addressed. By calculating the propagation loss, terrain loss, electromagnetic loss under multiple environmental and electromagnetic constraints, and adding actual elevation and terrain data as reference, a more realistic and objective analysis of the impact of the environment around the position on the performance of radar equipment is provided, and finally the evaluation indexes and selection methods is proposed in this paper. The proposed evaluation indexes and selection methods and visualization can provide accurate, reliable and intuitive strategies for optimizing the deployment of radar equipment under multiple constraints.

This study introduces an electromagnetic interference detection technique to increase the immunity of a microcontroller-based system in a complex electromagnetic environment (EME). The detection method is explained. First, the interference in the power supply and at the input port of the microcontroller is detected. The simulation results are achieved in both time domain and frequency domain. The measurement results are obtained to verify the correctness of the detection method and the application of the detection method in the automotive field is presented. The final objective of the work is to ensure that the microcontroller-based system works fast in a normal EME and correctly in a complex EME without adding too much cost.

To accurately evaluate Beidou(BD) receivers complex electromagnetic environment adaptive capacity, based on the analysis of the working mechanism and the easy attack of the receiver, BD receiver facing war complex electromagnetic environment is constructed, simulation on the effect of signal capture and tracking is carried out, and assessment method is studied. The relationship between the positioning success rate and communication success rate of a certain type of BD receiver and electromagnetic environment complexity is given, providing BD receiver application with important reference significance.

Assessing the complexity degree of electromagnetic environments (EME) is a typical pattern recognition problem. Feature extraction is the most significant step for EME complexity classification tasks. In his work, a novel feature extraction scheme for EME complexity classification scheme based on non-negative matrix factorization (NMF) is presented. EME signals with four complexity degree are simulated to evaluate the effectiveness of the presented method. Experimental results reveal that the NMF based features to be desirable indices for accurate complexity degree evaluation of EME.

Electromagnetic compatibility (EMC) is the ability of a Radio communication Equipment (RCE) to operate with a desired quality of service in a given Electromagnetic Environment (EME) and not to create harmful interference with other RCE. This paper presents an algorithm which improves the simulation speed of estimating EMC of RCE in a complex EME, based on a stage by stage frequency-energy filtering criterion. This algorithm considers different interference types including: Blocking and intermodulation. It consist of the following steps: simplified energy criterion where filtration is based on comparing the free space interference level to the industrial noise, frequency criterion which checks whether the interfering emissions characteristic overlap with the receiver's channels characteristic and lastly the detailed energy criterion where the real channel interference level is compared to the noise level. In each of these stages some interference cases are filtered out by the relevant criteria. This reduces the total number of dual and different combinations of RCE involved in the tedious detailed energy analysis and thus provides an improved simulation speed.

The parabolic equation (PE) method is very effective for computing the complex electromagnetic environment (EME) simulation. For the large-scale 3D EME simulation based on the PE method, the computation and time complexity is not acceptable. To solve this problem, a quasi-3D PE simulation method with low complexity is introduced. But the accuracy of this method is not high, and some methods have been proposed to improve the accuracy by compensating error, choosing appropriate slice angle, interpolating some values between slices and mixing the PE and ray tracing method. With a multi-level parallel method, the 3D EME simulation can be paralleled from the three levels: job parallel, task parallel, thread parallel, and it is used to accelerate the computation process dramatically in order to calculate faster.

The basins of the inland waterways of the Russian Federation are characterized by a variety of specific navigation features, the destructive effects of which significantly affect the parameters of the purpose of radio navigation systems. Therefore, the task arises to develop a model and estimate the electromagnetic deformation of the high-precision radio navigation field in the basins of the inland waterways of Russia caused by their navigational features. The study and identification of the general navigational features of the basins of the inland waterways of Russia and the assessment of the degree of influence of their destabilizing factors on the quality indicators of the high-precision radio navigation field. New navigation features have been identified in the basins of the inland waterways of Russia, the destructive factors of which deform the high-precision radio navigation field and reduce the quality of transmission of differential corrections. The results obtained confirm a decrease in the accuracy of positioning unmanned vessels in sections of the waterway with a complex terrain topology and electromagnetic environment. At the same time, the positioning accuracy in river basins may deteriorate in local areas from 1.6 times (from 6.8 m to 28.7 m) to 4.3 times (from 27.3 m to 117 m), depending on the electro-magnetic situation and the value of the geometry coefficient. A decrease in the quality of differential correction transmission will be manifested at the boundaries of service areas and range from 1 dB in sparsely populated areas and up to 30 dB in industrial zones. These factors will reduce the safety of navigation, so they must be taken into account when operating ships and designing functional additions to the global nav. The results obtained in the work can be used in the formation and optimization of the topology of control and correction stations of differential additions to the global navigation satellite system and to meet the requirements for the accuracy of positioning of mobile objects in difficult physical and geographical conditions of the terrain and electromagnetic environment.

Electromagnetic environments are becoming increasingly complex and congested, creating a growing challenge for systems that rely on electromagnetic waves for communication, sensing, or imaging. The use of intelligent, reconfigurable metasurfaces provides a potential means for achieving a radio environment that is capable of directing propagating waves to optimize wireless channels on-demand, ensuring reliable operation and protecting sensitive electronic components. Here we introduce wavefront shaping, a technique that combines a deep learning network with a binary programmable metasurface to shape waves in complex electromagnetic environments and to drive the system towards a desired scattering response. We applied this technique to accurately determine metasurface configurations based on measured system scattering responses in a chaotic microwave cavity. The state of the metasurface that realizes desired electromagnetic wave field distribution properties was successfully determined even in cases previously unseen by the deep learning algorithm. Our work represents an important step towards realizing intelligent reconfigurable metasurfaces for smart radio environments that can ensure both the integrity of electronic systems and optimum performance of wireless networks.

In this paper we discuss electromagnetic compatibility problems that arise in "Smart city" with electronic infrastructure. There the technical means and system are using in a hard electromagnetic environment in industrial, residential and public areas, as well as in transport. A special load falls on telecommunication networks, which provide both traditional communication and the management of various IoT devices, technical systems and ets. Radio emissions increase significantly. It was emphasized that the continuous and full functioning of technical means in the electromagnetic environment of "Smart city" and the elimination of unacceptable electromagnetic interference created by technical means are mandatory conditions for the implementation of "Smart city" concept, so the safety problem consideration is required. We overview the possible problems overview in the concept of a "Smart city" related to equipment and systems electromagnetic safety. Particular attention is paid to technical means and systems related to safety, for example, used in transport and also telecommunication networks. It was emphasized that the continuous and full quality functioning of technical means in "Smart city" electromagnetic environment and the elimination of unacceptable electromagnetic interference created by technical means are mandatory conditions for the implementation of "Smart city" concept, and should take into account all aspects associated with a specific electromagnetic environment with a high density of electronic equipment, requirements for telecommunications networks quality communication

Introduction. The Russian telecommunications industry is on the threshold of introducing 5G/IMT-2020 (5G) mobile communications. The expected technological innovations of the new generation standard will lead to an increase in the capacity of mobile operators ‘ networks, data transfer speeds, the emergence of new scenarios for the use of mobile communications and the development of innovative digital services. This will contribute to economic growth by increasing labour productivity, automation and introducing new technologies in various economy and human activity areas. At the same time, the electromagnetic environment (EMO) in the areas where people stay will also change. The purpose of the study is to consider the unique features of the architecture of the 5G network to predict the impact on the population of electromagnetic fields (EMF) of the radio frequency (RF) range. Material and methods. The study is analytical. The information base of the research was Russian strategic documents on the development of 5G technologies, articles published in domestic and foreign journals. Results. The primary input data for the construction of 5G networks are presented, allowing us to evaluate EMO and identify the new technology features that are significant in terms of the impact of RF electromagnetic fields on the population. The 5G network uses previously unused RF bands and new types of antennas. With the introduction of 5G, the density of base stations (BS) and access points will significantly increase, the heights of BS antennas will decrease, and the spatial and temporal characteristics of electromagnetic radiation will change substantially. Conclusion. The architecture of the 5G network differs significantly from the mobile communication standards of previous generations. The introduction of 5G networks will lead to a significant change in the electromagnetic background in the environment. An urgent task is to develop a theory of hygienic regulation of RF EMF for the population in a complex electromagnetic environment with simultaneous operation of 5G networks and previous generations and new approaches to determining the levels of EMF in the environment by computational and instrumental methods.

This paper presents a safety assessment model with regard to electromagnetic compatibility (EMC) fault suitable for estimating the EMC failure probability (EMC FP) of the complex system facing uncertain electromagnetic environment. First, the model is successfully applied to decompose the complex system into different independent subsystem and equipment. Then the practical EMI scenario is modeled as different typical EMC problem, such as the Plane Wave Coupling and Crosstalk respectively. After that the fault tree analysis (FTA) is proposed to use in combination with electromagnetic topology (EMT) calculating the EMC FP of the system. A focus is put on the practical case of the Desktop Management Interface (DMI) system. In this context, a system-level EMC safety assessment model has been applied to solve EMC FP by uncertainty analysis in high speed railways with the complex electromagnetic environment.

Radar signal sorting is a key technology in electronic warfare. The quality of signal sorting directly determines the outcome of electronic warfare. The accuracy and real-time performance of signal sorting are two important indicators to evaluate the quality of signal sorting. With the increasingly complex electronic countermeasure environment, there are many radar radiation sources in the battlefield, and the signal aliasing is serious. At the same time, there may be pulse loss and interference pulse in the electromagnetic environment. In such a complex electromagnetic environment, in order to improve the accuracy and real-time of radar signal sorting and master the battlefield initiative, this paper proposes a method of radar signal batch processing sorting based on sliding window. Firstly, the radar signal sorting transient library and the sorted radar signal library are set up, and the transient library is used to store radar signals in the sliding window. Move the sliding window continuously from the starting point. When the number of signals in the transient library is higher than the specified threshold, sort the radar signals in the transient library, and then store the sorted radar signals in the sorted radar signal library and delete them from the transient library. When the sliding window moves to the end point, the signals in the sorted radar signal library are merged. Simulation results show that compared with traditional methods, the proposed method has higher sorting accuracy and better real-time performance when there are more radar pulses and pulse loss.

Frequency hopping (FH) communication has good anti-fading, anti-jamming and anti-eavesdropping capabilities, so it is one of the main ways to combat electronic jamming. In order to further improve the anti-jamming capability of FH communication, the parameters such as fixed frequency interval, hopping rate and hopping frequency in conventional FH can be assigned with time-varying characteristics. In order to set appropriate hopping parameters to improve the performance of the system in the electromagnetic environment with various types of jamming, a heuristically accelerated Q-learning (HAQL) method is proposed in this paper. Firstly, a theoretical model for the parameter decision-making of FH system is made, and the key parameters affecting the energy efficiency of the system are analyzed. Secondly, a Q-learning model in complex electromagnetic environment is proposed, which includes setting states, actions and rewards, as well as a HAQL-based decision-making algorithm is put forward. Lastly, simulations are carried out under different jamming environments, and simulation results show that the average energy efficiency of HAQL algorithm is higher than that of the SARSA algorithm, the e-greedy QL algorithm and the HQL-OSGM algorithm, respectively.

Purpose This paper aims to design and investigate a high-precision tunneling magnetoresistance (TMR) noncontact current sensor based on a dual-gap anti-interference structure, to address the susceptibility of traditional TMR current sensors to external interference in complex electromagnetic environments. Design/methodology/approach A systematic methodology integrating theoretical modeling, finite element simulation and experimental validation was used. A mathematical model of the dual-gap magnetic circuit was established based on magnetic Ohm’s law to analyze its differential output mechanism for suppressing common-mode magnetic field interference. Key parameters such as magnetic core cross-section and air gap dimensions (a = b = 7 mm) were optimized through finite element simulation, evaluating magnetic field uniformity and conductor displacement error. Thermal performance and anti-interference capability were experimentally validated under controlled conditions. Findings The optimized dual-gap structure improves magnetic field uniformity to 0.0010 and reduces measurement error caused by conductor displacement to below 0.08%. It also demonstrates superior thermal management, lowering temperature rise by 27.4% compared to a single-gap structure under high load. Under an external interference field of 10 Oe, the dual-gap sensor achieves an output voltage error of 0.014%, outperforming the single-gap design (0.017%). The sensor maintains a linearity of ± 0.5% and an accuracy of ± 1% across a temperature range of –50°C to 70°C. Originality/value This study proposes an innovative dual-gap magnetic circuit structure that effectively enhances anti-interference performance and thermal stability in TMR current sensors. The research provides a practical and reliable design pathway for developing high-precision, robust current sensors suitable for demanding electromagnetic environments.

Interference detection is very important for high reliability applications with array-based GNSS receivers in complex electromagnetic environments, such as shipping positioning in sensitive waters, electromagnetic environment monitoring around the GNSS ground reference stations, etc. According to the common hypothesis that the power of the interference is far greater than the received GNSS signal, the interference can be detected using the ratio of the maximum eigenvalue and the minimum eigenvalue of the sample covariance matrix. However, the probability distribution function of the eigenvalue ratio is complex, it is difficult to compute the optimized threshold and analyze the detection performance. To solve these problems, the Tracy-Widom distribution is accurately approximated by using the Gaussian distribution with suitable parameters, and the analytical formulas for threshold setting are given under the constant probability of missed detection condition for the first time, then threshold setting and detection performance under different parameters are analyzed by simulation.