最新刊期
卷 50 ， 期 6 ， 2022
- 摘要：The artificial intelligence technology(e.g., deep learning) is an effective approach to electromagnetic target(ET) recognition. However, in the recognition of multi-mode ETs, when the training samples with a certain mode are missing or rare, the recognition rate with this mode will be significantly degraded. The reason mainly lies in that the data distance between different modes of the same ET may exceed the data distance between different ETs. To remedy this, a cross-modal ET recognition approach via Siamese network is developed in this paper. Following the framework of metric learning, we design the network structure and the loss function carefully, so that the recognition training process intentionally drives the Siamese network to enlarge the data distance between different ETs while shorten the distance between different modes of the same ET. Consequently, the multi-mode ETs can still be successfully recognized by employing certain distance-based decision criterion, even with imbalanced training data sets for different modes. The numerical results based on realistic data show that with same data sets and network size, the cross-modal recognition rate of the proposed approach is 20% higher than that of the classical convolutional neural network approach, and that of the popular data-enhancement approaches.关键词：electromagnetic targets;cross-modal recognition;siamese network;metric learning;imbalanced data set5|13|3更新时间：2025-12-08
- 摘要：Multi-function radars(MFRs) have great flexibilities in beam scheduling and complex modulation of radar work modes. It can perform multiple system tasks simultaneously in the radar timeline, which brings great challenges to electronic reconnaissance devices. Online detection of multiple MFR work mode changepoints accurately and rapidly is of great importance for identifying the behavioral intentions of a multi-function radar. This paper proposes an online detection method of MFR work mode changepoints. The proposed method takes the measurement noise, spurious pulses and lost pulses in real electromagnetic environment into consideration and can realize online changepoints detection of radar working mode under the observations contaminated by these non-ideal situations. Also, this method can estimate the modulation parameters of the work modes before and after the changepoints. Experimental results validate the effectiveness and superiority of the proposed method compared with the traditional changepoint detection methods.关键词：Multi-function radar;work mode;changepoint detection;spurious pulse;lost pulse;measurement noise9|8|1更新时间：2025-12-08
- 摘要：In order to solve the problem of collaborative decision-making of frequency-hopping communication jamming in collaborative electronic warfare, based on deep reinforcement learning, a collaborative jamming decision-making algorithm based on actor-critic algorithm framework is proposed, which fuses dominant functions by building a collaborative decision-making model of "overall optimization and making decision station by station". An expert experience mechanism is embedded in the reward function to improve the exploration ability of the algorithm, and the decision network is optimized by the distributed execution-centralized training method, so that the algorithm can output the jamming scheme with the highest resource utilization rate and greatly improve the efficiency of decision-making. The simulation results show that, compared with the existing intelligent decision algorithms, the jamming scheme presented in this paper can save 8% of the interference resources and improve the decision efficiency by more than 50%, which is of great practical value.关键词：deep reinforcement learning;communication jamming decision-making;jamming resource allocation;advantage function;expert incentive8|13|4更新时间：2025-12-08
- 摘要：In the increasingly complex electromagnetic spectrum environment, in order to realize the management and control of spectrum resources, it is necessary to determine whether the received signal is from the known or unknown radiation source. To tackle this problem, this paper proposes an algorithm named Open-MUSIC(MUltiple SIgnal Classification) to discriminate the known and unknown sources. The key idea of Open-MUSIC is to form the feature space from the known classes via a judiciously designed neural network, and then the feature space is decomposed into two orthogonal subspaces, namely the range subspace and the null subspace. Based on the projection ratio of the test signal's feature onto the two subspaces, we can accurately discriminate the known and the unknown radiation sources. Experiments on three datasets show that the performance of the Open-MUSIC is improved by more than 3% on electromagnetic data sets compared to other methods.关键词：open set recognition;feature subspace decomposition;center loss;projection4|13|0更新时间：2025-12-08
- 摘要：In order to solve the problem of jamming power allocation in battlefield cooperative communication countermeasures, this paper designs a distributed cooperative jamming power allocation method based on multi-agent deep reinforcement learning. Specifically, modeling the communication jamming power allocation as a fully cooperative multi-agent task, then the framework of centralized training and distributed decision-making is adopted to alleviate the characteristic of non-stationary environment and high dimensions in multi-agent system, reducing the communication overhead between agents as well, and introducing the maximum policy entropy criterion to control the exploration efficiency of each agent. Regarding maximizing the cumulative jamming reward and maximizing the entropy of the jamming policy as the optimization goal, then accelerates the learning of cooperative strategies. Simulation results indicate the proposed distributed method can effectively solve the high-dimensional cooperative jamming power allocation problem. Compared with the existing centralized allocation method, it has faster learning speed and less volatility, and the jamming efficiency is 16.8% higher than that of the centralized method under the same conditions.关键词：communication countermeasures;cooperative resource allocation;multi-agent deep reinforcement learning;distributed strategy;maximum policy entropy9|15|6更新时间：2025-12-08
- 摘要：In this paper, a novel filtering quadrature coupler(FQC) with reconfigurable frequency and output direction is presented. It simply consists of four half-wavelength step impedance resonators(SIRs) loaded with varactors at the open ends for frequency tuning and between resonators for inter-stage coupling control. Admittance invertors with electrical and magnetic types are utilized to replace the transmission lines in conventional quadrature coupler for filtering response. By using the simple configuration, the proposed FQC can realize reconfigurable output directions without any switch component. Theoretical analysis has been given and a microstrip prototype has been designed, fabricated and measured to demonstrate the proposed technique. The measured results show that the proposed FQC can continuously cover the frequency range of 1.2~1.6 GHz at forward output direction with 90° phase difference and at backward output direction with -90° phase difference.关键词：filtering quadrature coupler;reconfigurable coupler;reconfigurable filter;reconfigurable operating frequency;reconfigurable output direction5|11|0更新时间：2025-12-08
- 摘要：Modulation recognition is one of the key technologies in satellite communication anti-interference and interference analysis. The existing on-board recognition methods have low intelligence degree and poor adaptability. In order to solve these problems, an intelligent recognition method based on multi-fractal spectrum and deep learning is proposed. Firstly, the multi-fractal spectrum characteristics of common satellite communication signals are analyzed, a multi-fractal eigendomain matrix is constructed. On this basis, the eigendomain matrix is combined with the deep learning residual network, and the structure of the residual network is optimized and improved according to the multi-scale idea, and the multi-layer autonomous detail feature extraction advantage of the improved residual network perfectly corresponds to the multi-scale feature characterization capability of the multi-fractal spectrum. Finally, the modulation of satellite communication signal is effectively recognized. The simulation results show that this method has good recognition performance, when the SNR is not lower than 1 dB, the average recognition rate is greater than 89%.关键词：satellite communication;deep learning;modulation recognition;multi-fractal spectrum6|15|3更新时间：2025-12-08
- 摘要：Multifunctional radar working mode recognition is important for cognitive electronic warfare. In practical applications, due to the diversity and concealment of multifunctional radar operating modes, the intercepted pulses for different operating modes is limited. Therefore, using only limited intercepted pulse records to accurately recognize the modes of the radar is a challenging but important task for radar countermeasures. To address the above problem, this paper proposes a novel recognition method by integrating the prior knowledge with the prototype network. The core of this method is to encode and embed the prior knowledge into prototype network training to obtain better recognition performance with few training samples. The simulation results show that compared with prototype networks and SVM that do not use prior knowledge, the recognition accuracy of the prototype network with prior knowledge is increased by 2.9% and 10.5%, respectively.关键词：few samples;radar working modes recognition;prototype network;prior knowledge embedding3|10|10更新时间：2025-12-08
- 摘要：To address the difficulty of deinterleaving special radars with large pulse repetition interval(PRI) range and the low accuracy of PRI estimation in complex electromagnetic environment, a radar signal deinterleaving algorithm based on PRI multi-level bin and deep forest is proposed. The algorithm utilizes the PRI multi-level bin structure for PRI transformation to improve the detection rate for special radars. The PRI boundary features of radar signals are derived from the number of pulse pairs in the multi-level bin and the PRI transform results. The PRI boundary features of special radars in different environments is mixed and the features by smoothing filters are enhanced. The deep forest is trained to predict the complete PRI range and thus to correct the central PRI estimate. Finally, based on the central value of PRI and the PRI range, the pulses are searched and extracted. Simulation experiments show that the proposed algorithm can effectively deinterleaving jittered, unilinear, bilinear, sawtooth and sinusoidal radars with large PRI range. The PRI range prediction performance is improved by 14% and the PRI estimation error is reduced by 75%.关键词：electronic reconnaissance;special radar;multi-level bin;deep forest;pulse repetition interval estimation;pulse repetition interval range5|10|3更新时间：2025-12-08
- 摘要：To solve the problem of low efficiency of electromagnetic spectrum anomaly detection, we propose a new method of spectrum anomaly detection based on depth feature fusion which combines convolutional neural networks(CNN) and long short-term memory(LSTM) Networks. Firstly, a deep feature extraction network is constructed, which includes a multi-level CNN and a LSTM. The network can extract depth features in a hierarchical manner. Then, pooling layer, concatenate layer and other operations are used to fuse the depth features to achieve high-precision prediction of spectrum data. Finally, the mean square error between the predicted data and the real data is calculated by discriminating the spectrum anomaly. The algorithm can detect multiple kinds of abnormal states under the condition of unsupervised learning. We verified our algorithm in frequency bands of public spectrum data. The results show that our algorithm can effectively realize electromagnetic spectrum anomaly detection.关键词：deep learning;anomaly detection;spectrum prediction;fusion of depth feature16|18|0更新时间：2025-12-08
- 摘要：Cognitive radio is a key technology to solve the problem of energy efficiency in wireless communication, and spectrum sensing is of great significance for improving the efficiency of spectrum utilization. To solve the problem that the consensus-based distributed cooperative spectrum sensing algorithm is vulnerable to malicious node data injection attacks, we propose two approaches for detecting and localizing malicious nodes based on neural networks. And a collaborative peer-to-peer machine learning protocol(Gossip Learning) is adopted to facilitate training these neural network models. We simulate the process of distributed cooperative spectrum sensing on a 9-node Manhattan network, and verify the effectiveness of the proposed approaches. Numerical results illustrate that the proposed neural network-based approaches can effectively improve the performance of detecting and localizing malicious nodes. The collaborative learning strategy can enable nodes to learn more attack characteristics, and thus make the network more robust to attacks.关键词：cognitive radio;cooperative spectrum sensing;consensus algorithm;malicious node;neural network;collaborative learning6|12|2更新时间：2025-12-08
Intelligent game of electromagnetic spectrum
- 摘要：With the frequent occurrence of security chip information leakage incidents, it is imperative to improve the protection capabilities of security chips. This paper proposes a method of software-defined active shield generation and protection system construction, which can generate a high-entropy top-level metal protection network in a short time without the need for security background knowledge. The active shield can effectively shield key components such as chip encryption modules, and at the same time meet the regulatory requirements. The method proposed in this paper can define wiring type, line width, line space, and other parameters through the software, and can be applied to different process nodes. Relevant technologies have been simulated, and verified under the Hua Hong 130 nm process, realizing the combination of the active shield and two kinds of integrity detection circuits, verifying the detection effect of active shield against focused ion beam and microprobe attacks, and realizing effective perception and protection against intrusive physical attacks.关键词：integrated circuit safety;active shield;Hamiltonian structure;detection circuit;resistance to physical attack4|8|0更新时间：2025-12-08
- 摘要：In this paper, a K-band four-channel integrated receiving front-end module is developed using the multilayer low temperature co-fired ceramics (LTCC) technology for the application of low earth orbit satellite communication. The operating frequency is from 17.7 to 20.2 GHz. MMIC chips, including low noise amplifiers, 6 bit phase shifters, 5 bit attenuators and series-parallel converters, and multilayer ceramic capacitors are mounted inside the cavity of the module while passive components, such as a power combiner and low-pass filters, are embedded into the multilayer substrate. The overall size of the module is 28×28×1.35 mm3. In measurements, the in-band channel gain is over 31.5 dB, the noise figure is 1.7~1.9 dB, and the suppression against the transmitting band of 28~30 GHz is over 61.5 dBc. The control errors of phase shift and attenuation amplitude are better than 4.7° and 1 dB, respectively. It is demonstrated that our design has the advantages of high integration, high gain, high suppression and low noise.关键词：low temperature co-fired ceramic(LTCC) technology;integrated receiving front-end module;low earth orbit(LEO) satellite communication3|10|2更新时间：2025-12-08
- 摘要：Data privacy protection and service environment trust have become important issues with the rapidly increasing amount of data and computing power of services in current era of Mobile Internet. This paper studies the trusted privacy service computing model for typical application scenarios of convolutional neural network. It explores data and model computing methods supporting homomorphic encryption to protect data privacy, builds methods of service certificate storage and calculating equity interests distribution based on blockchain and smart contract technology to ensure the openness, transparency, credibility and traceability of service computing. A novel resource and data service paradigm of cloud environment is explored for resource providers, model owners and users to promote the effective integration of resources and develop sharing economy. Finally, the privacy protection method in the model is analyzed through experiments.关键词：homomorphic encryption;privacy protection;smart contract;convolutional neural network9|13|0更新时间：2025-12-08
- 摘要：Due to the nature of spatial diffusion, urban air pollution presents a high correlation with regional concentration feature. Therefore, how to use spatio-temporal related data from urban multiple air pollution detection sites to predict air pollution concentration of a special target location is an important research effort for solving the problem of uneven site distribution. Concerning the multi-dimensional impacts of the air pollutant factors’ features and the influence of meteorological factors, we propose an air pollutant concentration prediction model, which uses multi-site spatial detection data within a region to predict the concentration of the target station in this paper. This model is able to learn dimensional correlation characteristics and spatial correlation characteristics from multi-site pollutant concentration and meteorological data in the urban area through the multi-layer convolutional neural network, and then analyze the time-series correlation characteristics of multi-site concentration by utilizing the multi-layer auto-encoder network based long short-term memory network. The experimental results show that our proposed model obtains better performances than traditional machine learning based models under a real-world dataset, and meanwhile, the generalization performance of the proposed model has been examined based on multiple urban air pollution database.关键词：deep learning;air pollution;spatio-temporal data;multiple sites joint prediction;convolutional neural network;long short-term memory network3|11|1更新时间：2025-12-08
- 摘要：Lots of experiments have shown that the abnormal expression of microRNA(miRNA) is related to the evolution and progression of human complex diseases. Identifying associations between miRNAs and diseases is beneficial to promote the development of clinical medicine. However, traditional experimental methods are often time-consuming and inefficient, so there is an urgent need for efficient computational methods to predict the potential associations between miRNAs and diseases. In this paper, we propose an end-to-end computational model based on heterogeneous graph attention network to predict the associations between miRNAs and diseases. This model captures the structure and attribute information of heterogeneous neighbors via the multi-head attention mechanism, and fuses them with the attribute information of the central vertex to generate more representative feature embeddings of miRNAs and diseases, and then predicts the potential associations between miRNAs and diseases through a fully connected layer. The 5-fold cross-validation results show that our model achieves 93.52% and 94.82% AUC values based on HMDD v2.0 and HMDD v3.0 datasets, respectively. In addition, the case study on esophageal neoplasms shows that 48 of the top 50 miRNAs predicted by our model are confirmed. The above experimental results indicate that our model can be used as a reliable tool to predict candidate disease-related miRNAs.关键词：graph attention network;microRNA-disease associations;heterogeneous graph;deep learning3|9|1更新时间：2025-12-08
- 摘要：In the process of virtual restoration of damaged cultural relics, fragments matching is one of the important research contents. The traditional geometric driven matching algorithms have large matching error for fracture surfaces with low overlapping rate,thus aiming at cultural relics with certain thickness, an automatic matching and splicing algorithm of cultural relics fragments based on feature region division is proposed. Firstly, the fracture surfaces of fragments are extracted, normal vector features are constructed in the local region of the points on the fracture surface to obtain the feature points and feature point sets of the fracture surfaces; secondly, each feature point set is divided into several small-scale point cloud regions, and the fragment fracture surfaces are aligned by region matching; finally, the iterative closest point (ICP) algorithm based on threshold constraint is used to further accurately align the fracture surfaces, so as to achieve the final matching of cultural relic fragments. The experimental results show that the time efficiency and matching accuracy of the proposed algorithm are at least 10% and 20% higher than those of many existing algorithms, respectively, and it is suitable for the matching of cultural relic fragments with low overlapping fracture surfaces.关键词：fragments matching;feature point;region division;threshold constraint;iterative closest point5|10|1更新时间：2025-12-08
- 摘要：The space interference generated by the inclined interface is a linear noise with a certain tendency in the GPR profile, and it can be suppressed by f-k filtering approach. Because the conventional f-k filtering method uses the complex conjugate feature of FFT transform, it does not pay special attention to and process the negative apparent velocity (negative wave number) signal in the actual data, and the suppression effect of linear interference wave is not ideal, which has a great impact on the data interpretation. Therefore, this study improves the f-k filtering method. In the process of filtering, this study analyzes the data of positive and negative wave number domain after f-k transformation of actual GPR data, and identifies and suppresses the positive and negative wave number signals in the actual data respectively. The improved f-k filtering method can effectively suppress the linear noise and highlight the detection target in both simulation data and actual production data.关键词：ground penetrating radar;f-k filtering;space interference;linear noise8|12|1更新时间：2025-12-08
- 摘要：Aiming at the problems of misalignment and distortion after parallax image stitching, a smooth optimization method for parallax image stitching based on local projection is proposed. The input image is performed feature point detection, matched by locality preserving structure, and calculated the projection matrix. The normalized distance is determined by the projection model of the coincident area and the projection matrix. If it is less than the threshold, it will be retained, otherwise it will be discarded and continue matrix calculation. In the non-coincident part of the image, the minimum bending energy function is obtained by calculating the deformation function of the image, so that the non-coincident region transits to the global transformation. The experimental results show that the proposed algorithm can not only improve the matching accuracy of the image, but also optimize the distortion of the image, enhance the integrity of the image and obtain a better visual experience.关键词：parallax images stitching;projection matrix;global transformation;threshold2|10|2更新时间：2025-12-08
- 摘要：Industrial internet is rapidly growing up while encountering severe information security risks at the same time. Aiming at the problem that traditional intrusion detection methods are low in accuracy and difficult to adapt to the massive unbalanced data of industrial Internet, an industrial Internet intrusion detection method based on capsule network is proposed. Firstly, a module involved feature extraction module is constructed based on the residual block, and a global average pooling layer is introduced to get high-quality data features. Secondly, the dynamic routing algorithm is introduced. The intrusion data features are clustered through iteration, and classification are completed in the module based on capsule network. The test results out of the data set from sensor network with Modbus/TCP protocol used in gas pipeline show that the method can improve the accuracy rate while extracting features implicitly. Compared to the listed algorithms, the proposed method in this paper performs better in test indexes with stronger robustness to unbalanced data and is closer to meet the needs of intrusion detection from industrial Internet.关键词：industrial Internet;intrusion detection;capsule network;residual network8|11|2更新时间：2025-12-08
- 摘要：Unlike the previous reversible flip-flops(RFFs) which have a single D, T or JK flip-flop characteristic function for one circuit, an edge-triggered(including dual edge-trigged) RFF with function configurable(FCRFF) is designed based on the proposed unified characteristic equation of D, T and JK FFs. By preset some inputs of FCRFF, the proposed edge-trigged FCRFF can act as D, T and JK reversible FF and also can load data asynchronously. The functions of proposed FCRFF are approved by simulation using Modelsim after modeled with Verilog HDL. Comparing with those published D, T and JK reversible FFs, the proposed FCRFF can combine D, T and JK reversible FFs' functions into one circuit and have asynchronous data loading function additionally only with a few quantum cost increasing.关键词：reversible logic;reversible flip-flop;reversible dual edge-trigged flip-flop;reversible sequential circuit3|15|0更新时间：2025-12-08
- 摘要：Hyperspectral microwave radiometer is a new type of passive microwave remote sensor for detecting atmospheric trace gases, and the digital spectrometer is the core component of the hyperspectral microwave radiometer. In this paper, a new broadband, real-time digital spectrometer design and implementation scheme is proposed. The core radix 16 real-time complex fast Fourier transform(FFT) algorithm is formed by improving and combining the parallel processing and complex processing of FFT. Finally, the power spectrum of the signals can be obtained. The results for 1 024(1k) spectral channels are achieved by the digital spectrometer with the sampling rate of 4.8 GHz, the quantization bits of 8 bit, and the input 3 dB bandwidth of 2 GHz. The real atmospheric brightness temperature spectrum is simulated and analyzed by atmospheric radiative transfer simulator(ARTS), and then the input point frequency signal is tested. The results show that the maximum value of sub-band brightness temperature bias caused by the core algorithm is about 0.02 K, and the core algorithm sub-band sensitivity deteriorates within 20% compared with the ideal sub-band sensitivity. The effective number of bits(ENOB) of the digital spectrometer is better than 3 bit, the signal-to-noise ratio(SNR) is better than 20 dB, and the spectral resolution is constant at 2.3 MHz, which can effectively meet the requirements of radiometers for spectral line detection in middle and upper atmosphere.关键词：microwave limb sounding;hyperspectral microwave radiometer;broadband digital spectrometer;FPGA parallel processing;radix 16 real-time complex FFT algorithm3|17|2更新时间：2025-12-08
- 摘要：An analysis method about the minimum acceptable power consumption of multiple-loop feedback filter is presented. When a 3rd follow-the-leader-feedback(FLFB) low pass filter working at the stable state edge, based on Routh-Hurwitz stability criteria, synthesize the minimum acceptable phase margin curve and transconductance figure by MATLAB, and the relationship between filter design parameters and power consumption is given through circuit-level analysis and verification. Design is fabricated in UMC 40 nm CMOS technology, the post-simulation results show that the cutoff frequency is adjustable for 0.9~9.9 MHz, the layout area is 0.03 mm2, and the total power consumption is 0.36 mW, reduced nearly 30% compared with the traditional design that phase margin is 60°. Under the premise of ensuring the stable operation of the filter, the power consumption is reduced, confirmed the minimum acceptable power consumption theory.关键词：low pass filter;minimum acceptable power consumption;follow-the-leader-feedback;stability criteria3|10|3更新时间：2025-12-08
PAPERS
- 摘要：To give a comprehensive overview on the NSFC(National Natural Science Foundation of China) major international(regional) cooperation research program on information science, we review the projects applied and funded from 2011 to 2021. More specifically, we summary and analyze the proposed and approved projects from the following aspects, i.e., approved rate, subject code, affiliation, and research area of the projects. Moreover, we briefly introduce some typical projects as showcases. This review would be valuable and constructive to the reform of the NSFC project.关键词：information science;the NSFC major international(regional) cooperation research programs;approved project analysis2|10|0更新时间：2025-12-08
- 摘要：Molecular communication, which uses tiny particles to encode, transmit and receive information, is a communication paradigm with good biological compatibility and small size, and is the one of the most promising communication schemes for the realization of nanonetwork engineering. The concept of molecular communication has attracted wide attention since it was put forward. At present, the theory of molecular communication has been widely studied, and the related experiments have also made progress. However, there are still many problems to be solved in the construction of practical molecular communication systems. To promote the development of molecular communication, it is necessary to systematically summarize the theories and current research progress of molecular communication. In this paper, the basic concepts and research progress of diffusion-based molecular communication are described, including channel models, signal encoding, modulation, and receiving mechanisms. In addition, the latest research progress of the synchronization mechanisms of molecular communication systems, mobile molecular communication systems, and molecular communication experiment systems are introduced. Finally, future works and research directions are given.关键词：molecular communication;channel;encoding;modulation;detection;synchronization;mobile molecular communication;experiment4|15|1更新时间：2025-12-08
- 摘要：Connected component analysis(CCA) is one of the major steps in binary image processing, which label pixels in single-pass and extract the features of each connected component at the same time. Single-pass connected component analysis algorithm based on FPGA hardware architecture can realize fast real-time bit stream image processing. In this article, we focus on connected component labeling(CCL) algorithms and single-pass connected component analysis algorithms developed in the last decade, explain the implementation strategies and architectures of the typical connected component analysis algorithms, present their pseudo codes, and describe their Union-find algorithms. In addition, through data comparison, the performance of different algorithms is compared and analyzed in terms of memory requirements and throughput of algorithm hardware architectures, and their advantages and disadvantages are summarized. The analysis results provide a theoretical basis and data reference for the realization of connected component detection based on FPGA high-speed bit stream images.关键词：connected component analysis;connected component labeling;feature extraction;image processing;FPGA3|7|3更新时间：2025-12-08
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