Applications of Electromagnetic Sensing Technologies in Complex Electromagnetic Environment

Electrical stimulation vs thermal effects in a complex electromagnetic environment

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.

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.

The battlefield environment that modern electronic information equipment faces during use is very complicated, which has become one of the main characteristics of the informationized battlefield. This article starts with the composition and characteristics of a complex electromagnetic environment, references relevant standards, introduces the definition and composition of a complex electromagnetic environment, and summarizes its characteristics. On this basis, this article introduces the general methods of complex electromagnetic environment tests, including digital simulation tests, semi-physical simulation tests, and full-physical simulation tests. Among them, in the full physical simulation test, an equivalent method is generally used to achieve it. At the same time, this article introduces test evaluation methods, including element-level evaluation and effectiveness-level evaluation. Combining engineering practice, this paper puts forward the difficulties of constructing a complex electromagnetic environment. It is an inevitable requirement for the development of weapons and equipment to carry out comprehensive experimental research on the complex electromagnetic environment of aircraft, and to be able to assess the combat capability of the product. It is also an objective requirement for the development trend of the information military.

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.

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.

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.

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.

Aiming at the requirements of multi-spectral transparency, electromagnetic (EM) shielding and radar stealth for window materials in visible-infrared (IR) integrated optoelectronic systems, this paper proposes a double-layer indium tin oxide (ITO) micro-nano structure metamaterial based on a ZnS substrate, which realizes the efficient coupling of "dual - spectral transparency - EM shielding - radar stealth". Through the periodic collaborative design of the bottom orthogonal grid network and the upper concentric square ring patches, while ensuring high transmittance in the visible light (380-780 nm) and IR (2-10 μm) bands, the EM shielding efficiency (SE) in the 100 MHz to 1 GHz frequency band is achieved to be more than 20 dB, and the absorption rate in the X-band (8-12 GHz) is more than 90%. Theoretical modeling and simulation reveal the composite action mechanism of "grid equivalent admittance shielding-resonant cavity energy dissipation", and magnetron sputtering and photolithography techniques are adopted to achieve millimeter-scale microstructure fabrication. Experimental results show that this metamaterial breaks through the balance limitations among light transmittance, SE, and radar stealth performance of traditional transparent shielding materials, providing an integrated solution for the protection of optoelectronic systems in complex EM environments.

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.

Publication in the conference proceedings of EUSIPCO, Glasgow, Scotland, 2009

The reviewer feels the author has succeeded, where many have failed, in writing a textbook for a course in detection and estimation theory. Derived from course notes, this text includes many of the peripheral structures which make a book suitable for classroom. Among them are numerous examples, over 120 pages of problems and a l2-page glossary of notation. The text is well referenced and is indexed by both subject and author.

Stretchable tunable frequency selective fabrics and their electromagnetic response mechanism