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Microwave absorbing materials play an increasingly important role in modern electronic warfare technology for enhancing electromagnetic compatibility and suppressing electromagnetic interference. High‐entropy ceramics (HECs) possess extraordinary physical and chemical properties, and more importantly, the high tunability of multi‐component HECs has brought new opportunities to microwave absorbing materials. Rich crystallographic distortions and multi‐component occupancies enable HECs to have highly efficient microwave absorption properties, excellent mechanical properties, and thermal stability. Therefore, the structural advantages of HECs are integrated from comprehensive perspectives, emphasizing on the role of dielectric and magnetic properties in the absorption phenomenon. Strategies are proposed to improve the microwave absorption capacity of HECs, including composition optimization, microstructure engineering, and post‐treatment technology. Finally, the problems and obstacles associated with high‐entropy materials (HEMs) research are discussed. The innovative design concepts of high‐entropy microwave absorbing ceramics are highlighted. [ABSTRACT FROM AUTHOR]

It is our great pleasure to present you with this IET Radar, Sonar and Navigation special issue on "Electronic Attack and Protection for Modern Radar Systems and Radar Networks". The recent development of fast digital to analogue converters (DACs) and analogue to digital converters (ADCs), field programmable gate arrays (FPGAs) and parallel computing has contributed to the development of modern radars that, at the same time, can also be more easily attacked using digital radio frequency memories (DRFMs). The development of passive and netted multiband, multistatic, multichannel radars has also changed the EW scenario significantly. Classical EA can be less effective against passive, multistatic and multichannel radars and, as a result, new methods and new technologies have to be developed for effective countermeasures. Multichannel and multistatic jammers have also started to play a role in the EW scene. The aim of this special issue was to gather some of the most recent work in this area. The result is a collection of 12 interesting and timely papers aiming to address current technical challenges in electronic warfare. The papers included in this collection covers areas around the more general electronic warfare context as well as address specific challenges of electronic attack and electronic protection as summarised below. [ABSTRACT FROM AUTHOR]

In modern electronic warfare, multi‐function radar work mode recognition is increasingly crucial. However, the challenges posed by complex electromagnetic environments, such as lost pulses, spurious pulses, and measurement errors, along with the reliance of traditional multi‐task learning strategies on clean samples, make it difficult for existing algorithms to achieve satisfactory recognition performance in real‐world scenarios. To address these issues, this paper introduces a novel residual shrinkage reconstruction recurrent neural network (RS‐RRNN). The network uses a Gated Recurrent Unit as its backbone to extract temporal features and enhances feature extraction by reconstructing the GRU's input, while also reducing dependence on clean samples. These features are then processed through a residual shrinkage structure to reduce noise, which significantly improves the model's robustness in non‐ideal scenarios. Simulations demonstrate that RS‐RNN has better performances in accuracy and robustness than existing networks. [ABSTRACT FROM AUTHOR]

Spot jamming poses a significant threat to radar detection due to its ability to rapidly intercept radar signals and emit high‐power interference. A novel Cognitive Multi‐Carrier Radar (CMCR) is proposed, which utilises a detection waveform comprising multiple narrow bands to reduce the disruption from the spot jammer. Additionally, it can analyse the target's Radar Cross‐Section (RCS) characteristics and proactively select frequencies with high RCS for detection, thereby enhancing target detection capability. The online frequency allocation problem of CMCR is a Multi‐Armed Bandit (MAB) problem with a combinatorial action space. To tackle the challenge from the huge action space, an efficient aDaptive Accept Reject (DART) method is employed, which significantly reduces the regret of CMCR in the detection task. Moreover, a slide‐window change point indicator is proposed to monitor the change of target's RCS, which enables CMCR to be applicable in scenarios where target's RCS varies. Finally, the effectiveness and robustness of CMCR are through extensive numerical experiments. [ABSTRACT FROM AUTHOR]

Jammers aim to interfere with active radars during military operations. Still, they can strengthen our capabilities on the battlefield if there are proper methods to use them. This paper demonstrates the possibility of utilising a ground‐based barrage jammer (to jam radars or communications) as an illumination source for passive radar detection, tracking and inverse synthetic aperture radar (ISAR) imaging. It shows the feasibility of using a jammer for cooperative (friendly jammer) and non‐cooperative (hostile jammer) operations. The results come from the European Defence Agency project no B 1516 IAP2 GP entitled jammer‐based passive radar. This article will present some of the outcomes of field trials conducted in June 2022 in Poland within the international electronic warfare exercises. Designed jammer demonstrators, with a maximum bandwidth of 115 MHz, were used as illuminators of opportunity and made it possible to test the operation of passive radars with five signal types (within two bands—L‐band and S‐band) for military targets (i.e. fighters, transport planes, helicopters). In the first part of the article, detection, ISAR imaging and tracking issues will be addressed. The second part of the article will focus on the results obtained during the project's joint field trials. [ABSTRACT FROM AUTHOR]

Active‐passive composite monopulse radar (APCMR) enhances the anti‐jamming capability by combing the advantages of active radars and passive radars. Previous studies have discussed the effectiveness of cross‐eye jamming against APCMR in a simplified scenario for isolating platform echo. In this paper, platform echo and cross‐eye jamming signals are jointly considered to analyse the jamming performance on APCMR. A mathematical model of the cross‐eye jamming against APCMR is established in the presence of the platform echo, and the jamming performance on active radar and passive radar is evaluated and compared in terms of cross‐eye gain and its probability. In order to ensure the jamming performance on both active and passive radars, a guideline for the setting of jammer parameters is proposed based on numerical simulations. The study can provide theoretical foundation for the design and application of cross‐eye jammers. [ABSTRACT FROM AUTHOR]

The analysis of the Armed Forces (AF) operational capabilities requires the construction of a formal model. Elements of this model will be presented here. Including selected aspects of Electronic Warfare (EW) in an operational capability assessment model is an important and difficult task. The essence of the impact of radio‐electronic, like other forms of cyber warfare, on reconnaissance, command and communications systems is to hinder or prevent kinetic operations. The model should identify and prioritise the required capabilities by defining the key objectives: identification of the future security environment and within it the operational environment, identification of planning scenarios and requirements for future forces, including forces to execute EW, identification of specific tasks in relation to AF missions and tasks, Identification of the list of AF required capabilities in the AF capability catalogue. The idea of identifying required capabilities and identifying gaps is presented in this chapter. The key questions/problems posed in the analysis process are: Do the identified capabilities fit with the mission and operational concepts and threats? What are the indicators for achieving the desired operational capabilities? What might be the cost of providing the AF with the required capabilities? What is the key approach to address these issues? An operational capability approach to planning is used, including the identification of the AF' reference modules, including EW units. Dimensioning of operational capabilities using formal and simulation methods is an important problem. An optimisation model is presented for determining the structure of the AF, based on reference modules with desired capabilities, enabling the realisation of identified operational concepts, taking into account the following criteria: operational and cost. The analysis proposes custom simulation models, based on mathematical models of the AF. The simulation is based on a step‐by‐step analysis with an introduced scenario and possible enemy structure and defined mission. A way of modifying the assessment of the parties' potentials as a result of the EW impact is presented. This has implications for the allocation of reference units in the formation of own forces in response to the enemy's potential formation and action. [ABSTRACT FROM AUTHOR]

The authors analyse the sequential lobing radar (SLR) resistance against the scan rate modulation (SRM) jamming technique. Unlike previous studies, the authors analyse SLRs with sinc antenna patterns, enabling investigation of the sidelobe region's vulnerability. By incorporating second‐order angular tracking loops (SOATLs), the first analysis of break‐lock probability for SLRs under SRM jamming is introduced. The analysis reveals the influence of SOATL parameters (damping ratio and natural frequency) on both angular root‐mean‐square‐error at low jamming‐to‐signal‐ratio (JSR) region and break‐lock probability at high JSR region. Additionally, the impact of squint angle on SLR resistance to SRM jamming is examined. Furthermore, the optimal duty cycle as a function of JSR, which maximises break‐lock probability is presented. Significantly, the theoretical results support the 20 dB JSR requirement for SRM effectiveness, often cited experimentally in literature, and extend the theoretical analysis of the SRM technique carried out for the main lobe region of SLRs. This finding bridges the gap between theoretical analysis and practical observations. [ABSTRACT FROM AUTHOR]

Modern radar systems are critical infrastructure in defence and civilian applications. In the defence domain, modern radars operate in a highly contested, congested, and constrained electromagnetic environment. In the context of operating in this challenging environment, the challenges across the system life cycle are examined in testing modern radar systems which are characterised by advanced features, such as multi‐function capability, advanced digital signal processing, high resolution, wideband, and frequency agile systems that incorporate phase array and active electronically scanned array capabilities. The challenges and key objectives in testing these sophisticated modern radar systems are highlighted, as well as the enabling technologies that can support Test & Evaluation of such systems. An architecture for Hardware‐in‐the‐Loop testing, which leverages modular and flexible commercial‐of‐the‐shelf hardware, is proposed together with an application software that allows the testing of radar with a radar target generator. [ABSTRACT FROM AUTHOR]

Accurate work state recognition of multifunction radar (MFR) is crucial in electronic warfare, as it helps understand the enemy's intention and evaluate potential threats. A pulse‐level work state recognition method of MFR based on the residual block with spatial attention connected gated recurrent unit by features using metric coding and correlative embedding (MC‐RSG) is proposed. Metric coding is designed to generate the distance vector with time of arrival, and the correlative embedding is performed on the distance vector and raw data features to increase the feature information by extracting feature information associated with the previous and subsequent pulses in each feature sequence, respectively. Besides, we make use of the model called RSG containing the residual block with spatial attention connected gated recurrent unit to learn the features of pulse sequences and identify the radar work state label of each pulse. The experimental work shows that the method is robust and has achieved up to 97% recognition accuracy on the test dataset under ideal observation conditions and 5% higher than the comparison network in high noise observation conditions. [ABSTRACT FROM AUTHOR]

The interrupted‐sampling repeater jamming (ISRJ) is an effective kind of intro‐pulse coherent jamming based on digital radio frequency memory. It appears as a group of false targets that are difficult to distinguish on the range profile after pulse compression, which seriously affects the target identification and tracking. According to the coherence between ISRJ and real target echo and the waveform discontinuity caused by intermittent interception, a new method is proposed for ISRJ parameter estimation and jamming suppression based on block sparse recovery. To ensure the effectiveness of sparse recovery, the transmitted signal is divided into several random phase‐encoded sub‐pulses. Firstly, the pulse‐number and time‐delay of the received echo are estimated by block orthogonal matching pursuit. Then, the jamming slices are identified based on the sampling duty ratio and the Doppler frequency is estimated through matching. Finally, according to the parameter estimation results, the jamming slices are reconstructed to eliminate ISRJ. Numerical experiments in two typical scenarios have shown that this method can effectively suppress ISRJ. Especially in the scenario of high jamming duty ratio, this method exhibits good anti‐jamming performance. [ABSTRACT FROM AUTHOR]

The jamming in electronic warfare environment significantly degrades the performance of the radar system, especially the mainlobe jamming. The distributed array radar can suppress the mainlobe jamming by increasing the array aperture with auxiliary arrays. However, when the aperture of an auxiliary array is smaller than that of the main array, it results in residual jamming in auxiliary arrays after beamforming and affects the performance of the radar system. To tackle this issue, a mainlobe and sidelobe jamming joint suppression method with eigen‐projection matrix processing (EMP) and null constraints is proposed. In the proposed method, firstly, the adaptive beamforming with EMP is performed in main and auxiliary arrays to suppress the sidelobe jamming with mainlobe maintenance. Then, the null constraints based on the Capon spectrum of main array are applied to suppress the residual jamming in auxiliary arrays. Finally, the minimum mean square error (MMSE) beamforming is utilised to cancel the mainlobe jamming. Simulation results demonstrate the jamming suppression performance of the proposed method. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Radar emitter signal deinterleaving based on pulse description words (PDWs) is a challenging task in the field of electronic warfare because of the parameter sparsity and uncertainty of PDWs. In this paper, a modulation-hypothesis-augmented Transformer model is proposed to identify emitters from a single PDW with an end-to-end manner. Firstly, the pulse features are enriched by the modulation hypothesis mechanism to generate I/Q complex signals from PDWs. Secondly, a multiple-parameter embedding method is proposed to expand the signal discriminative features and to enhance the identification capability of emitters. Moreover, a novel Transformer deep learning model, named PulseFormer and composed of spectral convolution, multi-layer perceptron, and self-attention based basic blocks, is proposed for discriminative feature extraction, emitter identification, and signal deinterleaving. Experimental results on synthesized PDW dataset show that the proposed method performs better on emitter signal deinterleaving in complex environments without relying on the pulse repetition interval (PRI). Compared with other deep learning methods, the PulseFormer performs better in noisy environments. [ABSTRACT FROM AUTHOR]

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Forward jammers replicate and retransmit radar signals back to generate coherent jamming signals and false targets, making anti-jamming an urgent issue in electronic warfare. Jamming transmitters work at saturation to maximize the retransmission power such that only the phase information of the angular waveform at the designated direction of arrival (DOA) is retained. Therefore, amplitude modulation of MIMO radar angular waveforms offers an advantage in combating forward jamming. We address both the design of unimodular MIMO waveforms and their associated mismatch filters to confront mainlobe jamming in this paper. Firstly, we design the MIMO waveforms to maximize the discrepancy between the retransmitted jamming and the spatially synthesized radar signal. We formulate the problem as unconstrained non-linear optimization and solve it using the conjugate gradient method. Particularly, we introduce fast Fourier transform (FFT) to accelerate the numeric calculation of both the objection function and its gradient. Secondly, we design a mismatch filter to further suppress the filtered jamming through convex optimization in polynomial time. The simulation results show that for an eight-element MIMO radar, we are able to reduce the correlation between the angular waveform and saturated forward jamming to −6.8 dB. Exploiting this difference, the mismatch filter can suppress the jamming peak by 19 dB at the cost of an SNR loss of less than 2 dB. [ABSTRACT FROM AUTHOR]

Based on the principle of spatial power combination of sparse array time reversed signals, the relationship of distances between constructive interference points to cross angle of beams and viewing angles has been analyzed. Then the formulas of distances between adjacent constructive points at 360-degree views are derived. Considering that the distance between constructive interference points around target is frequently needed to be less than target's antenna size, The variation law of the view range with beam crossover angle has been simulated and analyzed with MATLAB when the above conditions are met at the same frequency and without errors. On this basis, array deployment recommendations are summed up. In addition, the effects of the received time window length and the difference of the distance between each array element and the target point on the synthesized power have been analyzed. Finally, the spatial power combination simulation experiments of the sparse array time-reversed signal have been carried out. The experimental results show that the methods and conclusions of this paper can provide theoretical basis and reference for the research and application of sparse array power combination technology in long-range wireless energy delivery, high-power microwave weapons, electronic warfare, etc. [ABSTRACT FROM AUTHOR]

The ionospheric F2 critical frequency (foF2) is one of the most crucial application parameters in high-frequency communication, detection, and electronic warfare. To improve the accuracy of spatial reconstruction of the ionospheric foF2, we propose a high-accuracy surface (HAS) modeling method. This method converts difficult-to-solve differential equations into more manageable algebraic equations using direct difference approximation, significantly reducing algorithm complexity and computational load while exhibiting excellent convergence properties. We used seven stations in Brisbane, Canberra, Darwin, Hobart, Learmonth, Perth, and Townsville, with one station as a validation station and six as training stations (e.g., Brisbane as a validation station and the other stations—Canberra, Darwin, Hobart, Learmonth, Perth, and Townsville—as training stations). The training stations and the HAS method were used to train and reconstruct the validation stations at different solar activity periods, seasons, and local times. The predicted values of the validation stations were compared with the measured values, and the proposed method was analyzed and validated. The reconstruction results show the following. (1) The relative root mean square errors (RRMSEs) of HAS method prediction in different solar activity epochs were 13.67%, 7.74%, and 9.19%, respectively, which are 13.57%, 7.41%, and 6.41% higher than the prediction accuracy of the Kriging method, respectively. (2) In the four seasons, the RRMSEs of the HAS method prediction are 9.27%, 13.1%, 8.81%, and 8.09%, respectively, which are 10.83%, 11.73%, 4.25%, and 12.00% higher than the prediction accuracy of the Kriging method. (c) During the daytime and nighttime, the RRMSEs of HAS method prediction were 9.23% and 11.17%, which were 5.92% and 11.99% higher than the prediction accuracy of the Kriging method, respectively. (d) Under the validation dataset, the average predictive RRMSE of the HAS method was 10.29%, and the average predictive RRMSE of the IRI prediction model was 12.35%, with a 2.06% improvement in the predictive accuracy of the HAS method. In general, the prediction effect of the HAS method was better than that of the Kriging method, thus verifying the effectiveness and reliability of the proposed method. In summary, the proposed reconstruction method is of great significance for improving usable frequency prediction and enhancing communication performance. [ABSTRACT FROM AUTHOR]

Aimed at the problems of optical frequency combs, such as their large number of comb lines, their high flatness, and their lack of ease in generating, as well as the fact that the channelization efficiency of the scheme based on optical frequency combs is low, we proposed a microwave photonic channelization receiver based on signal polarization multiplexing. Using two-line local optical frequency combs with different frequencies to demodulate the RF signal in the orthogonal polarization state, 16 sub-channels with a bandwidth of 1 GHz can be received simultaneously. The experimental results show that the image rejection ratio can reach 28 dB, and the third-order spurious-free dynamic range of the system can reach 96.8 dB·Hz2∕3. This scheme has the advantages of a large number of sub-channels and a high channelization efficiency; it has great application potential in broadband wireless communication, radar, and electronic warfare systems. [ABSTRACT FROM AUTHOR]

In this article a compact sinusoidal tapered slot Vivaldi linear antenna array is designed for X and Ku band applications is presented. Printed Vivaldi antennas are extensively used for broadband applications because it gives high gain and broad bandwidth. The proposed antenna consists of two circular stubs, one rectangular slot and sinusoidal tapered lines on both sides of the antenna structure. These two tapered lines separated by circular slots and rectangular slot. The bandwidth of the antenna is improved with two circular stubs before the tapering. A rectangular slot is included before the two stubs to reduce the aperture width of the antenna. The feed line is then terminated with sectorial stub to have better coupling to the slot. The profile of the tapering of slot is designed as sinusoidal variation to have good end fire radiation for the entire frequency range. The simulated single antenna has return loss less than− 10 dB in between the frequencies 8.2–20 GHz. A five-element linear array is designed, simulated and prototype model is fabricated. The simulated and experimental results show return loss is less than − 7.5 dB for the frequency range of 8.2–20 GHz. The maximum gain of single element and array is 4.6 dBi and 7 dBi respectively. The Co and cross polarization radiation patterns are measured. The designed Vivaldi antenna array is used in X, KU band, electronic warfare and phased array applications. [ABSTRACT FROM AUTHOR]

This paper presents a miniaturized Vivaldi antenna with a scan volume of ± 30° designed for the 6–18 GHz tactical operational band, commonly employed in phased array systems and modern surveillance applications. The proposed antenna offers enhanced radiation characteristics, low cross polarization, broad beam width, and moderate gain. The design presented in this paper follows a step-by-step approach to achieve enhanced performance in terms of multi-octave bandwidth and compact size. Initially, a traditional Vivaldi antenna was designed and examined, with a modified feed structure. Subsequently, corrugated edges were inserted into the antenna, increasing its electrical length and resulting in good impedance matching, especially in the 6–10 GHz frequency band. A prototype model is fabricated and tested to validate its performance against the simulation results. The measured results demonstrate that the return loss (S11) remains below −10 dB across the operating frequency range, achieving a 50% bandwidth, with a gain of 3–7 dB, and improved co-cross polarization of −23 dB at 6 GHz and −26 dB at 18 GHz. [ABSTRACT FROM AUTHOR]

Precise radar pulse detection is the premise of electronic support measures. A constant false alarm rate (CFAR) detection algorithm based on difference of box (DOB) filter is proposed to realise low‐complexity and environment‐adaptive radar pulse detection, and the principle behind the proposed algorithm is revealed. Specifically, the DOB filter is adopted to extract the rising edges and falling edges of radar pulses, and the signal variation law of probability density functions (PDFs) during the process of DOB filter are first theoretically analysed. Based on the derived PDFs, dynamic detection threshold and fixed threshold factor for the proposed CFAR algorithm based on DOB filter are deduced to detect the presence of radar pulses. Furthermore, the closed‐form expression of the detection probability is derived. Simulations and on‐board field programmable gate arrays implementation verify the superiority of the proposed CFAR algorithm based on DOB filter. Simulation results show that the proposed algorithm performs well in detecting various types of pulse signals, the detection probability ≥99% on condition that the signal‐to‐noise ratio ≥3 dB and false alarm probability = 10−8. Moreover, the proposed CFAR algorithm based on DOB filter can deal with both singular pulses and pulse on pulse signals. [ABSTRACT FROM AUTHOR]

In the increasingly intricate electromagnetic environment, the radar receiver may simultaneously encounter multiple intentional or unintentional jamming signals, which results in temporal and spectral overlap of received signals and forms a composite jamming signal. The nature and extent of interference contained in the received signal are often unknown, while they significantly affect the accuracy of radar detection. AnOpen‐Set Compound Jamming Signal Recognition Framework based on Multi‐Task Multi‐Label (MTML‐OCJR) is proposed. Based on the time–frequency characteristic of compound jamming signals, the proposed framework employs multi‐label classification to identify components of compound jamming signals while incorporating an unknown signal detection task into the classification process. Time–frequency image reconstruction combined with extreme value model estimation is used to detect unknown types of jamming signals, enabling simultaneous signal recognition and anomaly detection. The obtained results show that the proposed approach has superior recognition performance for composite jamming signals in closed‐set environments and high anomaly detection ability for unknown signals in open‐set environments. This method has the potential to significantly enhance the effectiveness and reliability of jamming systems in battlefield scenarios. [ABSTRACT FROM AUTHOR]

This paper presents a study of the impact of different types of waveform jamming schemes against remote detonation communication devices based on Long term evolution (LTE) technology. Two main categories of waveform jamming signals (single-carrier and multi-carriers) were used. Also, two jamming scenarios against LTE-based remote detonation devices (jamming the whole LTE frame and jamming the LTE synchronization channel) were investigated. The key point of evaluating the effectiveness of the presented waveform jamming signals is by measuring their ability to successfully cut off the connection between the transmitter and the LTE-based remote detonation device. This is achieved by verifying that the remote detonation device is unable to successfully receive the transmitted information (Deny of Service (DOS) mode). To this end, emulations of these scenarios are held using two Keysight software-defined radio software programs (SystemVue 2015 and VSA 89600). Finally, a real practical experiment of the impact of different waveform jamming schemes against LTE-based remote detonation devices is emulated to present the optimal waveform jamming scheme against these types of devices. [ABSTRACT FROM AUTHOR]

Electronic warfare equipment estimates the azimuth and elevation of an unknown target by processing radar echoes received from monopulse or array antennas and interrupts radar sensing by transmitting jamming signals to the target. However, state-of-the-art targets maneuver at low altitudes in a sea surface environment to deliberately produce interference through multi-path, which poses a significant challenge for accurately estimating the estimation of the elevation angle. In this study, we propose an algorithm to accurately estimate the elevation angle of a low-altitude target despite the presence of a few arrays. Assuming that the sampled complex echoes are obtained after down-converging from the X-band (i.e., 10 GHz) to the base band, the proposed method demodulates the unknown linear frequency modulation using particle swarm optimization (PSO) and estimates the elevation angle by exploiting the new Fourier relationship between the wavelength and elevation angle. The simulation results suggest that our proposed method can successfully estimate the elevation angle for low-altitude maneuvering targets in a sea-surface environment. [ABSTRACT FROM AUTHOR]

Efficient and effective radar emitter recognition is critical for electronic support measurement (ESM) systems. However, in complex electromagnetic environments, intercepted pulse trains generally contain substantial data noise, including spurious and missing pulses. Currently, radar emitter recognition methods utilizing traditional artificial neural networks (ANNs) like CNNs and RNNs are susceptible to data noise and require intensive computations, posing challenges to meeting the performance demands of modern ESM systems. Spiking neural networks (SNNs) exhibit stronger representational capabilities compared to traditional ANNs due to the temporal dynamics of spiking neurons and richer information encoded in precise spike timing. Furthermore, SNNs achieve higher computational efficiency by performing event-driven sparse addition calculations. In this paper, a lightweight spiking neural network is proposed by combining direct coding, leaky integrate-and-fire (LIF) neurons, and surrogate gradients to recognize radar emitters. Additionally, an improved SNN for radar emitter recognition is proposed, leveraging the local timing structure of pulses to enhance adaptability to data noise. Simulation results demonstrate the superior performance of the proposed method over existing methods. [ABSTRACT FROM AUTHOR]

The object of this study is the process of forming a training dataset for diagnosing the technical condition of unmanned aerial vehicles (UAVs) using machine-learning algorithms. UAV flights are extremely important for various aspects of troop deployment. Combat UAV flights are performed under the influence of negative factors that cause flight special cases (FSC), which hinder the execution of combat missions, lead to mission failures, and result in the aircraft damage or loss. The available capabilities of autopilots are not enough for control under complex conditions, and in certain situations, the human operator cannot timely recognize a flight special case, including evaluation of the destructive impact of enemy’s electronic warfare systems on communication channels and operation of UAV. Therefore, the urgent issue is the intellectualization of onboard control systems, particularly towards recognizing the current technical state of UAV using artificial intelligence methods. To design such systems, labeled datasets are required. The procedure for forming datasets that consider the specificity of UAV construction and their combat use under adversarial conditions is not defined, necessitating the development of an appropriate method. Based on the well-known CRISP-DM methodology, a method for dataset formation has been proposed for subsequent use in artificial intelligence systems that use various machine-learning methods. This method differs from existing ones by considering the specificity of combat mission execution under adversarial conditions, which allowed for an 8.0 % increase in the accuracy of recognizing special cases in UAV flights by the onboard system. It also enabled timely detection of electronic warfare impacts on UAV and evaluation of the effectiveness of radio signal receivers jamming. [ABSTRACT FROM AUTHOR]

Robustness against Electronic Warfare/Electronic Defence attacks represents an important advantage of Noise Radar Technology (NRT). An evaluation of the related Low Probability of Detection (LPD) and of Intercept (LPI) is presented for Continuous Emission Noise Radar (CE‐NR) waveforms with different operational parameters, that is, "tailored", and with various "degrees of randomness". In this frame, three different noise radar waveforms, a phase Noise (APCN) and two "tailored" noise waveforms (FMeth and COSPAR), are compared by time–frequency analysis. Using a correlator (i.e. a two antennas) receiver, assuming a complete knowledge of the band (B) and duration (T) of the coherent emission of these waveforms, it will be shown that the LPD features of a CE‐NR do not significantly differ from those of any CE radar transmitting deterministic waveforms. However, in real operations, B and T are unknown; hence, assuming an instantaneous bandwidth estimation will show that the duration T can be estimated only for some specific "tailored" waveforms (of course, not to be operationally used). The effect of "tailoring" is analysed with prospects for future work. Finally, some limitations in the classification of these radar signals are analysed. [ABSTRACT FROM AUTHOR]

Distributed interrupted sampling repeater jamming (D-ISRJ) is the application of interrupted sampling repeater jamming technology within the framework of distributed jamming systems. It can generate coherent false targets after passing through the target radar's matched filter, but these false targets exhibit strong regularity in range and amplitude. Addressing this issue, a distributed interrupted sampling frequency-shifted repeater jamming method based on the group teaching optimization algorithm (GTOA) is proposed in this paper. By introducing frequency-shifted modulation during the retransmission of the jamming signal, the frequency shift amount of the jamming unit in each round of repeater jamming is used as an optimization variable to construct an optimization model for distributed interrupted sampling frequency-shifted repeater jamming. The parameters are then solved by using GTOA. Simulations are conducted to analyze the jamming effects under different distributed jamming modes, and the proposed optimization algorithm is compared to common swarm intelligence algorithms in the same optimization model. The method proposed in this paper can be used in the field of precision electronic warfare to improve the jamming effect of synthetic aperture radar. Experimental results show that under the given simulation conditions, the jamming signal generated by the proposed method can achieve better jamming effects. [ABSTRACT FROM AUTHOR]

"The Cybernetic Border: Drones, Technology, and Intrusion" by Iván Chaar López explores the evolution and purpose of the border as a techno-political machine for surveillance and management of subjects in the U.S. empire-nation. The text delves into the use of drones, sensors, and information systems to control and classify "intruders," primarily focusing on unauthorized Mexican immigrants. It also discusses the intersection of technology, politics, and racial formations in border enforcement, shedding light on the complexities of border management. The book is praised for its research and analysis, although some readers may find it overly reliant on buzzwords and wish for more concrete examples of how the cybernetic border operates. [Extracted from the article]

Highlights: Lightweight dual-functional segregated nanocomposite foams are developed via the supercritical CO2 (SC-CO2) foaming combined with hydrogen bonding assembly and compression molding strategy The segregated nanocomposite foams exhibit superior infrared stealth performances benefitting from the synergistic effect of highly effective thermal insulation and low infrared emissivity. Excellent absorption-dominant electromagnetic interference shielding performances are achieved owing to the synchronous construction of microcellular structures and segregated structures Lightweight infrared stealth and absorption-dominant electromagnetic interference (EMI) shielding materials are highly desirable in areas of aerospace, weapons, military and wearable electronics. Herein, lightweight and high-efficiency dual-functional segregated nanocomposite foams with microcellular structures are developed for integrated infrared stealth and absorption-dominant EMI shielding via the efficient and scalable supercritical CO2 (SC-CO2) foaming combined with hydrogen bonding assembly and compression molding strategy. The obtained lightweight segregated nanocomposite foams exhibit superior infrared stealth performances benefitting from the synergistic effect of highly effective thermal insulation and low infrared emissivity, and outstanding absorption-dominant EMI shielding performances attributed to the synchronous construction of microcellular structures and segregated structures. Particularly, the segregated nanocomposite foams present a large radiation temperature reduction of 70.2 °C at the object temperature of 100 °C, and a significantly improved EM wave absorptivity/reflectivity (A/R) ratio of 2.15 at an ultralow Ti3C2Tx content of 1.7 vol%. Moreover, the segregated nanocomposite foams exhibit outstanding working reliability and stability upon dynamic compression cycles. The results demonstrate that the lightweight and high-efficiency dual-functional segregated nanocomposite foams have excellent potentials for infrared stealth and absorption-dominant EMI shielding applications in aerospace, weapons, military and wearable electronics. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

With the maturation of digital radio frequency memory (DRFM) technology, various intra-pulse retransmission interference methods have emerged. These flexible and changeable retransmission interference methods pose significant challenges to radar detection tasks, particularly in modern battlefields. This paper proposes an attention-guided complex-valued transformer (AGCT) as a solution. First, the encoder maps the received signal contaminated by interference and noise into a high-dimensional space. Then, the dilated convolution block (DCB) group and attention block (AB) group in the mask estimator extract the delicate multi-scale features and large-scale features of the interference, respectively, to obtain a multidimensional space mask. Finally, the decoder restores interference to the time domain and outputs the estimated target echo using residual learning. Considering the characteristics of intra-pulse interference, we introduced the energy attention block (EAB) at the end of the DCBs and the ABs within our network. This addition ensures a heightened focus on extracting interference features. Furthermore, we implemented a curriculum learning strategy during the network training. This approach gradually acclimates the network to fit different types of retransmission interference, starting from simpler to more complex scenarios. Our extensive experiments, conducted under various conditions, have provided compelling evidence of the AGCT's superior performance. Compared to the comparative network, the AGCT's advantages are particularly pronounced under more harsh conditions, demonstrating its robustness and effectiveness. [ABSTRACT FROM AUTHOR]

In electronic warfare, radar signal deinterleaving is a critical task. While many researchers have applied deep learning and utilised known radar classes to construct interleaved pulse sequences training sets for deinterleaving models, these models face challenges in distinguishing between known and unknown radar classes in open‐set scenarios. To address this challenge, the authors propose a novel model, the Reconstruction Bidirectional Recurrent Neural Network (RBi‐RNN). RBi‐RNN utilises input reconstruction and employs a joint training strategy incorporating cross‐entropy loss, reconstruction loss, and centre loss. These strategies aim to maximise inter‐class latent representation distances while minimising intra‐class disparities. By incorporating an open‐set recognition method based on extreme value theory, RBi‐RNN adapts to open‐set scenarios. Simulation results demonstrate the superiority of RBi‐RNN over conventional models in both closed‐set and open‐set scenarios. In open‐set scenarios, it successfully discriminates between known and unknown radar signals within interleaved pulse sequences, deinterleaving known radar classes with high stability. The authors lay the foundation for future unsupervised deinterleaving methods designed specifically for unknown radar pulses. [ABSTRACT FROM AUTHOR]