Electronic Warfare Research Articles

An ultrathin polymer-derived UHTCs coating on CFRP substrate: Effective electromagnetic wave absorber

The utilization of carbon fiber-reinforced polymer (CFRP) materials in electronic equipment encounters notable challenges of electronic warfare operations and the risk of detection by various sensors. A novel ceramic coating comprising TiC/SiOC with added Al2O3 adhesive was formulated to address these issues. The TiC/SiOC-50 wt% Al2O3 coating demonstrated exceptional microwave-effective absorption bandwidth (EAB) of 13.5 GHz, effectively covering the entire Ka-band, while maintaining a thin thickness of 0.60 mm. The TiC/SiOC-80 wt% Al2O3 system exhibited remarkable EM characteristics, including a minimum reflection loss (RLmin) of −58.26 dB, an EAB of 10.74 GHz, and an ultra-thin thickness of 0.38 mm, which sets a new record as the thinnest reported coating in the existing literature. The outstanding electromagnetic performance, coupled with their lightweight and thin characteristics, positions these coatings as highly viable solutions for various electromagnetic shielding and absorption applications in extreme environments.

Considerations, Advances, and Challenges Associated with the Use of Specific Emitter Identification in the Security of Internet of Things Deployments: A Survey

Initially introduced almost thirty years ago for the express purpose of providing electronic warfare systems the capabilities to detect, characterize, and identify radar emitters, Specific Emitter Identification (SEI) has recently received a lot of attention within the research community as a physical layer technique for securing Internet of Things (IoT) deployments. This attention is largely due to SEI’s demonstrated success in passively and uniquely identifying wireless emitters using traditional machine learning and the success of Deep Learning (DL) within the natural language processing and computer vision areas. SEI exploits distinct and unintentional features present within an emitter’s transmitted signals. These distinctive and unintentional features are attributed to slight manufacturing and assembly variations within and between the components, sub-systems, and systems comprising an emitter’s Radio Frequency (RF) front end. Although sufficient to facilitate SEI, these features do not hinder normal operations such as detection, channel estimation, timing, and demodulation. However, despite the plethora of SEI publications, it has remained largely a focus of academic endeavors, primarily focusing on proof-of-concept demonstration and little to no use in operational networks for various reasons. The focus of this survey is a review of SEI publications from the perspective of its use as a practical, effective, and usable IoT security mechanism; thus, we use IoT requirements and constraints (e.g., wireless standard, nature of their deployment) as a lens through which each reviewed paper is analyzed. Previous surveys have not taken such an approach and have only used IoT as motivation, a setting, or a context. In this survey, we consider operating conditions, SEI threats, SEI at scale, publicly available data sets, and SEI considerations that are dictated by the fact that it is to be employed by IoT devices or IoT infrastructure.

(Invited) Industrial Face of Nanotechnology

Ever since the proposal and demonstration of quantum dots in 1980 by Drs. A. Efros, Al. Efros and A. Ekimov, the relentless progress of nanotechnology has been unstoppable. And nowhere this progress is more evident than in the Si Very Large Scale Integrated Circuits (VLSI) and Thin Film Transistor (TFT) technologies. The minimum feature size of the Si VLSI with up to 2.6 trillion transistors on a chip was reduced to 3 nm in 2022 with plans for the 2 nm technology. TFTs fabricated on glass or even on cloth or paper enable integrated circuits with 50 nm tolerances over square meter sizes. These technologies have become disruptive with applications ranging from 5G and Beyond 5G communications to robotics, driverless cars, and electronic warfare. This talk will focus on the new counter-intuitive physics of ballistic transport required to support the design, characterization, and parameter extraction for nanoscale Si VLSI and TFT integrated circuits. Figure 1

Detection of OFDM modulations based on the characterization in the phase diagram domain

Signal modulation identification is of high interest for applications in military communications, but is not limited only to this specific field. Some possible applications are related to spectrum surveillance, electronic warfare, quality services, and cognitive radio. Distinguishing between multi-carrier signals, such as orthogonal frequency division multiplexing (OFDM) signals, and single-carrier signals is very important in several applications. Conventional methods face a stalemate in which the classification accuracy process is limited, and, therefore, new descriptors are needed to complement the existing methods. Another drawback is that some features cannot be extracted using conventional feature extraction techniques in practical OFDM systems. This paper introduces a new signal detection algorithm based on the phase diagram characterization. First, the proposed algorithm is described and implemented for simulated signals in MATLAB. Second, the algorithm performance is verified in an experimental scenario by using long-term evolution OFDM signals over a software-defined radio (SDR) frequency testbed. Our findings suggest that the algorithm provides good detection performance in realistic noisy environments.

Основные направления деятельности ООО «ТПК Элсервис» в части противодействия беспилотным воздушным судам

The article presents the main activities of TPK Elservice LLC in terms of expanding the tactical and technical characteristics of the previously developed small-sized means of radio reconnaissance and electronic warfare. A brief description of the radio reconnaissance automatic post is given. An automated complex for measuring the characteristics of log-periodic antennas is presented. Brief characteristics of the X-band radar – FMCW for solving the problems of detection and trajectory tracking of drones are given.

Role of Radar Cross Section Facilities, In a Radar and Electronic Warfare Defence Research and Evaluation Capability

This paper demonstrates the role of Radar Cross Section (RCS) facilities, consisting of modelling and simulation (M&S), Hardware in the Loop- (HWIL) and field Test and Evaluation (T&E) environments, in a Radar and Electronic Warfare (EW) Defence Research and Evaluation capability. The link between the development and utilisation of radar and EW facilities and the scientific process is illustrated by examples

The Development of the Real Time Target Simulator for the RF Signal of Electronic Warfare using VST and FPGA

In this paper, the target simulator for RF signals was developed by using VST(Vector Signal Transceiver) and set by real-time signal processing SW programs. A function to process RF signals using FPGA(Field Programmable Gate Array) board was designed. The system functions capable of data processing, raw signals monitoring, target signals(simulated range, velocity) generating and RF environments data analyzing were implemented. And the characteristics of modulated signal were analyzed in RF environment. All function of programs for processing RF signal have options to store signal data and to manage the data. The validity of the signal simulation was confirmed through verification of simulated signal results.

Joint Optimization of Jamming Type Selection and Power Control for Countering Multifunction Radar Based on Deep Reinforcement Learning

Developing intelligent jamming methods to combat the multi-function radar (MFR) has become a vital task in electronic warfare, because the MFR can tune into different working modes according to surrounding environment information. In this paper, we present a solution to the limitations of conventional jamming methods, including strong prior knowledge dependence and inaccurate selection strategies.Specifically, we study a joint optimization of jamming type selection and power control task (JO-JTSPC) for a general radar countermeasure scenario. In particular, we first model the sequential decision-making task JO-JTSPC as a Markov Decision Process (MDP). Subsequently, considering the differences in the designed action space, we accordingly develop two algorithms, i.e., dueling double deep Q-learning (D3QN) and hybrid proximal policy optimization (HPPO), to solve the optimization problem. Taking into consideration the threat level of various MFR working modes and the corresponding required jamming effect, we elaborately design the reward function of MDP as a weighted summation of the mode switching factor, jamming performance factor and jamming power factor. Further, the learned polices of these algorithms are derived based on the designed reinforcement learning (RL) elements. Extensive simulation results demonstrate that the proposed algorithms can learn highly adaptive polices in the radar countermeasure scenarios and achieve good jamming performance.

EW SYSTEMS MANAGEMENT. A CRITICAL REVIEW IN THE ACTUAL CONTEXT OF MULTIPLE CRISIS AND TURBULENCES

The paper refers to the management of electronic warfare systems and the latest approaches in this field. Also, some important main historical milestones and new development trends in the field of EW (Electronic Warfare) are being discussed. Finally, after identifying the relationship between ECM (electronic counter measures) and ES (electronic support) and the gaps in the current research of electronic warfare systems, it has been shown how is this domain influenced in the current context of multiple turbulences and crises

DSSS Signal Detection Based on CNN.

With the wide application of direct sequence spread spectrum (DSSS) signals, the comprehensive performance of DSSS communication systems has been continuously improved, making the electronic reconnaissance link in communication countermeasures more difficult. Electronic reconnaissance technology, as the fundamental means of modern electronic warfare, mainly includes signal detection, recognition, and parameter estimation. At present, research on DSSS detection algorithms is mostly based on the correlation characteristics of DSSS signals, and autocorrelation algorithm is the most mature and widely used method in practical engineering. With the continuous development of deep learning, deep-learning-based methods have gradually been introduced to replace traditional algorithms in the field of signal processing. This paper proposes a spread spectrum signal detection method based on convolutional neural network (CNN). Through experimental analysis, the detection performance of the CNN model proposed in this paper on DSSS signals in various situations has been compared and analyzed with traditional autocorrelation detection methods for different signal-to-noise ratios. The experiments verified the estimation performance of the model in this paper under different signal-to-noise ratios, different spreading code lengths, different spreading code types, and different modulation methods and compared it with the autocorrelation detection algorithm. It was found that the detection performance of the model in this paper was higher than that of the autocorrelation detection method, and the overall performance was improved by 4 dB.

Quantum Technologies and the Engineering of Josephson JunctionBased Sensors: Disruptive Innovation as a Strategic Differential for National Security and Defense

The so-called area of quantum technologies is a new and disruptive technological field, essentially from physics and engineering, with the ability to affect almost all human activities. They are based on the properties of quantum mechanics like quantum tunneling, quantum entanglement, and quantum superposition. Examples of areas of application of these emerging technologies are quantum computing, quantum communications, quantum sensing, quantum cryptography, quantum internet, quantum imaging, quantum metrology, quantum biology, among others. These technologies are of the interest of both the defense and security industry, and military and governmental actors. For military applications, and after a strong advanced engineering process, these technologies introduce new capabilities, improving effectiveness and increasing precision, thus leading to the so-called quantum warfare, wherein new military strategies, doctrines, policies, and ethics should be established. In particular, these military applications of quantum technologies can be described for various warfare domains like land, air, space, electronic, cyber, and underwater warfare and also for intelligence, surveillance, target acquisition and reconnaissance. Among those applications mentioned before, quantum computing is expected to have a number of important uses such as optimization and machine learning, associated to both artificial intelligence and blockchain. Quantum computers are perhaps best known for their expected ability to carry out Shor’s algorithm, which can be used to factorize large numbers and is an important process in the securing of data transmissions, essential for military applications. In this review of our own work, we show the physics and some of the applications of the Josephson junction which plays and important and essential role in the fabrication of quantum computers with superconducting qubits. Nowadays, applications of Josephson junction devices go from the most sensitive sensor to measure magnetic flux, called S.QU.I.D. (from Superconducting Quantum Interference Device) to the core of quantum computers, the quantum bits. The Josephson junction is an old quantum engine for a rising new world with incredible disruptive technological possibilities in engineering, especially in military applications where it plays a fundamental strategic differential for National Security and Defense.

Simulation of Cognitive Electronic Warfare System With Sine and Square Waves

Today’s Electronic Warfare (EW) receivers need advanced technology to achieve real-time surveillance operations. Dynamic and intelligent systems are required for UAVs and other airborne applications. The airborne Electronic Warfare systems must be knowledge-based systems, learning from the threat scenario with highly integrated capabilities to detect, react, and adapt to radar threats in real-time. Artificial intelligence is a machine-dependent process, by adapting certain rules and logic supported by human intelligence, AI can be used for cognitive processing. Cognitive signal processing is required for making the system autonomous and dynamic in nature. Military action on radar signatures requires a set of commands to be executed dynamically with the help of the proposed EW system. It is proposed to design and develop a cognitive EW architecture and simulation of machine learning that combines neural network architecture with the help of sine and square waves as input. This paper presents the Cognitive signal processing for EW systems with Neural Network, Recurrent Neural Network (RNN), Machine learning (ML), and Deep learning (DL) techniques with their simulation with sine and square waves.

Efficient waveform design with jamming characteristics for precision electronic warfare

The goal of precision electronic warfare (PREW) is to implement blanket jamming on the targets precisely and ensure that friendly devices are not affected; thus, it requires controlling energy precisely in the spatial domain and covering the working bandwidth of the target equipment in the frequency domain. In this paper, we propose the algorithms to design waveforms with jamming characteristics for PREW, where the frequency requirement is converted to mitigation on the autocorrelation peak sidelobe level (APSL) of the combined waveform in the time domain. Then, we establish two multiobjective problems (MOPs) based on one-step and two-step methods, which have their own advantages in practice; that is, the former performs better on the computational efficiency by obtaining the waveform directly, and the latter controls the energy better in the worst-case scenario by recovering the covariance matrix of the waveform. To solve the two MOPs, the ℓp-norm and a reasonable conversion are employed to approximate the highly nonconvex APSL terms, and the objective functions are transformed into quadratic terms within the majorization-minimization (MM) framework. An accelerating scheme is applied to expedite the proposed algorithms. Numerical examples demonstrate that the two proposed algorithms outperform the existing algorithms on the jamming performance and computational burden.

SMSP Mainlobe Jamming Suppression with FDA-MIMO Radar Based on FastICA Algorithm

In the electronic warfare environment, the performance of ground-based radar target search is seriously degraded due to the existence of smeared spectrum (SMSP) jamming. SMSP jamming is generated by the self-defense jammer on the platform, playing an important role in electronic warfare, making traditional radars based on linear frequency modulation (LFM) waveforms face great challenges in searching for targets. To solve this problem, an SMSP mainlobe jamming suppression method based on a frequency diverse array (FDA) multiple-input multiple-output (MIMO) radar is proposed. The proposed method first uses the maximum entropy algorithm to estimate the target angle and eliminate the interference signals from the sidelobe. Then, the range-angle dependence of the FDA-MIMO radar signal is utilized, and the blind source separation (BSS) algorithm is used to separate the mainlobe interference signal and the target signal, avoiding the impact of mainlobe interference on target search. The simulation verifies that the target echo signal can be effectively separated, the similarity coefficient can reach more than 90% and the detection probability of the radar is significantly enhanced at a low signal-to-noise ratio.

High-frequency electric field intensity measurement based on frequency shift with high gain and wide frequency range

For the safe operation of equipment and personal safety protection in high-voltage environments, the precise measurement of the high-frequency electric field is of paramount importance. Optical electric field sensor (OES) is a current research trend for high-frequency electric field measurement but is generally limited by low sensitivity and the need for high-speed acquisition modules. Here, we propose a high-frequency electric field intensity measurement approach based on frequency shift with a high gain and a wide frequency range. We used two different frequency shift methods, i.e., stimulated Brillouin scattering and down-conversion. Based on the former method, an amplification module is designed to enhance the OES signal with a frequency range from 11 GHz to 20 GHz and a noise-suppressed gain of up to 63 dB, and based on the latter one, the high-frequency OES signal is down-converted to a sub-MHz intermediate frequency signal. The frequency shift approach shows the potential to detect and analyze high-frequency electric fields with low cost and a small footprint, which is valuable for their applications in electronic warfare, high-voltage engineering, space exploration, etc.

RESEARCH OF AIMING SYSTEMS FOR MILITARY OBJECTS

The formation of electronic warfare is mutually conditioned by the dynamics of the struggle of means of attack and defense. Electronic combat, which is a form of operational and combat support, has become a new element of the content of operations and combat operations. One of the main directions of development of means, complexes and methods of electronic warfare is the improvement of the element base and technical solutions in the construction of electronic warfare equipment. Another direction is associated with a change in conceptual provisions associated with the creation and implementation of new technologies. For the successful solution of the problem, a brief overview of the currently existing and operating self-directed systems is given, their structure (transmitters) is considered, and the algorithm of the missile's approach to the target is considered. The structure of existing missiles and the requirements for its parts were considered. In comparison, missiles produced by different countries were analyzed. Various dispositions of electromagnetic waves are used in systems for missile control. Based on the ranges used, there are Radio-Technical, infrared, optical (laser) control systems. Also, the methods of aiming were considered: active, semiactive, passiv. Keywords: Self-directed head, aiming methods, launch of the rocket to the visible and invisible targets.

Research on Optical Spectrum Processing for Photonic-Assisted Broadband RF Cross- Eye Jamming System

Cross-eye jamming technology has been used in electronic warfare, which attempts to protect a military platform from monopulse tracking radars. The cross-eye jamming technology has the ability of inducing angular errors to the monopulse tracking radars by transmitting two jamming signals with equal amplitudes and opposite phases. At present, high operation frequency and broadband cross-eye jamming system has been rarely demonstrated. Therefore, the present cross-eye jamming systems are hard to jam frequency-agile radar or multi-band radar, whose carrier frequency covers a large spectral range. In this paper, a photonic-assisted broadband radio frequency (RF) cross-eye jamming system is proposed and experimentally demonstrated. To achieve effective jamming effect, the intercepted radar signal is modulated to optical carriers and the phase shift is realized by optical spectrum processing. The relationship between system parameter tolerances and jamming effects are also simulated. Furthermore, the RF transfer function of X-band, Ku-band and K-band has been obtained in the experiments. The experimental results show that the amplitude and phase mismatch are below 2.15 degrees and 0.4 dB, respectively. Calculated cross-eye gain is 39dB.

Binarization for time-frequency images of LPI radar signals based on K-means

Low probability of intercept radar signal is widely used because it is difficult to be intercepted by non-cooperative receivers in electronic warfare. We need to binarize the time-frequency images when analyzing LPI radar signals based on time-frequency distribution. However, the existing binarization algorithms cannot distinguish noise from the signal frequency at low signal-to-noise ratios. In this paper, we propose to use K-means algorithm to binarize the gray time-frequency images of LPI radar signals. We use F1-score to comprehensively consider the effect of binarization. Based on linear frequency modulation signals, the simulation experiments show that the F1-score of the proposed algorithm exceeds the F1-score of Otsu’s method by 40% to 80% when the signal-to-noise ratio is from -6 dB to 2 dB. The binarization effect of K-means is excellent and has great application prospects.

An 800-W Four-Level Supply Modulator for Efficient Envelope Tracking of RF Transmitters

Modern RF communication and electronic warfare applications require systems capable of amplifying signals with high bandwidths and high peak to average power ratios (PAPR). One technique used to meet these demands is supply modulation also known as envelope tracking where the drain voltage of the power amplifier (PA) is dynamically changed according to the signal envelope. The limiting factor with supply modulation is typically the efficiency and switching speed of the power converter. The power converter must also be capable of producing high power levels when supplying an array of PA units or a single high power transmitter. This paper demonstrates the design and characterization of a four-level discrete supply modulator with a peak output power of 800W operating at a maximum switching frequency of 10MHz. The modulator switches between four discrete voltages from 10 to 20V. GaN on silicon HEMT power transistors are selected for the switching devices after conducting a survey of commercially available silicon MOSFET, silicon-carbide MOSFET, and GaN on silicon power transistors. Trace interconnect models are developed to achieve accurate predictions of the time domain waveforms, including ringing at the switching edges. These interconnects are first analyzed using full-wave electromagnetic simulations, and then modeled with RLC networks suitable for time domain simulations. For a test signal with equal duty cycle between the four levels, an efficiency greater than 94.0% is demonstrated for average output powers exceeding 91.6W. When tracking the envelope of an 8MHz 64-QAM signal, an average efficiency of 93.5% is achieved providing a peak power of 800W.

Radar Jamming Decision-Making in Cognitive Electronic Warfare: A Review

With the increasingly complex electromagnetic environment and the intelligent development of radar, the jammer, as opposed to radar, urgently needs to improve its ability to recognize threat targets and make jamming decisions. In this paper, we first introduce the concepts and systems of cognitive electronic warfare (CEW) and summarize its research status. Through analysis of the existing CEW systems, we propose a CEW model suitable for the cluster confrontation scenarios. Then, for the radar jamming decision-making (RJDM) namely a crucial part of CEW, we discuss the advantages, disadvantages, and applications of the traditional methods and analyze the machine-learning based methods including Markov decision processing, the newest Q-Learning, Deep Q-Learning (DQN), Double Deep Q-Learning (DDQN), A3C algorithms, and their improved algorithms etc. We build radar adversarial models and verify the effectiveness of reinforcement learning (RL) algorithm and the superiority of deep RL by simulating both the underlying Q-Learning and DQN algorithms. Finally, the research trends of CEW are discussed.