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Addressing the formidable challenges posed by multiple jammers jamming multiple radars, which arise from spatial discretization, many degrees of freedom, numerous model input parameters, and the complexity of constraints, along with a multi-peaked objective function, this paper proposes a cooperative jamming resource allocation method, based on evolutionary reinforcement learning, that uses joint multi-domain information. Firstly, an adversarial scenario model is established, characterizing the interaction between multiple jammers and radars based on a multi-beam jammer model and a radar detection model. Subsequently, considering real-world scenarios, this paper analyzes the constraints and objective function involved in cooperative jamming resource allocation by multiple jammers. Finally, accounting for the impact of spatial, frequency, and energy domain information on jamming resource allocation, matrices representing spatial condition constraints, jamming beam allocation, and jamming power allocation are formulated to characterize the cooperative jamming resource allocation problem. Based on this foundation, the joint allocation of the jamming beam and jamming power is optimized under the constraints of jamming resources. Through simulation experiments, it was determined that, compared to the dung beetle optimizer (DBO) algorithm and the particle swarm optimization (PSO) algorithm, the proposed evolutionary reinforcement learning algorithm based on DBO and Q-Learning (DBO-QL) offers 3.03% and 6.25% improvements in terms of jamming benefit and 26.33% and 50.26% improvements in terms of optimization success rate, respectively. In terms of algorithm response time, the proposed hybrid DBO-QL algorithm has a response time of 0.11 s, which is 97.35% and 96.57% lower than the response times of the DBO and PSO algorithms, respectively. The results show that the method proposed in this paper has good convergence, stability, and timeliness. [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]

The specific emitter identification is widely used in electronic countermeasures, spectrum control, wireless network security and other civil and military fields. In response to the problems that the traditional specific emitter identification algorithm relies on a priori knowledge and has poor generalizability, and the existing specific emitter identification algorithm based on deep learning has poor feature selection and the adopted feature extraction network is not targeted, etc., the specific emitter identification algorithm based on multi-sequence feature learning is proposed. Firstly, multiple sequence features of the emitted signal of the communication radiation source are extracted, and these features are combined into multiple sequence features. Secondly, the multiple sequence fusion convolutional network is constructed to fuse and deeply extract the multiple sequence features and complete the classification of individual communication radiation sources through the classifier of neural network. The selected sequence features of this algorithm contain more and more essential RFF information, while the targeted design of the multi-sequence feature fusion learning network can effectively extract the essential RFF information. The results show that the algorithm can significantly improve the performance of SEI compared with the benchmark algorithm, with a recognition rate gain of about 17%. [ABSTRACT FROM AUTHOR]

Multi-UAV cluster technology is a hot topic in modern electronic countermeasures research. Based on the "OODA loop" theory of electronic countermeasures, this paper analyzes the effectiveness evaluation method of multi-UAV collaborative electronic countermeasures. We establish an electronic countermeasures correlation state analysis model based on CRITIC weighting and improved gray correlation theory. This method combines multi-UAV collaborative scene examples and use the gray state correlation analysis method based on the dynamic resolution coefficient. We simulate the effects of electronic countermeasures and various influencing factors on the expected task objectives and verify the effectiveness of the proposed method. The results show that this method can better adapt to the dynamic electronic countermeasures scenarios of multi-UAV clusters and has certain participation value for comprehensively and systematically improving the effectiveness evaluation of electronic countermeasures. [ABSTRACT FROM AUTHOR]

In radar electronic countermeasures, as the difference between jamming and targets continues to decrease, traditional methods that are implemented based on classical features are currently unable to meet the requirements of jamming detection. Compared with classical features such as texture, scale, and shape, shadow has better discernability and separability. In this paper, target shadow is investigated and applied to detect jamming in Synthetic Aperture Radar (SAR) images, and a SAR false target identification method based on shadow features is proposed. First, a difference image is generated by change detection, which can extract the shadow region in single-time SAR images. Then, a three-step differentiation condition is proposed, which can distinguish false targets from real targets. Simulated experimental results show that the proposed method can effectively extract the shadow region in SAR images and accurately distinguishreal and false targets. Furthermore, the potential of shadow in SAR image interpretation and electronic countermeasures is also demonstrated. [ABSTRACT FROM AUTHOR]

The purpose of this study is to evaluate the jamming effectiveness evaluation against monopulse radar when using a non-coherent blinking jamming model at regular intervals based on three aircraft flight trajectories. To begin, the formation trajectory is solved under various aircraft attitudes to provide the radar cross section model for three-aircraft formation flying. Following that, the jamming angle tracking error model for three-aircraft formation flying is built and coupled with the features of monopulse radar angle tracking. The effective decoy angle and other criteria are used to measure the variance in jamming performance and the efficacy of formation flying radar jamming under varying jamming power and jamming gain. Finally, using the jamming effectiveness assessment criterion, the jamming effectiveness of formation flight is calculated. The findings demonstrate that the three-aircraft formation based on time transformation jamming model can successfully induce the monopulse radar angular tracking error, enhance it to 1.54 times, and stabilize the jamming effectiveness at 0.84, and it also has a relatively good jamming effect under straight flight trajectory and circular flight trajectory. Our jamming strategy will contribute to the design of electronic countermeasures, of which the findings of this research have practical significance for the application of new jamming styles. [ABSTRACT FROM AUTHOR]

With the spread of airborne corner reflector (ACR) in the field of shipborne equipment, radar guided anti‐ship missile is facing new challenges. In order to achieve the mastery of the jamming principle of this apparatus, the paper studied its motion properties and sequential Radar Cross Section (RCS) properties. Firstly, the motion model of the ACR was obtained under certain constraints, by deriving the centroid dynamics equation and rotation dynamics equation according to the theoretical mechanics. Then, the dynamic sequential RCS model of ACR array was established by combining the motion model with the modified geometric optics method and coherent synthesis method. Through the simulation and analysis of the motion model, it was found that the flight process of the ACR can be divided into two stages: fast falling and steady falling. In the fast falling stage, the variables of the ACR system change rapidly, while the ACR rotates slowly and falls smoothly in the steady falling stage. From simulation of dynamic sequential RCS model, the results showed that the obvious depolarisation effect is occur in the fast falling stage. Further statistical analysis showed that, the omnidirectivity of single ACR is well from the dynamic perspective, meanwhile array placement can effectively enhance RCS amplitude and improve the probability density distribution. [ABSTRACT FROM AUTHOR]

In recent years, there has been significant research focused on identifying jamming signals using neural networks to improve identification accuracy. However, traditional networks require large‐scale datasets for training, which is challenging in small sample scenarios such as actual battlefield jamming signal data. Additionally, the large number of parameters in traditional models presents deployment challenges for devices. To address these issues, this study proposes a lightweight neural network model called MobileViT_CA, an improved version of MobileViT, for jamming recognition in small sample scenarios. MobileViT_CA adopts a coordinate attention mechanism suitable for lightweight networks, which further improves the classification performance of the network. The model converts one‐dimensional jamming signals into two‐dimensional time‐frequency distribution images through time‐frequency analysis and then uses the network for recognition. Compared with traditional neural network models, MobileViT_CA significantly reduces the network parameter volume while maintaining high recognition accuracy, accelerating network inference speed, and reducing hardware requirements. Experimental results show that MobileViT_CA performs well in small sample data. The model's fast learning ability has also been verified by using transfer learning, and the use of Grad‐CAM and t‐SNE to analyse MobileViT_CA demonstrates its advantages in feature recognition and extraction. Overall, this approach has the potential to significantly improve the reliability and effectiveness of jamming recognition systems in battlefield scenarios. [ABSTRACT FROM AUTHOR]

Microwave-absorbing materials have attracted extensive attention due to the development of electronic countermeasures. In this study, novel nanocomposites with core–shell structures based on the core of Fe-Co nanocrystals and the shell of furan methylamine (FMA)-modified anthracite coal (Coal-F) were designed and fabricated. The Diels-Alder (D-A) reaction of Coal-F with FMA creates a large amount of aromatic lamellar structure. After the high-temperature treatment, the modified anthracite with a high degree of graphitization showed an excellent dielectric loss, and the addition of Fe and Co effectively enhanced the magnetic loss of the obtained nanocomposites. In addition, the obtained micro-morphologies proved the core–shell structure, which plays a significant role in strengthening the interface polarization. As a result, the combined effect of the multiple loss mechanism promoted a remarkable improvement in the absorption of incident electromagnetic waves. The carbonization temperatures were specifically studied through a setting control experiment, and 1200 °C was proved to be the optimum parameter to obtain the best dielectric loss and magnetic loss of the sample. The detecting results show that the 10 wt.% CFC-1200/paraffin wax sample with a thickness of 5 mm achieves a minimum reflection loss of −41.6 dB at a frequency of 6.25 GHz, indicating an excellent microwave absorption performance. [ABSTRACT FROM AUTHOR]

Radar operating mode identification is one of the top priorities in the electronic countermeasure field for threat prediction. However, the inference speed and accuracy of existing identification methods are still not satisfactory for threat detection, and some of them need extra prior knowledge to extract features. This paper introduces an identification approach for radar operating mode to solve these problems. The variational relevance vector machine (VRVM) is presented as the feature extractor and the basic unit of identification. An improved chaotic gravity search algorithm (CGSA) is developed to increase the search breadth and optimize the hyperparameters of VRVM. Threshold-one-versus-one (TOVO) is further proposed to screen the identification results to form the final ensemble method called CGSA–VRVM–TOVO. Experimental results indicate the CGSA–VRVM–TOVO achieves 99.44% accuracy without prior knowledge. Compared with XGBoost, Random Forest, and LightGBM, our approach is 1.94%, 0.55%, and 1.11% higher in accuracy, respectively, and twice as fast as the fastest method of them all. [ABSTRACT FROM AUTHOR]

As a basic task and key link of space situational awareness, space target recognition has become crucial in threat analysis, communication reconnaissance and electronic countermeasures. Using the fingerprint features carried by the electromagnetic signal to recognize is an effective method. Because traditional radiation source recognition technologies are difficult to obtain satisfactory expert features, automatic feature extraction methods based on deep learning have become popular. Although many deep learning schemes have been proposed, most of them are only used to solve the inter-class separable problem and ignore the intra-class compactness. In addition, the openness of the real space may invalidate the existing closed-set recognition methods. In order to solve the above problems, inspired by the application of prototype learning in image recognition, we propose a novel method for recognizing space radiation sources based on a multi-scale residual prototype learning network (MSRPLNet). The method can be used for both the closed- and open-set recognition of space radiation sources. Furthermore, we also design a joint decision algorithm for an open-set recognition task to identify unknown radiation sources. To verify the effectiveness and reliability of the proposed method, we built a set of satellite signal observation and receiving systems in a real external environment and collected eight Iridium signals. The experimental results show that the accuracy of our proposed method can reach 98.34% and 91.04% for the closed- and open-set recognition of eight Iridium targets, respectively. Compared to similar research works, our method has obvious advantages. [ABSTRACT FROM AUTHOR]

The existing research proposes an intra-pulse frequency agile radar waveform with "active" anti-jamming characteristics. It uses the discontinuity and periodicity of the interrupted-sampling repeater jamming and combines the anti-jamming algorithm to effectively suppress interrupted-sampling repeater jamming. In order to improve the jamming effectiveness of the interferer for the intra-pulse frequency agile waveform, this paper proposes to jam the intra-pulse frequency agile radar by using a non-uniform interrupted-sampling and forwarding method under parameter constraints. The proposed method first obtains the sub-pulse width of the intra-pulse frequency agile radar waveform by parameter estimation of the intercepted intra-pulse frequency agile radar signal through time–frequency ridge extraction and wavelet transform. Then, we construct non-uniform interrupted-sampling repeater jamming based on sub-pulse width constraint interference parameters. Theoretical analysis and results show that the non-uniform interrupted-sampling forwarding under parameter constraints makes it challenging to suppress interference in multiple domains, such as the time–frequency and pulse compression domain for intra-pulse frequency agile radar, which significantly improves the jamming capability of the jammer for intra-pulse frequency agile radar. [ABSTRACT FROM AUTHOR]

In this study, an anti‐deception jamming target tracking algorithm based on the data‐level fusion is proposed in a distributed radar network. First, the consensus covariance intersection (CCI) algorithm is proposed to improve tracking performance by introducing the consensus theory to the field of covariance intersection fusion. Second, unscented Kalman filter is utilised to implement the preprocessing of distributed filtering. Then, two distributed target discrimination schemes are developed for non‐collaborative and collaborative false targets respectively. For non‐collaborative false targets, according to the characteristics that estimated spatial locations of the false target from different radars are relatively scattered, a false target elimination method based on nearest neighbour algorithm is proposed. For collaborative false targets, after equipped with passive radars that are less vulnerable to interference, the consensus algorithm is introduced to convey the real target information to the unconnected active radars, thus achieving an effect of global anti‐deception jamming. Finally, the CCI algorithm is deployed for distributed fusion of physical target tracking, so as to improve the overall estimation performance. [ABSTRACT FROM AUTHOR]

Interrupted sampling repeater jamming (ISRJ) is a classic active coherent jamming. Due to its structural limitations, it has inherent defects such as a discontinuous time–frequency (TF) distribution, strong distribution regularity of pulse compression results, limited jamming amplitude, and strong false targets lagging behind the real target. These defects have not been fully resolved yet due to the limitation of the theoretical analysis system. Based on the analysis of the influence factors of ISRJ on the interference performance for linear-frequency-modulated (LFM) and phase-coded signals, this paper proposes an improved ISRJ method based on the joint subsection frequency shift and two-phase modulation. The coherent superposition of jamming signals at different positions for LFM signals is achieved by controlling the frequency shift matrix and the phase modulation parameters to form a strong pre-lead false target or multiple positions and ranges of blanket jamming areas. For the phase-coded signal, the pre-lead false targets are generated through code prediction and the two-phase modulation of the code sequence, resulting in similar noise interference. The simulation results show that this method can overcome the inherent defects of ISRJ. [ABSTRACT FROM AUTHOR]

This paper proposes two data-independent phase-only beamforming algorithms for frequency diverse array multiple-input multiple-output radar against swarm interference. The proposed strategy can form a deep null at the interference area to achieve swarm interference suppression by tuning the phase of the weight vector, which can effectively reduce the hardware cost of the receiver. Specifically, the first algorithm imposes constant modulus constraint and sidelobe level constraint, and the phase-only weight vector is solved. The second algorithm performs a constant modulus decomposition of the weight vector to obtain two phase-only weight vectors, and uses two parallel phase shifters to synthesize one beamforming weight. Both methods can obtain the phase-only weight to realize suppression for swarm interference. Simulation results demonstrate that our strategy shows superiority in beam shape, output signal-to-interference-noise ratio, and phase shifter quantization performance, and has the potential for use in many applications, such as radar countermeasures and electronic defense. [ABSTRACT FROM AUTHOR]

Chaff is widely used in electronic countermeasures as an effective passive jamming method. This study proposes a chaff identification method that integrates the distribution of distance, Doppler frequency, and power in Range‐Doppler imaging. The traditional radar signal processing method estimates the distance and Doppler frequency, and the mean‐shift algorithm is combined to complete the clustering after the constant false alarm detection. Then, the target and chaff cloud models are modelled in three dimensions: radar cross‐section, range, and Doppler frequency. Using the Neyman–Pearson criterion, three chaff likelihood ratio test detectors are designed based on these assumptions. The three detectors can effectively identify the chaff, and then the theoretical detection probability and influencing factors are analysed. At the same time, the Kullback–Leibler divergence is used to describe the distribution difference between the data to be detected and the theoretical target and chaff. Besides, the different classifiers are used to identify the features of the differences in Kullback–Leibler divergence in three dimensions. Finally, the real‐life chaff datasets verified the excellent recognition rate of the authors' method for the chaff. [ABSTRACT FROM AUTHOR]

Due to advantages such as low power consumption and high concealment, deceptive jamming against synthetic aperture radar (SAR) has received extensive attention in electronic countermeasures. However, the false targets generated by most of the deceptive jamming methods still have limitations, such as poor controllability and strong regularity. Inspired by the idea of waveform coding, this paper proposed a repeater-type SAR deceptive jamming method through the joint encoding of amplitude and phase in intra-pulse and inter-pulse, which can generate a two-dimensional controllable deceptive jamming effect. Specifically, the proposed method mainly includes two parts, i.e., grouping and encoding. The number of groups determines the number of false targets, and the presence of the phase encoding produces false targets. The amplitude encoding affects the amplitude of the false targets. For the intra-pulse cases, the proposed method first samples the intercepted SAR signal. Meanwhile, the sampling points are grouped in turn. For the inter-pulse cases, the grouped objects are the pulses. Subsequently, the joint encoding of amplitude and phase is performed on each group, which generates jamming signals with deceptive effects. In this paper, the imaging effect of the generated jamming signals is analyzed in detail, and the characteristics of false targets, including numbers, position, and amplitude, are derived. The simulation and experimental results verify the correctness of the theoretical analysis. In addition, the superiority of the proposed method is verified by comparing it with other methods. [ABSTRACT FROM AUTHOR]

Airborne synthetic aperture radar (SAR) systems often encounter the threats of interceptors or electronic countermeasures (ECM) and suffer from motion measurement errors. In order to design and analyze SAR systems while considering such threats and errors, an integrated raw data simulator is proposed for airborne spotlight electronic counter-countermeasure (ECCM) SAR. The raw data for reflected echo signals and jamming signals are generated in arbitrary waveform to achieve pulse diversity. The echo signals are simulated based on the scene model computed through the inverse polar reformatting of the reflectivity map. The reflectivity map is generated by applying a noise-like speckle to an arbitrary grayscale optical image. The received jamming signals are generated by the jamming model, and their powers are determined by the jamming equivalent sigma zero (JESZ), a newly proposed quantitative measure for designing ECCM SAR systems. The phase errors due to the inaccuracy of the navigation system are also considered in the design of the proposed simulator, as navigation sensor errors were added in the motion measurement process, with the results used for the motion compensation. The validity and usefulness of the proposed simulator is verified through the simulation of autofocus algorithms, SAR jamming, and SAR ECCM with pulse diversity. Various types of autofocus algorithms were performed through the proposed simulator and, as a result, the performance trends were identified to be similar to those of the real data from actual flight tests. The simulation results of the SAR jamming and SAR ECCM indicate that the proposed JESZ is well-defined measure for quantifying the power requirements of ECCM SAR and SAR jammers. [ABSTRACT FROM AUTHOR]

The increasing demand in the development of autonomous driving systems makes the employment of automotive radars unavoidable. Such a motivation for the demonstration of fully-autonomous vehicles brings the challenge of secure driving under high traffic jam conditions. In this paper, we present the investigation of Advanced Driver Assistance Systems (ADAS) radars from the perspective of electronic warfare (EW). Close to real life, four ADAS jamming scenarios have been defined. Considering these scenarios, the necessary jamming power to jam ADAS radars is calculated. The required jamming Effective Radiated Power (ERP) is −2 dBm to 40 dBm depending on the jamming scenario. These ERP values are very low and easily realizable. Moreover, the effect of the jamming has been investigated on the radar detection at radar Range Doppler Map (RDM) and 2-Dimensional Constant False Alarm Rate (2D-CFAR). Furthermore, the possible jamming system requirements have been investigated. It is noted that the required jamming system will not require high-end technology. It is concluded that for the security of automotive driving, the ADAS radar manufacturer should consider the intentional jamming and related Electronic Counter Countermeasures (ECCM) features in the design of ADAS radars. [ABSTRACT FROM AUTHOR]

Engineering changes (ECs) are new product development activities addressing external or internal challenges, such as market demand, governmental regulations, and competitive reasons. The corresponding EC processes, although perceived as standard, can be very complex and inefficient. There seem to be significant differences between what is the “officially” documented and the executed process. To better understand this complexity, we propose a data-driven approach, based on advanced text analytics and process and data mining techniques. Our approach sets the first steps toward an automatic analysis, extracting detailed events from an unstructured event log, which is necessary for an in-depth understanding of the EC process. The results show that the predictive accuracy associated with certain EC types is high, which assures the method applicability. The contribution of this article is threefold: 1) a detailed model representation of the actual EC process is developed, revealing problematic process steps (such as bottleneck departments); 2) homogeneous, complexity-based EC types are determined (ranging from “standard” to “complex” processes); and 3) process characteristics serving as predictors for EC types are identified (e.g., the sequence of initial process steps determines a “complex” process). The proposed approach facilitates process and product innovation, and efficient design process management in future projects. [ABSTRACT FROM AUTHOR]

Electronic countermeasures (ECMs) against a radar are actions taken by an adversarial jammer to mitigate the effective utilization of the electromagnetic spectrum by the radar. On the other hand, electronic counter-countermeasures (ECCMs) are actions taken by the radar to mitigate the impact of ECMs so that the radar can continue to operate effectively. The main idea of this article is to show that ECCMs involving a radar and a jammer can be formulated as a principal–agent problem (PAP)—a problem widely studied in microeconomics. With the radar as the principal and the jammer as the agent, we design a PAP to optimize the radar's ECCM strategy in the presence of a jammer. The radar seeks to optimally trade off the signal-to-noise ratio of the target measurement with the measurement cost: cost for generating radiation power for the pulse to probe the target. We show that for a suitable choice of utility functions, the PAP is a convex optimization problem. Furthermore, we analyze the structure of the PAP and provide sufficient conditions under which the optimal solution is an increasing function of the jamming power observed by the radar; this enables computation of the radar's optimal ECCM within the class of increasing affine functions at a low computation cost. Finally, we illustrate the PAP formulation of the radar's ECCM problem via numerical simulations. We also use simulations to study a radar's ECCM problem, wherein the radar and the jammer have mismatched information. [ABSTRACT FROM AUTHOR]

A photonics-based radar jamming signal generator is proposed in this paper. By adjusting a polarization controller, interrupted-sampling repeater jamming (ISRJ), comb spectrum modulation jamming (CSMJ), ISRJ and CSMJ composite jamming can be respectively generated after photoelectric conversion. We have experimentally verified the generation of ISRJ signals with duty cycles of 50% and 25%, the generation of CSMJ signals with comb spectrum frequency intervals of 5 MHz and 10 MHz, and the generation of their composite jamming signals in the Ku band. Additionally, the ISRJ and CSMJ composite jamming effect of radar signals in the Ka band has been tested. After matched filtering processing, multiple false targets are produced and the total number of jamming targets can be up to 25, demonstrating significant jamming effects. The proposed structure can generate multi-format jamming signals without using digital radio frequency memory, which is suitable for producing high-frequency and large-bandwidth jamming signals. It can be applied in electronic countermeasure systems. • The scheme can generate multi-format jamming signals for LFM signal, namely interrupted-sampling repeater jamming (ISRJ), comb spectrum modulation jamming (CSMJ), ISRJ and CSMJ composite jamming. • The scheme does not use digital radio frequency memory, which is easy to generate high frequency and large bandwidth jamming signals. The experimental results show that the LFM signal with 1-GHz bandwidth in Ku band and the LFM signal with 1.2-GHz bandwidth in Ka band have good jamming effects. • After matched filtering processing, multiple false targets are generated and the total number of jamming targets can be up to 25, demonstrating significant jamming effects. The scheme has good application value in electronic countermeasure system. [ABSTRACT FROM AUTHOR]

Online parameter identification is vital for boosting the accuracy of the battery equivalent circuit model (ECM) under dynamic profiles. However, traditional recursive least squares (RLS) method easily decays with the noise corruption from sensors or insufficient exciting signal in reality, which further limits the performance of ECM in battery modeling and states estimation. This article thus proposes a reliable online parameter identification method for battery ECM, which utilizes a well-designed information appraisal procedure based on the Fisher-information-based Cramer–Rao lower bound (CRLB). Without increasing much computing complexity, a comprehensive appraisal indicator, derived recursively from CRLB, enables a new mechanism for online parameter updating. Simulation and experimental results prove the validity of the proposed method under different driving cycles, temperatures, and aging conditions. The results show that the identification accuracy of the proposed method has been significantly improved comparing with a typical RLS and a multiple adaptive forgetting factors RLS method. [ABSTRACT FROM AUTHOR]

Split manufacturing was introduced as a countermeasure against hardware-level security threats such as IP piracy, overbuilding, and insertion of hardware Trojans. However, the security promise of split manufacturing has been challenged by various attacks which exploit the wellknown working principles of design tools to infer the missing back-end-of-line (BEOL) interconnects. In this work, we define the security of split manufacturing formally and provide the associated proof, and we advocate accordingly for a novel, formally secure paradigm. Inspired by the notion of logic locking, we protect the front-end-of-line (FEOL) layout by embedding secret keys which are implemented through the BEOL in such a way that they become indecipherable to foundrybased attacks. At the same time, our technique is competitive with prior art in terms of layout overhead, especially for large-scale designs (ITC'99 benchmarks). Furthermore, another concern for split manufacturing is its practicality (despite successful prototyping). Therefore, we promote an alternative implementation strategy, based on package-level routing, which enables formally secure IP protection without splitting at all, and thus, without the need for a dedicated BEOL facility. We refer to this as "poor man's split manufacturing" and we study the practicality of this approach by means of physical-design exploration. [ABSTRACT FROM AUTHOR]

This article presents a detailed circuit analysis of energy selective surface (ESS), which adaptively protects electronic equipment from high-power microwaves (HPMs) thanks to its self-actuated response and nonlinear transmission feature. With the help of the equivalent circuit model (ECM), four types of ESS schemes are individuated and two of them are analyzed in detail to explore the influence of ECM parameters on the performance of ESS. Then, a high-performance ESS is designed through the proposed method. The proposed structure is realized by metal periodic structures loaded with diodes and lumped capacitors. A prototype is fabricated and measured. The results of simulations and experiments agree well, showing that the proposed ESS provides more than 30 dB shielding for high-power signals and an insertion loss lower than 1 dB for low-power signals. The excellent nonlinear transmission characteristic makes the proposed ESS practical for HPM protection. [ABSTRACT FROM AUTHOR]

In this article, the estimation problem of the state of charge (SOC) of Lithium-ion batteries is investigated. In order to truly reflect the unreliability of the sensor measured data, the data missing phenomenon with respect to the sensor measurement (e.g., the terminal voltage) is taken into account for the addressed estimation issue. By introducing a stochastic variable obeying the Bernoulli distribution with a known probability, the random occurrence of the sensor measurement unavailability is well characterized. The second-order resistor–capacitor equivalent circuit model, where the model parameters are identified by the recursive least-squares method, is developed to govern the dynamical behaviors of a Lithium-ion battery. A data-unavailability-resistant nonlinear recursive filtering algorithm is proposed to estimate the real SOC in an unreliable industrial environment. An upper bound of the filtering error covariance is obtained, which is further minimized at each sampling instant. In addition, the filter gain is recursively parameterized by solving an optimization problem with respect to two coupled recursive Riccati-like equations, thereby being suitable for the online implementation. Finally, extensive experiments are conducted to demonstrate the validity of the proposed filtering approach. [ABSTRACT FROM AUTHOR]

Frequency selective surface (FSS) with ultrawide out-of-band rejection is proposed in this article. For achieving an ultrawide and high-intensity stopband, a common second-order bandpass FSS is designed and then improved by an equivalent circuit model (ECM) design. The hybrid resonator pole separation (HRPS) decoupling method is proposed and applied during the design process. The modified ECM could realize the suppress effect on the unexcepted out-of-band transmission pole caused by coupling between layers and achieve the desired ultrawideband rejection. Furthermore, the corresponding FSS structure is established from the modified ECM through the mapping method. In addition, we conducted a detailed analysis of equivalent circuit design and the required frequency response achieve method. The measured results show that a second-order passband from 3.12 to 4.64 GHz with 0.3 dB insertion loss (IL) in the band is obtained by the proposed FSS. Meanwhile, transition bands from the passband to the stopband are narrow, and the transmission coefficients out of the passband could be suppressed under −20 dB from 5.5 to over 40 GHz. All the results demonstrate that the proposed FSS can realize an excellent out-of-band rejection while maintaining a well passband. [ABSTRACT FROM AUTHOR]

This article presents a joint state-of-charge (SOC) and state-of-available-power (SOAP) estimation method based on online battery model parameter identification. First, the SOAP of lithium-ion batteries is analyzed thoroughly, and a safe operating area border-based (SOAB-based) SOAP estimation is proposed. Second, based on the adaptive battery-state estimator (ABSE) and improved ABSE, a joint SOC and SOAB-based SOAP estimation method is proposed. The joint estimation results show that the improved ABSE achieves higher accuracy than the ABSE at different battery aging states. The open-loop accuracy evaluation results show that the improved ABSE identifies the battery model parameters more accurately, and the ABSE algorithm error source lies in its identified Rp being much higher than the actual value when the battery is charged/discharged at a high current. The ABSE does not consider the influence of load current on the equivalent circuit model parameters, so it is not suitable for SOAP estimation in theory. The improved ABSE proposed by our team can eliminate this modeling error, identify the battery model parameters, and estimate the SOC and SOAB-based SOAP more accurately. This improved ABSE is an effective algorithm for estimating the battery state when the battery is charged/discharged with a high current. [ABSTRACT FROM AUTHOR]

This article introduces an efficient modeling approach based on the Wiener structure to reinforce the capacity of classical equivalent circuit models (ECMs) in capturing the nonlinearities of lithium-ion (Li-ion) batteries. The proposed block-oriented modeling architecture is composed of a simple linear ECM followed by a static output nonlinearity block, which helps achieving a superior nonlinear mapping property while maintaining the real-time efficiency. The observability of the established battery model is analytically proven. This article also introduces an efficient parameter estimator based on extended-kernel iterative recursive least squares algorithm for real-time estimation of the parameters of the proposed Wiener model. The proposed approach is applied for state-of-charge (SoC) estimation of 3.4-Ah 3.6-V nickel-manganese-cobalt-based Li-ion cells using the extended Kalman filter (EKF). The results show about 1.5% improvement in SoC estimation accuracy compared with the EKF algorithm based on the second-order ECM. A series of real-time tests are also carried out to demonstrate the computational efficiency of the proposed method. [ABSTRACT FROM AUTHOR]

In this article, we present a via-based hybrid metal–graphene metamaterial absorber with miniaturized periodicity, broad absorption band, and large-angle radar cross Section (RCS) reduction. The unit cell of the absorber is composed of a cross-shaped graphene film, four metal arrow-shaped patterns, and four cylindrical vias. By extending the length of vias and folding the shape of the pattern on the top, the unit size of this proposed absorber is reduced greatly, while its absorption performance maintains. Furthermore, the adopted hybrid metal–graphene structure avoids loading multiple lumped elements, and the complexity and the cost of the fabrication are reduced by screen-printing technology. Because of the elements with miniaturized periodicity, the proposed absorber can shift the grating lobe (GL) out of the absorption band when illuminated by a large-angle oblique incident wave. A prototype absorber is fabricated and measured. The period of the proposed absorber is about $0.045\lambda _{L}$ at the lowest operating frequency. To the best of our knowledge, it is the smallest among the reported counterparts. Experimental results show that the absorber exhibits broadband absorption around 2.73~7.54 GHz and efficient RCS reduction with no GL under a large incident angle. The equivalent circuit analysis, full-wave simulation, and measurement results are in good agreement. [ABSTRACT FROM AUTHOR]

The correct assessment of battery states is essential to maximize battery pack performances while ensuring reliable and safe operation. This article introduces EIS2MOD, a novel modeling framework for li-ion cells based on distribution of relaxation time. A physically-based electric circuit model is developed starting from electrochemical impedance spectroscopy and open-circuit voltage measurements. Distribution of relaxation time (DRT) is applied to deconvolve the electrochemical phenomena from the EIS. The presented methodology is based on: DRT calculation from EIS; DRT analysis for ECM configuration; and model parameters extraction and fitting. The proposed framework is applied to large format li-ion pouch cells, which are tested over the whole state of charge (SoC) range and a wide temperature range (−10 °C to 35 °C). Different current profiles have been tested to validate the model, showing its high accuracy in reproducing the battery cell behavior (e.g., RMSE on the battery terminals voltage lower than 1.50% for driving cycle simulations at variable temperature and SoC). An additional advantage of EIS2MOD is its light computational load thus offering an attractive framework for battery management system implementation. [ABSTRACT FROM AUTHOR]

The energy management strategy is the key factor for hybrid vehicles since it determines how efficiently the engine power is transferred to the wheels. As a local-optimal and implementable strategy, the equivalent consumption minimization strategy is of great research interest. The equivalent factor and the gain coefficient of penalty function are two important parameters in the strategy that need to be determined in advance. It is challenging to choose these parameters to achieve minimum fuel consumption in different on-road driving cycles. For some off-road vehicles, such as wheel loaders, the loading cycle is highly repetitive. This brings a great opportunity to optimize these parameters cycle-to-cycle. In this study, an adaptive equivalent consumption minimization strategy is applied to a series hydraulic hybrid wheel loader. A cycle-to-cycle tuning scheme is developed where the equivalent factor and the gain coefficient of penalty function are optimized through repetitive loading cycles. The potential with parameter optimization in different loading cycles is identified. Results show a fuel-saving with the cycle-to-cycle optimization method of up to 6.36% in a 57 s loading cycle. [ABSTRACT FROM AUTHOR]

The equivalent consumption minimization strategy (ECMS) has been considered as a practical energy management strategy for the hybrid electric vehicles (HEVs) because it can be implemented in real time while providing satisfactory performance. However, it is still challenging to adjust an equivalent factor (EF) to its own optimal value in real time because the EF is fundamentally affected by the current driving condition. Although many adaptive ECMSs (A-ECMSs) have been developed to adjust the EF based on a charge-sustaining condition, they do not adequately respond to a change in the driving conditions. In this study, a novel ECMS for the HEVs is proposed to provide the near-optimal performance by considering actual driving conditions. First, the near-optimal condition for the EF is defined to consider a driving condition. Based on it, an iterative scheme is presented to numerically obtain the near-optimal EF. Then, the convergence analysis of the iterative scheme is conducted with practical considerations to implementing the proposed method into real-world applications. Simulation results show that the proposed strategy has better adaptability to changes in the driving conditions with a smaller loss of optimality than conventional A-ECMS which relies only on the charge-sustaining condition. The proposed strategy is also experimentally validated under real-world driving conditions. [ABSTRACT FROM AUTHOR]

In this article, the frequency-selective rasorber (FSR) built on multilayer resistive sheets, which achieves a broad absorption band, was proposed. First, the detailed analysis of the absorption and transmission performance for FSR with the single-layer/multilayer resistive sheets based on the equivalent circuit model (ECM) was demonstrated, which proved that the FSR with the multilayer resistive sheets can obtain a broader absorption band. Second, the multilayer resonator (MR) of a smaller size and higher design freedom compared with single-layer resonator was proposed. Then, the FSR on the basis of multilayer resistive sheets using MR was designed. It consists of the three-layered metallic structures and separated by an air spacer. For the top and middle layers, the lumped-resistor-loaded metallic dipole with the MR inserted into the center was applied to generate a wide absorption band and transparent window, respectively. For the bottom layer, the square-slot frequency-selective surface was optimized to match the transmission band of the resistive sheet. Simulated and measured results show that the broad absorption band and transmission band with low insertion loss have been realized, and the proposed FSR yields the widest relative bandwidth $\vert S_{11}\vert \le -10$ dB of 145.2%. [ABSTRACT FROM AUTHOR]

Objective: This study develops a biomedical ultrasound imaging method to infer microstructural information (i.e., tissue level) from imaging mechanical behavior of skeletal muscle (i.e., organ level). Methods: We first reviewed the constitutive model of skeletal muscle by regarding it as a transversely isotropic (TI) hyperelastic composite material, for which a theoretical formula was established among shear wave speed, deformation, and material parameters (MPs) using the acoustoelasticity theory. The formula was evaluated by finite element (FE) simulations and experimentally examined using ultrasound shear wave imaging (SWI) and strain imaging (SI) on in vivo passive biceps brachii muscles of two healthy volunteers. The imaging sequence included 1) generation of SW in multiple propagation directions while resting the muscle at an elbow angle of 90°; 2) generation of SW propagating along the myofiber direction during continuous uniaxial muscle extension by passively changing the elbow angle from 90° to 120°. Ultrasound-quantified SW speeds and muscle deformations were fitted by the theoretical formula to estimate MPs of in vivo passive muscle. Results: Estimated myofiber stiffness, stiffness ratio of myofiber to extracellular matrix (ECM), and ECM volume ratio all agreed with literature findings. Conclusion: The proposed mathematical formula together with our in-house ultrasound imaging method enabled assessment of microstructural material properties of in vivo passive skeletal muscle from organ-level mechanical behavior in an entirely noninvasive way. Significance: Noninvasive assessment of both micro and macro properties of in vivo skeletal muscle will advance our understanding of complex muscle dynamics and facilitate treatment and rehabilitation planning. [ABSTRACT FROM AUTHOR]

Cloud-based cell-free massive multiple-input multiple-output (CFmMIMO) technology, which exploits a large number of distributed antennas to cooperatively serve multiple users, constitutes an appealing technique for B5G/6G wireless communications. However, the distributed nature of cloud-based CFmMIMO imposes great challenges in analyzing the error probability bounds, and very few efforts have so far been paid to optimize the detector design. In this paper, we try to add a stroke to this blank by analyzing the symbol error rate (SER) and design near-optimal detection algorithms. Specifically, considering non-identical large-scale coefficients and channel estimation errors, we first leverage the pairwise error probability to derive an asymptotic SER bound for uplink cloud-based CFmMIMO systems, which is verified by simulation results. Furthermore, motivated by the concepts of successive interference cancellation (SIC) and error correction mechanism (ECM), we design two distinct types of near-optimal detectors for cloud-based CFmMIMO systems and analyze their complexity and convergence performance. Finally, extensive simulation results show that our proposed SIC and ECM based detectors outperform conventional matched filtering (MF) and minimum mean squred error (MMSE) counterparts. In particular, the MMSE-SIC and MMSE-ECM detectors approach the derived asymptotic bound, and the MF-ECM detector strikes a balance between the SER and complexity in ultra CFmMIMO scenarios. [ABSTRACT FROM AUTHOR]

In this article, the problem of finite-time adaptive fuzzy tracking control for multi-input and multi-output (MIMO) nonlinear systems with input saturation is investigated. The new finite-time command filter is introduced for generating command signals and their derivatives to work out the matter of “explosion of complexity,” and the modified fractional power-based error compensation mechanism (ECM) serves as removing the effect of filter error. Then, the finite-time adaptive control scheme is established via the backstepping recursive design technique. It guarantees all the signals of the closed-loop system (CLS) are finite-time bounded while the output tracking errors are regulated to a sufficiently small neighborhood of the origin in finite time. Finally, the effectiveness of the proposed finite-time control scheme is verified by a numerical comparison example. [ABSTRACT FROM AUTHOR]

In order to achieve anti-jamming, radar needs to identify the jamming signals to distinguish between the target echo signals and the jamming signals. Interrupted sampling repeater jamming (ISRJ) is a widely used jamming type in radar and electronic countermeasures. In this paper, we propose an efficient channel attention (ECA)-based one-dimensional residual neural network method for the ISRJ signal recognition. The joint features based on axially integral bispectrum and square integral bispectrum are used to extract the target echo signal and ISRJ signal. The ECA-based one-dimensional residual neural network is applied to the ISRJ recognition. The experiment results show that the proposed ECA-based one-dimensional residual neural network has better correct recognition rate under low signal-to-noise ratio and can offer 30.17% reduction in timeliness than the improved convolutional neural network-residual network (CNN-ResNet) method. [ABSTRACT FROM AUTHOR]

To meet the needs of optically transparent camouflage and concealment in the military field, as well as to improve the aesthetics and flexibility of wireless electronic devices. In this paper, a rectangular wideband liquid antenna with medium transparency and a hollowed-out center is proposed. The antenna is fabricated by using 3D printing technology and is primarily composed of a hollowed-out rectangular resin container, a transparent ionic liquid, and a non-transaprent slot-coupled feeding structure. By removing the center of the resin container and filling it with air, a resonator is formed that merges a rectangular ring with air. This method decreases the equivalent relative permittivity of the entire resonator and expands the operating bandwidth. Experimental results show that the antenna has an impedance bandwidth of 7 GHz-8.25 GHz, a relative bandwidth of 16.4%, a optical transparency of 84.57% and a maximum gain of 9.5dBi at 8 GHz. The proposed antenna has potential applications in electronic countermeasures, multimode composite guidance, 5G communication, and transparent electronic devices. [ABSTRACT FROM AUTHOR]

This article proposes a novel method for the generation of the deceptive jamming signal against spaceborne SAR, which can calculate the jammer’s frequency response (JFR) efficiently. The first advantage of this algorithm is that the real-time computational complexity is independent of the number of fake scattering units, so it is particularly suitable for generating scenes containing a large number of scatterers. Besides, the imaging quality of fake targets is also improved significantly, especially in the case of squint geometries. First, using the Taylor series expansion and approximations, we derive the recurrence relationship of the slant range between the adjacent pulse repetition intervals. Based on this relationship, the JFR at each azimuth time is mapped to a special spatial spectrum, which is the 2-D Fourier transform along the range and azimuth dimensions of the JFR matrix at the time of the first pulse arrival. Therefore, after the initial JFR is calculated, the subsequent JFRs can be quickly obtained by sinc function interpolation. Then, the validity and effective region of this algorithm are estimated by the theoretical analysis of the slant range error. The simulation results and a computational complexity analysis verify that the algorithm demonstrates superior performance in terms of imaging quality and efficiency. [ABSTRACT FROM AUTHOR]

Radar emitter classification (REC) plays an increasingly significant role in the electronic reconnaissance system. Due to there are many unreliable factors in traditional feature-based methods, this article focuses on improving the accuracy and stability of REC based on multipaths of original radar signals. A novel aggregated multipath extreme gradient boosting (AMP-XGBoost) is therefore put forward. Multi-path, including multi-scale, multi-domain transformations and their concatenations, is developed to exploit more information of the original signal, which contributes to providing more distinguishable features. XGBoost is used to automatically extract the features contained in these paths and complete recognition. Finally, multiple paths are sifted and aggregated according to certain weights to obtain a higher accuracy. Experiments are carried out based on signals from 6 different intra-pulse modulation mode radars with the same radio frequency (RF) range. It is demonstrated that the proposed method has higher REC accuracy than the methods only based on a single scale or domain. In the meantime, experimental results under different low SNRs show that the proposed method has higher stability. Finally, experiments based on the measured aviation radar data proves the superiority of the proposed method. [ABSTRACT FROM AUTHOR]

Due to the rapid progress of electronic countermeasures in the radar area, it is urgent to meet the demand of novel technologies that possess more possibilities for precise target indication without the influence of mainlobe jamming. Recently, frequency diverse array (FDA) steals the spotlight due to its property of range‐angle‐dependent beamforming. Besides, the multicarrier methods are also presented to generate range‐dependent beampattern. In this paper, a novel multicarrier approach is proposed based on FDA radar, namely, irregular superposed multicarrier approach. Pencil‐shaped range‐angle beampattern can be generated. Moreover, in the equal amount of frequency components, our proposed scheme outperforms the existing multicarrier FDA systems considering four aspects of performance. Simulations and comparative results validate the superiority of the proposed scheme. [ABSTRACT FROM AUTHOR]

Lithium-ion battery packs are critical to ensure the operational reliability and service life of spacecraft. The battery pack health diagnosis is meaningful for reasonable mission plan and proper control actions of spacecraft. However, the characters of space application scenarios include periodic charge and discharge, nearly constant discharge current, low electric current rate, and fixed depth of discharge, which bring challenges to battery pack state-of-health estimation. Considering these characters, this article proposes a health diagnosis approach for lithium-ion battery pack based on an improved equivalent circuit model. First, an empirical model is introduced into the standard first-order equivalent circuit model to improve the accuracy of discharge process modeling under constant current. Furthermore, a parameter lookup table is developed to simulate the complete discharge based on the in-orbit partial discharge. Finally, the battery pack complete discharge process is virtually conducted to realize battery pack capacity estimation. The proposed method just satisfies the special operating conditions in space applications. The proposed method is validated based on a real tested lithium-ion battery pack. And the results indicate that the proposed method can realize the high-accurate health diagnosis for both battery pack and its inner cells under space operating conditions, which illustrate the adaptability and applicability of the proposed method in space applications. [ABSTRACT FROM AUTHOR]

An essentialtask of the electronic support measures system is to deinterleave the intercepted radar pulse stream. To improve the radars' antijamming capability and adapt the radars to different application scenarios, the pulse signals emitted by various radars are becoming abundant, causing the pulse stream intercepted by the reconnaissancereceiver to becomemore and more complicated. Apart from fixed pulse repetition interval (PRI) signals, other PRI modulated signals, such as jitter PRI and staggered PRI, also appear in the intercepted radar pulse stream. The aforementioned pulse stream is defined as mixed radar signals in this article. The deinterleaving of mixed radar signals is an inevitable challenge in the field of electronic countermeasures. A novel algorithm for deinterleaving mixed radar signals is proposed in this article. It is flexible for deinterleaving different PRI modulated signals. A sequence retrieval method based on clustering ideas is also proposed in the algorithm, which enables different pulse sequences to be accurately separated. Simulation results show that the new algorithm has great PRI estimation accuracy for mixed radar signals in a large pulse missing rate. [ABSTRACT FROM AUTHOR]

Randomized stepped-frequency (RSF) radar, which transmits pulses with random carrier frequencies in a coherent processing interval, has an excellent electronic counter-countermeasures performance and the ability to generate the high-range-resolution profiles (HRRPs) of target with a narrow bandwidth receiver. Due to the random nature, the choice of carrier frequencies in RSF radar is usually an undersampling of available frequencies, which make the HRRP generated by matched filtering suffer from high noise-like sidelobes. In this article, we take the sinc-envelopes formed by linear-frequency-modulation pulses as well as RSF phases into account, and propose a novel (or generalized) range sidelobe suppression filters design method for RSF chirp waveform based on convex optimization (the model is transformed into a second-order cone program). By using these filters, the target HRRP with much lower sidelobes can be obtained, and the performance can be traded with the instantaneous bandwidth of the receiver, which provides a new idea for solving the sidelobe problem in RSF radar. [ABSTRACT FROM AUTHOR]

Fifth Generation District Heating and Cooling (5GDHC) networks, in which low temperature water is distributed to water-source heat pumps (WSHPs) in order to meet thermal demands, are expected to have a significant impact on the decarbonisation of energy supply. Thermal storage installed in these networks offers operational flexibility that can be leveraged to integrate renewable electrical and thermal energy sources. Thus, when considered as part of a smart multi-energy district, 5GDHC substation devices (e.g., WSHPs, storage) may be optimally operated using Model Predictive Control (MPC) in order to match demand with low-cost supply of electricity. However, the application of MPC requires the ability to model 5GDHC networks within the context of a multi-energy system. Hence, this paper extends an existing, generalised control-oriented modelling framework for multi-energy systems to accommodate 5GDHC networks. Additions include the ability to represent hydraulic pumps, thermodynamic cycle devices (such as WSHPs) and multi-energy networks within the framework. Furthermore, an economic MPC (eMPC) scheme is proposed for energy management of 5GDHC-based smart districts. Finally, a case study is presented in which the proposed eMPC controller is compared with rule-based control for economic operation of a smart district. [ABSTRACT FROM AUTHOR]

While elastin and collagen have received a lot of attention as major contributors to aortic biomechanics, glycosaminoglycans (GAGs) and proteoglycans (PGs) recently emerged as additional key players whose roles must be better elucidated if one hopes to predict aortic ruptures caused by aneurysms and dissections more reliably. GAGs are highly negatively charged polysaccharide molecules that exist in the extracellular matrix (ECM) of the arterial wall. In this critical review, we summarize the current understanding of the contributions of GAGs/PGs to the biomechanics of the normal aortic wall, as well as in the case of aortic diseases such as aneurysms and dissections. Specifically, we describe the fundamental swelling behavior of GAGs/PGs and discuss their contributions to residual stresses and aortic stiffness, thereby highlighting the importance of taking these polyanionic molecules into account in mathematical and numerical models of the aorta. We suggest specific lines of investigation to further the acquisition of experimental data to complement simulations and solidify our current understanding. We underscore different potential roles of GAGs/PGs in thoracic aortic aneurysm (TAAD) and abdominal aortic aneurysm (AAA). Namely, we report findings according to which the accumulation of GAGs/PGs in TAAD causes stress concentrations which may be sufficient to initiate and propagate delamination. On the other hand, there seems to be no clear indication of a relationship between the marked reduction in GAG/PG content and the stiffening and weakening of the aortic wall in AAA. [ABSTRACT FROM AUTHOR]

A novel design of a dual-polarized rasorber with an interabsorption transmission band is proposed. The design consists of a lossy frequency-selective surface (FSS) at the top and a lossless bandpass FSS at the bottom. The two FSS layers are separated by an air spacer. The lossy FSS consists of lumped resistor loaded cross dipole elements connected to an outer ring resonator with a slotted circular patch inside. The lossless FSS consists of a square slot. The series resonance of the lossy FSS contributes to absorption, whereas the parallel resonance of the lossy FSS and the parallel resonance of the lossless FSS together contribute to transmission. The proposed design provides a bandwidth with the reflection coefficient below $-$ 10 dB from 2.89 to 8.85 GHz, corresponding to a fractional bandwidth (FBW) of 101.5%. It has a thickness of 0.096 λL (λL is the wavelength corresponding to the lowest cutoff frequency of the bandwidth with the reflection coefficient below − 10 dB). The rasorber also shows a − 1-dB transmission band from 6.1 to 7.19 GHz (FBW 16.4%) with a minimum insertion loss of 0.44 dB at 6.6 GHz. It exhibits quite stable absorption and transmission characteristics up to 45 ° angle of incidence. The operating principle of the rasorber is discussed using an equivalent circuit model. Experimental validation of the rasorber performance is also done. Good agreement between the measured and the full-wave simulation results is observed. [ABSTRACT FROM AUTHOR]

The linear frequency-modulated frequency agile radar (FAR) can be used for synthesizing high-range-resolution profiles (HRRP), and also has excellent electronic counter-countermeasures performance. Similar to the Newtonalized orthogonal matching pursuit (NOMP) for line spectral estimation problem, the NOMP for the FAR radar termed as NOMP-FAR is designed to process each coarse range bin to extract the HRRP and velocities of multiple targets, including the guide for determining the oversampling factor and the stopping criterion. In addition, it is shown that the target will cause false alarm in the nearby coarse range bins, and a post-processing algorithm is proposed to suppress the ghost targets. Numerical simulations are conducted to demonstrate the effectiveness of NOMP-FAR. [ABSTRACT FROM AUTHOR]