Search Results (27)

In ultra-wideband (UWB) radio fuzes, the signal processing unit’s capability to rapidly and accurately extract target characteristics under battlefield conditions directly determines detonation precision and reliability. Escalating electronic warfare creates complex electromagnetic environments that compromise UWB fuze reliability through false alarms and missed detections. This study pioneers a novel signal processing architecture. The framework integrates: (1) fixed-parameter Least Mean Squares (LMS) front-end filtering for interference suppression; (2) One-Dimensional Convnlutional Neural Network (1D-CNN) recognition trained on One-Dimensional Conditional Generative Adversarial Network (1D-CGAN)-augmented datasets. Validated on test samples, the system achieves 0% false alarm/miss detection rates and 97.66% segment recognition accuracy—representing a 5.32% improvement over the baseline 1D-CNN model trained solely on original data. This breakthrough resolves energy-threshold detection’s critical vulnerability to deliberate jamming while establishing a new technical framework for UWB fuze operation in contested spectra. Full article

In order to solve the dynamic adaptation problem of the working frequency band of the FSS in the complex electromagnetic environment and further expand the frequency tuning range, a reconfigurable AFSS unit model based on PIN and varactor diodes are designed, which can achieve the insertion loss below−1 dB in the wide frequency range of 10.2–15.2 GHz, meet the working-band switching, and allow for flexibly adjusting the working frequency point. In order to verify the accuracy of the design method, a square-ring aperture and notched patch-coupling structure that can exhibit broadband transmission response in the X-Ku band is first proposed based on the equivalent circuit model topology. A numerical simulation and a processing test of the structure are carried out. The measured data are in good agreement with the simulation results. After optimizing the unit structure, different capacitance values and resistance values are added to the diodes in the numerical simulation to control the equivalent PIN diode switch and the capacitance change in the varactor diodes. According to the equivalent circuit model and the electric-field intensity distribution, the AFSS regulation mechanism of the loaded diodes is explored. In this paper, through numerical simulation optimizations and experimental verification, the design method and performance optimization strategy of frequency-tunable FSS in the working range of 2–18 GHz are systematically studied, which provides theoretical support for the design of electromagnetic functional devices in the new generation of communication, radar, and electronic warfare systems. Full article

Secure communication for critical command nodes has emerged as a pivotal challenge in modern warfare, in particular considering the vulnerability of these nodes to electronic reconnaissance. To cope with the severe interference, this paper proposes a robust solution for long-distance secure command and control system leveraging phase-modulated microwave photonic links. Studies that analyze the impairing nonlinear distortions and phase noise stemming from different sources in optical phase demodulation during long-haul transmission has been carried out, unveiling their impairment in coherent transmission systems. To overcome these limitations, a linearized phase demodulation and noise suppression technique based on composite optical phase-locked loop and multi-core fiber is proposed and experimentally validated. Experimental results demonstrate a long-haul transmission over 100 km with an 81 dB suppression for third-order intermodulation distortion and a 27 dB improvement in noise floor at 5 MHz under closed-loop condition, verifying a significant enhancement in the fidelity in long-distance transmission. This method ensures a highly reliable secure communication for command and control systems in contested electromagnetic environments. Full article

Satellite communications are pivotal to global Internet access, connectivity, and the advancement of information warfare. Despite these importance, the open nature of satellite channels makes them vulnerable to eavesdropping, making the enhancement of interception resistance in satellite communications a critical issue in both academic and industrial circles. Within the realm of satellite communications, polarization modulation and quadrature techniques are essential for information transmission and interference suppression. To boost electromagnetic countermeasures in complex battlefield scenarios, this paper integrates multi-parameter weighted-type fractional Fourier transform (MP-WFRFT) with directional modulation (DM) algorithms, building upon polarization techniques. Initially, the operational mechanisms of the polarization-amplitude-phase modulation (PAPM), MP-WFRFT, and DM algorithms are elucidated. Secondly, it introduces a novel variable polarization-amplitude-phase modulation (VPAPM) scheme that integrates variable polarization with amplitude-phase modulation. Subsequently, leveraging the VPAPM modulation scheme, an exploration of the anti-interception capabilities of MP-WFRFT through parameter adjustment is presented. Rooted in an in-depth analysis of simulation data, the anti-scanning capabilities of MP-WFRFT are assessed in terms of scale vectors in the horizontal and vertical direction. Finally, exploiting the potential of the robust anti-scanning capabilities of MP-WFRFT and the directional property of antenna arrays in DM, the paper proposes a secure transmission technique employing directional variable polarization modulation with MP-WFRFT. The performance simulation analysis demonstrates that the integration of MP-WFRFT and DM significantly outperforms individual secure transmission methods, improving anti-interception performance by at least an order of magnitude at signal-to-noise ratios above 10 dB. Consequently, this approach exhibits considerable potential and engineering significance for its application within satellite communication systems. Full article

Battlefields contain complex networks of electromagnetic (EM) systems, owned by adversary/allied military forces and civilians, communicating intentionally or unintentionally. Attacker’s strategies may include Intentional EM Interference (IEMI) to adversary target systems, although transmitted signals may additionally degrade/disrupt allied/civilian systems (called victims). To aid decision-making processes relating to IEMI attacks, Risk Assessment (RA) is performed to determine whether interference risks to allied/civilian systems are acceptable. Currently, there is no formalized Quantitative RA Method (QRAM) capable of calculating victim risk distributions, so a novel approach is proposed to address this knowledge gap, utilizing an Electromagnetic Warfare (EW) IEMI RA method modeling scenarios consisting of interacting EM systems within complex, dynamic, diverse, and uncertain environments, using Systems-of-Systems (SoS) theory. This paper aims to address this knowledge gap via critical analysis utilizing a case study which demonstrates the use of an Acknowledged SoS-based model as input to a QRAM capable of calculating victim risk distributions within EW IEMI RA-associated scenarios. Transmitter operators possess only uncertain/fuzzy knowledge of victim systems, so it is proposed that a Moot Acknowledged System-of-Fuzzy-Systems applies to EW IEMI RA scenarios. In summary, a novel SoS description feeding a novel QRAM (supported by a systematic literature review of RA mathematical modeling techniques)is proposed to address the knowledge gap. Full article

In modern warfare, the advancement of low detectable technology has made the reduction of an aircraft radar cross section (RCS) crucial for survivability, while engine inlets significantly impact the overall detectability index as major forward scattering sources. Inspired by radar absorbing structures (RASs) based on metasurface theory, as well as the spoof surface plasmon polariton (SSPP) theory, this paper proposes a comprehensive design of radar absorbing grilles (RAGs) which are installed at the inlet aperture of the aircraft intake, where RAGs allow airflow to cross through and absorb the detecting radar wave. To enhance the ability of electromagnetic wave attenuation, an indium tin oxide (ITO) film is added in the middle of the RAGs to change the impedance characteristics. This study clarifies the mechanism influencing radar wave absorption characteristics through design parameters (unit length and sheet resistance) and radar characteristic parameters (frequency, incident angle, and polarization mode). The absorption peak gradually shifts towards lower frequencies with the increase in unit length from 8 to 16 mm of the grille. The integrated average absorption first increases and then decreases with the increase in sheet resistance from 100 to $800 \Omega /\square$ applied as ITO film in the middle of the grille. When the unit length of RAG is 12 mm and $400 \Omega /\square$, the sheet resistance is applied, and a 90% absorption bandwidth is achieved to 100% within the 8–18 GHz band. The 90% absorption bandwidth reaches 72.3% in the 2–18 GHz band while maintaining absorption above 40% in the 2–8 GHz band. The integrated average absorption reaches 0.887, and the 90% absorption bandwidth increases to 255.6% of the original model’s bandwidth. The results indicate that the proposed RAGs based on metasurface exhibit broadband absorption performance and high angular stability, providing technical support for further application of these grilles in aircraft engine inlets. Full article

The importance of information gathering is emphasized to minimize casualties and economic losses in warfare. Through electronic warfare, which utilizes electromagnetic waves, it is possible to discern the enemy’s intentions and respond accordingly, thereby leading the battle advantageously. Consequently, related research is actively underway. The development of various radar signal modulation techniques has revealed limitations in the existing modulation recognition methods, necessitating the development of distinguishing features to overcome these limitations. This paper proposes and analyzes distinguishing features that can differentiate various modulation schemes. Eleven distinguishing features were employed, and twenty-two types of modulated signals, including analog, digital, and composite modulation, were classified using hierarchical classification approach and maximum likelihood estimation (MLE). The proposed method achieves a recognition performance of 99.76% at an SNR of 20 dB and 98.45% at an SNR of 8 dB. Full article

The increasingly complex electromagnetic environment of modern warfare and the proliferation of intelligent jamming threaten to reduce the survival rate of radio fuzes on the battlefield. Radio frequency (RF) stealth technology can fundamentally improve the anti-interception and reconnaissance capabilities of radio fuzes, thereby lessening the probability of them being intercepted, recognized, and jammed by the enemy. In this paper, an RF stealth waveform based on chaotic pulse-position modulation is proposed for ultra-wideband (UWB) radio fuzes. Adding a perturbation signal based on the Tent map ensures that the chaotic sequences have sufficiently long periods despite hardware byte limitations. Measuring the approximate entropy and sequence period shows that the Tent map with the addition of perturbation signals can maintain good randomness under byte constraints, closely approximating the Tent map with ideal precision. Simulations verify that the proposed chaotic mapping used to modulate the pulse position of an ultra-wideband radio fuze signal results in superior detection, anti-interception, and anti-jamming performance. Full article

Advances in radar technology have driven efforts to develop effective countermeasures. Plasma is recognized as a highly effective medium for absorbing electromagnetic waves. Recent research has focused on enhancing plasma element performance. This paper achieved ultra-high-density, low-pressure cold plasma with a density of 1.15 × 10¹² cm⁻³, surpassing similar studies by more than an order of magnitude. Tungsten electrodes with high-curvature spiked structures were invented to replace traditional iron–nickel alloy electrodes, increasing plasma density by 88.2% under the same conditions. Lightweight and cost-effective tubular and annular ultra-high-density, low-pressure cold plasma devices were developed, demonstrating exceptional performance in electromagnetic wave absorption, plasma transient antennas, and radar stealth technology. The influence of plasma on electromagnetic waves and its numerical relationship were analyzed. By measuring the radar cross-section (RCS), the reduction in radar detection rates was quantified. The results show that the ultra-high-density cold plasma devices exhibit very low intrinsic RCS values, suitable for plasma antenna applications. The array of plasma elements generates a large-area high-density low-pressure cold plasma. This plasma effectively reduces the radar cross-section (RCS) of metallic equipment in the S and C bands and shows attenuation in the X band. These effects highlight the superior characteristics of plasma technology in electronic warfare. This exploratory research lays the groundwork for further defense applications. Full article

With the development of electronic warfare technology, the intelligent jammer dramatically reduces the performance of traditional radar anti-jamming methods. A key issue is how to actively adapt radar to complex electromagnetic environments and design anti-jamming strategies to deal with intelligent jammers. The space of the electromagnetic environment is dynamically changing, and the transmitting power of the jammer and frequency diversity array (FDA) radar in each frequency band is continuously adjustable. Both can learn the optimal strategy by interacting with the electromagnetic environment. Considering that the competition between the FDA radar and the jammer is a confrontation process of two agents, we find the optimal power allocation strategy for both sides by using the multi-agent deep deterministic policy gradient (MADDPG) algorithm based on multi-agent reinforcement learning (MARL). Finally, the simulation results show that the power allocation strategy of the FDA radar and the jammer can converge and effectively improve the performance of the FDA radar and the jammer in the intelligent countermeasure environment. Full article

In modern warfare, frequency-hopping communication serves as the primary method for battlefield information transmission, with its significance continuously growing. Fighting for the control of electromagnetic power on the battlefield has become an important factor affecting the outcome of war. As communication electronic warfare evolves, jammers employing deep neural networks (DNNs) to decode frequency-hopping communication parameters for smart jamming pose a significant threat to communicators. This paper proposes a method to generate adversarial samples of frequency-hopping communication signals using adaptive whitening and feature gradient smoothing. This method targets the DNN cognitive link of the jammer, aiming to reduce modulation recognition accuracy and counteract smart interference. First, the frequency-hopping signal is adaptively whitened. Subsequently, rich spatiotemporal features are extracted from the hidden layer after inputting the signal into the deep neural network model for gradient calculation. The signal’s average feature gradient replaces the single-point gradient for iteration, enhancing anti-disturbance capabilities. Simulation results show that, compared with the existing gradient symbol attack algorithm, the attack success rate and migration rate of the adversarial samples generated by this method are greatly improved in both white box and black box scenarios. Full article

Poly(styrene-methyl methacrylate-acrylic acid) photonic crystals (PCs), with five different sizes (170, 190, 210, 230 and 250 nm), were applied onto three plain fabrics, namely polyamide, polyester and cotton. The PC-coated fabrics were analyzed using scanning electronic microscopy and two UV/Vis reflectance spectrophotometric techniques (integrating sphere and scatterometry) to evaluate the PCs’ self-assembly along with the obtained spectral and colors characteristics. Results showed that surface roughness of the fabrics had a major influence on the color produced by PCs. Polyamide-coated fabrics were the only samples having an iridescent effect, producing more vivid and brilliant colors than polyester and cotton samples. It was observed that as the angle of incident light increases, a hypsochromic shift in the reflection peak occurs along with the formation of new reflection peaks. Furthermore, color behavior simulations were performed with an illuminant A light source on polyamide samples. The illuminant A simulation showed greener and yellower structural colors than those illuminated with D50. The polyester and cotton samples were analyzed using scatterometry to check for iridescence, which was unseen upon ocular inspection and then proven to be present in these samples. This work allowed a better comprehension of how structural colors and their iridescence are affected by the textile substrate morphology and fiber type. Full article

In the field of electronic communication warfare, accurately predicting the range and intensity of shortwave interference signals presents a significant challenge due to the complex interplay between the ionospheric parameters and the electromagnetic environment. To address this challenge, we designed a novel tool to assess the interference impact area of shortwave interference signals in a dynamically changing ionospheric environment. Considering sophisticated ionospheric radio wave propagation models and innovative spatial grid methods, this tool finishes the comprehensive spatial distribution of the interference impact area and delivers grid-based insights into the interference intensity. Furthermore, the test verification of the tool demonstrated a mean error of 8.42 dB between the measured and simulated results, underscoring the efficacy and reliability of this tool. This pioneering work is poised to make substantial contributions to the field of communication electronic warfare and holds significant promise for guiding the development of interference countermeasures. Full article

In an electronic jamming system, the ability to adequately perceive information determines the effectiveness of an electronic countermeasures strategy. This paper proposes a new method based on the combination of a multi-agent electronic jammer and an information sharing mechanism. With the development of intelligent technology and deep learning, these technologies have been applied in electronic countermeasure game systems. Introducing intelligent technology into the electronic confrontation system can greatly improve decision-making efficiency. At the same time, a multi-agent electronic countermeasure cooperative system based on the information sharing method can break through the limited information perception capabilities of a single agent, thereby greatly improving the survivability of jamming systems in electronic warfare. Experimental results show that our method requires a lower jamming-to-signal ratio than the single jammer method to achieve effective electronic jamming. In addition, the electronic jamming parameters can be updated automatically as the external electromagnetic environment changes quickly, realizing a more intelligent electronic jamming system. Full article

In recent years, radar emitter signal identification has been greatly developed via the utilization of deep learning and has achieved significant improvements in identification accuracy. However, with the continuous emergence of complex regime radars and the increasing complexity of the electromagnetic environment, some new kinds of radar emitter signals collected are not in sufficient quantities to satisfy the demand of deep learning. As a result, in this paper, we adopted the prototypical network (PN) belonging to metric-based meta-learning to realize few-shot radar emitter signal recognition with the aim of meeting the needs of modern electronic warfare. Additionally, considering the problems that may arise in the field of few-shot radar emitter signal recognition, such as discriminative location bias caused by a small number of base classes or the large difference between base classes and novel classes, we proposed an attention-balanced strategy to improve meta-learning. Specifically, each channel in the feature map is forced to make the same contribution in the distinguishment of different classes. In addition, for PN, taking into account that the feature vectors of each support sample in the class are different, we set a network to exploit the relation between each support sample in the same classes, and weighted each feature vector of the support samples according to the relation. Large quantities of experiments indicate that our algorithm possesses more advantages than other algorithms. Full article