Comprehensive Experimental Research on Complex Electromagnetic Environment of Aircraft

Electronic jamming is the key technology of electronic countermeasure, for which models and simulations are studied on noise jamming, deception jamming, and chaff jamming. In the noise jamming, the simulation analysis of radio frequency noise jamming is conducted and the theoretical models of other forms of noise jamming are built. The simulation analysis of range-gate pull off (RGPO) is carried out in the deception jamming. In addition, theoretical modeling and simulation analysis of chaff jamming are carried out with the Monte Carlo method. Simulation results show that the models are correct and can be used to simulate the statistical characteristics of chaff jamming. With the development and wide application of electronic technology, radar, communication, navigation, and IFF signals constitute a complex electromagnetic environment. It is a must to study electronic jamming technology in the complex electromagnetic environment, which will play an indispensable role in the construction of information team and victory in the countermeasure of information technology.

Electrical stimulation vs thermal effects in a complex electromagnetic environment

This article presents an overview of wideband and multiband antennas for both ground-based and airborne applications. It includes previously published designs as well as new ones with improved performance. The use of such antennas significantly enhances the overall efficiency of communication systems. For airborne antennas, benefits include reduced aerodynamic drag, improved performance of radio communication equipment, lower UAV takeoff weight, reduced feeder line losses, and improved electromagnetic compatibility. For ground antennas, advantages include reduced weight and size of the ground control station (terminal), simplification and higher efficiency of the data terminal, shorter deployment time, and improved mechanical strength. The article also presents an application diagram for wideband and multiband antennas in UAS communication systems. The diagram illustrates the potential of using multiple communication modems configured for different frequency ranges via microstrip multiplexers. The results can be useful for developers of both unmanned aerial systems and UAS communication equipment, including individual components. The article demonstrates that the use of wideband and multiband ground and airborne antennas can substantially improve communication quality in complex electromagnetic environments while maintaining optimal values for weight, size, aerodynamic drag, and technological advancement of UAS communication equipment.

Modern warfare is carried out in a complex electromagnetic environment, where noise suppression interference directly affects the detection ability of airborne warning radar to target, in order to make airborne warning radar play its due role in battlefield. More and more requirements are put forward for radar combat capability in complex electromagnetic environment, that is, the requirement of radar anti-jamming ability in complex electromagnetic environment is becoming higher and higher. Suppression jamming is to cover or submerge useful signals with noise or similar jamming signals to prevent radar from detecting target signals. In order to evaluate the influence of suppression jamming on airborne warning radar, the influence of suppression jamming on the detection probability and detection distance of warning radar is analyzed. The variation of radar detection range and detection probability in complex electromagnetic environment compared with normal detection is given by flight test. It also provides a reference for evaluating the anti-jamming ability of airborne warning radar after being suppressed.

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.

The semi-physical simulation test method is the research focus of electronic warfare equipment performance evaluation test in complex electromagnetic environment. The complex electromagnetic environment signal generation technology based on digital geographic information is an effective technical approach to implement semi-physical simulation test. In this paper, the idea, method and current development of this technology was introduced from three aspects, i.e. simulation modeling in complex electromagnetic environment, electromagnetic signal propagation simulation based on digital geographic information, and complex-type signal generation.

The increasingly complex electromagnetic environment (CEME), characterized by dense signal occupancy, intentional interference, and dynamic spectral congestion, poses significant challenges to electromagnetic (EM) sensing technologies. This review comprehensively surveys the theoretical foundations and practical applications of EM sensing within such challenging environments. Key theoretical principles underpinning robust sensing in CEME are elucidated. The topics include wave propagation fundamentals, advanced modeling and characterization of CEME, detection and estimation theory under interference, and electromagnetic compatibility coupled with dynamic spectrum management. The practical deployment of EM sensing technologies is examined across critical sectors including defense (leveraging cognitive radar, multi-sensor fusion), communications (spectrum sensing for cognitive radio/dynamic access), and aerospace (addressing interference threats like 5G to altimeters). Emerging trends such as AI/ML-enhanced sensing, integrated sensing and communication, and collaborative/distributed sensing networks are highlighted as pivotal for future advancements. The review concludes by outlining key challenges and research directions aimed at enhancing sensor adaptability, resilience, and spectral efficiency in the face of ever-growing EM complexity.

To solve the problem that tradition signal recognition algorithms cannot effectively recognize the contaminated and diverse radar signals in complex and variable Electronic Warfare (EW) environment, a new recognition method based on deep convolutional neural network (CNN) and time-frequency (TF) analysis is proposed. Firstly, the TF images of radar signals are extracted as the inputs to the CNN model. Then, a new network, called CNN-TF, is constructed to analyze these time-frequency images and use the robustness of CNN to suppress the noise interference. Thirdly, a complete and diverse signal librai7 is constructed based on the complex EW environment, and the librai7 is used to train and test CNN-TF. Finally, trained CNN-TF will be used for signal recognition. Simulation results show that the proposed algorithm not only improves the performance of signal recognition, but also has excellent anti-noise performance, which makes the proposed algorithm adapt to the complex and variable electronic warfare 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.

The complex electromagnetic environment will limit the efficacy of communication equipment. It is critical to construct a complex electromagnetic environment to test communication equipment in order to maximize its capability. One of the most important methods for constructing a complex electromagnetic environment is signal reconstruction. This paper proposes a VAE‐GAN‐based method for reconstructing direct sequence spread spectrum (DSSS) signals. In this method, the deep residual shrinkage network (DRSN) and self‐attention mechanism are added to the encoder and discriminator of VAE‐GAN. In feature learning, the DRSNs can reduce the redundant information caused by noise in the collected signal. The self‐attention mechanism can establish the long‐distance dependence between the input sequences, making it easier for the network to learn the samples’ pseudonoise (PN) sequence features. In addition, feature loss is applied to the encoder and generator to improve network stability during training. The results of the experiments indicate that this method can reconstruct DSSS signals with the characteristics of the target signal.

With the proliferation of frequency-using devices and the advent of the era of big data, spectrum management and control are faced with challenges of effectiveness and accuracy. Modulation classification technology is the foundation and key part of spectrum management and control. Therefore, the effectiveness of modulation classification technology in big data scenario is very important. In this paper, we consider not only the validity of the classification model under the background of big data, but also the dynamics of noise in the complex electromagnetic environment. So we construct a big dataset containing different signals under different MSNR, and use the big data to drive the deep learning model, and finally get the classification result. The proposed method can realize modulation classification only by training one model, which avoids the redundancy of model training in previous algorithms. The simulation results demonstrate the effectiveness and reliability of the proposed method.

There are many limitations depend on traditional physical product testing methods. Firstly, the cost is high and adaptability is poor. Secondly, the test is lag and it can’t follow the new product design’s beat. Thirdly, it can’t converge with digital design method, and it difficult to meet with the requirement of industry information. Study a product’s digital test method which based on modern design technical, and discuss simulation testing technical come true which face to virtual prototyping of bag filter, and aiming at digital testing result of bag filter main working capability prove feasibility and effectiveness of this method. Firstly, analyses components of digital virtual testing system and theory of working, and provide design model of virtual prototyping testing and testing progress how to come true, and by changing the condition of working simulation, and sampling, and data processing, acquire the result of dust gas uniformity which is design prototyping of bag filter. Application prove that digital process, face to digital testing of product virtual prototyping, by testing object and testing instrument and testing progress, and so on, adopting model simulation, digital simulation, calculate experiment, simulate testing technical, complete prototyping testing working under fully virtual state in computer. Let prototyping design quality controlling which is based on quantizing move forward. Achieve parallel designing and testing, which is full with the zero-cost, zero-lag, zero error of large and complex mechanical equipment design testing.

In order to improve the fidelity and controllable of electromagnetic environment(EME) building, and build realistic EME for testing and researching the complex EME effect on the electronic information systems, this paper puts forward Equivalent building methods of complex EME based on the meta-elements. First, the paper analysis the domestic and foreign research which presents the current situation and the demand, and then puts forward the methods and expounds the core idea of basing the meta-elements to realize the equivalent EME building. Further it introduces extraction method of the electromagnetic signal environment meta-elements, and builds the description of them. In the end, it put forward the method and process to build the complex EME based on the meta-elements. This research results provide the technical support to improve the level of test EME building.

This paper mainly introduces the development status of radio frequency / infrared stealth materials, puts forward the application of nanostructured composite materials in stealth field, describes the characteristics and stealth mechanism of nanostructured composite materials, expounds the research status of a nanostructured composite carbon fiber material in radar and infrared stealth technology, and introduces the latest research results and application status of this material prepared by The 33rd Research Institute of China Electronics Technology Group Corporation in detail.Through data simulation and modeling, the stealth characteristic data of the nanostructured composite carbon fiber material are calculated. The material performance has reached the international advanced level, which can be applied in the future more complex electromagnetic environment, further improving the wartime survival ability of electronic equipment, and looking forward to the application prospect of the new nanostructured composite materials in the field of stealth.

With the widespread application of UAV technology, various countries are facing new threats in both military and civilian domains. To effectively counter these threats, UAV communication jamming has become a reliable countermeasure. Traditional communication jamming methods face several challenges. These include low efficiency, difficulties in managing dynamic and complex electromagnetic environments, and a heavy reliance on prior knowledge about the signals. This study presents intelligent jamming techniques for UAV signal processing to overcome the limitations found in current communication jamming technologies. The aim is to achieve precise jamming of individual target signals using intelligent jamming methods. This paper introduces an enhanced jamming signal generation algorithm built on the traditional convolutional autoencoder. Without relying on prior signal knowledge, the algorithm introduces complex convolutional networks and residual modules. The model leverages advanced convolutional networks to integrate the real and imaginary components of the signal for feature extraction, while the residual modules further refine signal processing and enhance feature learning. The model generates jamming signals by altering hidden layer features. These signals closely resemble the original communication waveforms. Simulation results show that, across different communication systems, the generated jamming signal waveforms exhibit strong similarity to the original signal waveforms. Moreover, under various signal-to-interference ratios (SIR), the jamming performance of the generated signals surpasses that of conventional jamming signals such as Gaussian noise and amplitude modulation noise.