A target parameter estimation method via atom-reconstruction in radar mainlobe jamming

Mainlobe jamming(MLJ)brings a big challenge for radar target detection,tracking,and identification.The suppression of MLJ is a hard task and an open problem in the electronic counter-counter measures(ECCM)field.Target parameters and target direction estimation is difficult in radar MLJ.A target parameter estimation method via atom-reconstruction in radar MLJ is proposed in this paper.The proposed method can suppress the MLJ and simultaneously provide high estimation accuracy of target range and angle.Precisely,the eigen-projection matrix processing(EMP)algorithm is adopted to suppress the MLJ,and the target range is estimated effectively through the beamforming and pulse compression.Then the target angle can be effectively estimated by the atom-reconstruction method.Without any prior knowledge,the MLJ can be canceled,and the angle estimation accuracy is well preserved.Furthermore,the proposed method does not have strict requirement for radar array construction,and it can be applied for linear array and planar array.Moreover,the proposed method can effectively estimate the target azimuth and elevation simultaneously when the target azimuth(or elevation)equals to the jamming azimuth(or elevation),because the MLJ is suppressed in spatial plane dimension.

基于Jamming转变理论的沥青路面车辙演化机制

沥青路面宏观车辙其实质是混合料细观结构演变的结果,为了深入理解路面车辙流变行为的发展过程,基于颗粒物质Jamming理论开展了沥青混合料车辙演化机制研究。采用图像处理技术构建了沥青混合料细观结构模型,基于时-温等效原理开展了车辙仿真测试,分析了车辙变形过程中混合料宏细观结构的变化特征,探究了沥青路面Unjamming转变行为的影响规律与车辙演化机制。结果表明:Jamming理论可以很好地解释沥青路面的车辙演变全过程,车辙深度与沥青混合料颗粒的堵塞程度密切相关;随着加载时间和作用荷载的增加,混合料Jamming堵塞程度增大,车辙深度和面积分数也逐渐增加,并最终趋于稳定,颗粒体系Jammed态的转变受到了沥青砂浆和集料骨架共同作用的影响;随着测试温度升高,试件内部颗粒位移和位移差增大,混合料Jamming堵塞程度降低。沥青路面颗粒体系由稳定的Jammed态转变为不稳定的Unjammed态,是诱导路面车辙和泛油病害发生的内因,研究结果实现了Jamming理论在非晶体系中的应用,为深入理解沥青混合料的车辙演变行为提供了一种新的研究思路。

Optimization of jamming formation of USV offboard active decoy clusters based on an improved PSO algorithm

Offboard active decoys(OADs)can effectively jam monopulse radars.However,for missiles approaching from a particular direction and distance,the OAD should be placed at a specific location,posing high requirements for timing and deployment.To improve the response speed and jamming effect,a cluster of OADs based on an unmanned surface vehicle(USV)is proposed.The formation of the cluster determines the effectiveness of jamming.First,based on the mechanism of OAD jamming,critical conditions are identified,and a method for assessing the jamming effect is proposed.Then,for the optimization of the cluster formation,a mathematical model is built,and a multi-tribe adaptive particle swarm optimization algorithm based on mutation strategy and Metropolis criterion(3M-APSO)is designed.Finally,the formation optimization problem is solved and analyzed using the 3M-APSO algorithm under specific scenarios.The results show that the improved algorithm has a faster convergence rate and superior performance as compared to the standard Adaptive-PSO algorithm.Compared with a single OAD,the optimal formation of USV-OAD cluster effectively fills the blind area and maximizes the use of jamming resources.

An angular blinking jamming method based on electronically controlled corner reflectors

Passive jamming is believed to have very good potential in countermeasure community.In this paper,a passive angular blinking jamming method based on electronically controlled corner reflectors is proposed.The amplitude of the incident wave can be modulated by switching the corner reflector between the penetration state and the reflection state,and the ensemble of multiple corner reflectors with towing rope can result in complex angle decoying effects.Dependency of the decoying effect on corner reflectors’radar cross section and positions are analyzed and simulated.Results show that the angle measured by a monopulse radar can be significantly interfered by this method while the automatic tracking is employed.

Jamming Assisted Covert Wireless Communication in Multi-Channel Systems

This paper investigates the jammerassisted multi-channel covert wireless communication(CWC)by exploiting the randomness of sub-channel selection to confuse the warden.In particular,we propose two sub-channel selection transmission schemes,named random sub-channel selection(RSS)scheme and maximum sub-channel selection(MSS)scheme,to enhance communication covertness.For each proposed scheme,we first derive closed-form expressions of the transmission outage probability(TOP),the average effective rate,and the minimum average detection error probability(DEP).Then,the average effective covert rate(ECR)is maximized by jointly optimizing the transmit power at the transmitter and the number of sub-channels.Numerical results show that there is an optimal value of the number of sub-channels that maximizes the average ECR.We also find that to achieve the maximum average ECR,a larger number of subchannels are needed facing a stricter covertness constraint.

Open World Recognition of Communication Jamming Signals

To improve the recognition ability of communication jamming signals,Siamese Neural Network-based Open World Recognition(SNNOWR)is proposed.The algorithm can recognize known jamming classes,detect new(unknown)jamming classes,and unsupervised cluseter new classes.The network of SNN-OWR is trained supervised with paired input data consisting of two samples from a known dataset.On the one hand,the network is required to have the ability to distinguish whether two samples are from the same class.On the other hand,the latent distribution of known class is forced to approach their own unique Gaussian distribution,which is prepared for the subsequent open set testing.During the test,the unknown class detection process based on Gaussian probability density function threshold is designed,and an unsupervised clustering algorithm of the unknown jamming is realized by using the prior knowledge of known classes.The simulation results show that when the jamming-to-noise ratio is more than 0d B,the accuracy of SNN-OWR algorithm for known jamming classes recognition,unknown jamming detection and unsupervised clustering of unknown jamming is about 95%.This indicates that the SNN-OWR algorithm can make the effect of the recognition of unknown jamming be almost the same as that of known jamming.

Jamming-Aided Secure Communication in Ultra-Dense LEO Integrated Satellite-Terrestrial Networks

The ultra-dense low earth orbit(LEO)integrated satellite-terrestrial networks(UDLEO-ISTN)can bring lots of benefits in terms of wide coverage,high capacity,and strong robustness.Meanwhile,the broadcasting and open natures of satellite links also reveal many challenges for transmission security protection,especially for eavesdropping defence.How to efficiently take advantage of the LEO satellite’s density and ensure the secure communication by leveraging physical layer security with the cooperation of jammers deserves further investigation.To our knowledge,using satellites as jammers in UDLEO-ISTN is still a new problem since existing works mainly focused on this issue only from the aspect of terrestrial networks.To this end,we study in this paper the cooperative secrecy communication problem in UDLEOISTN by utilizing several satellites to send jamming signal to the eavesdroppers.An iterative scheme is proposed as our solution to maximize the system secrecy energy efficiency(SEE)via jointly optimizing transmit power allocation and user association.Extensive experiment results verify that our designed optimization scheme can significantly enhance the system SEE and achieve the optimal power allocation and user association strategies.

Received Power Based Unmanned Aerial Vehicles (UAVs) Jamming Detection and Nodes Classification Using Machine Learning

This paper presents a machine-learning method for detecting jamming UAVs and classifying nodes during jamming attacks onWireless Sensor Networks(WSNs).Jamming is a type of Denial of Service(DoS)attack and intentional interference where a malicious node transmits a high-power signal to increase noise on the receiver side to disrupt the communication channel and reduce performance significantly.To defend and prevent such attacks,the first step is to detect them.The current detection approaches use centralized techniques to detect jamming,where each node collects information and forwards it to the base station.As a result,overhead and communication costs increased.In this work,we present a jamming attack and classify nodes into different categories based on their location to the jammer by employing a single node observer.As a result,we introduced a machine learning model that uses distance ratios and power received as features to detect such attacks.Furthermore,we considered several types of jammers transmitting at different power levels to evaluate the proposed metrics using MATLAB.With a detection accuracy of 99.7%for the k-nearest neighbors(KNN)algorithm and average testing accuracy of 99.9%,the presented solution is capable of efficiently and accurately detecting jamming attacks in wireless sensor networks.

Joint target assignment and power allocation in the netted C-MIMO radar when tracking multi-targets in the presence of self-defense blanket jamming

The netted radar system(NRS)has been proved to possess unique advantages in anti-jamming and improving target tracking performance.Effective resource management can greatly ensure the combat capability of the NRS.In this paper,based on the netted collocated multiple input multiple output(CMIMO)radar,an effective joint target assignment and power allocation(JTAPA)strategy for tracking multi-targets under self-defense blanket jamming is proposed.An architecture based on the distributed fusion is used in the radar network to estimate target state parameters.By deriving the predicted conditional Cramer-Rao lower bound(PC-CRLB)based on the obtained state estimation information,the objective function is formulated.To maximize the worst case tracking accuracy,the proposed JTAPA strategy implements an online target assignment and power allocation of all active nodes,subject to some resource constraints.Since the formulated JTAPA is non-convex,we propose an efficient two-step solution strategy.In terms of the simulation results,the proposed algorithm can effectively improve tracking performance in the worst case.

Numerical Analyses of Ice Jamming in Jacket Platform Conductor Array in Bohai Sea

Serious ice accumulating,pile-up and ice jamming occur around the conductor array of offshore jacket platforms during the winter every year in Bohai Sea,which could cause grave threats to the stability of platform structure,the safety of people and equipment,and even severer calamity.Therefore,the process of ice accumulation and ice jamming in the jacket platform area needs more concern.This study focuses on ice accumulation and jamming behaviors in the jacket platform conductor area by using a coupled two-dimensional hydro-ice dynamics model.A series of cases are conducted with different flow conditions,such as flow velocity,drifting direction and oscillatory flow.Through the simulation,the ice pile-up process is described and changes in ice-jamming thickness,ice pile-up location and ice pile-up volume are investigated.The differences in ice pile-up in the steady flow and oscillatory flow are analyzed.This study proposes a new approach to simulate the ice jamming process in the jacket platform conductor area,providing a reference for ice management on the platform.

Towards reinforcement learning in UAV relay for anti-jamming maritime communications

Maritime communications with sea surface reflections and sea wave occlusions are susceptible to jamming attacks due to the wide geographical area and intensive wireless communication services.Unmanned Aerial Vehicles(UAVs)help relay messages to improve communication performance,but the relay policy that depends on the rapidly changing maritime environments is difficult to optimize.In this paper,a reinforcement learning-based UAV relay policy for maritime communications is proposed to resist jamming attacks.Based on previous transmission performance,the relay location,the received power of the transmitted signal and the received jamming power,this scheme optimizes the UAV trajectory and relay power to save the energy consumption and decrease the Bit-Error-Rate(BER)of the maritime signals.A deep reinforcement learning-based scheme is also proposed,which designs a deep neural network with dueling architecture to further improve the communication performance and computational complexity.The performance bounds regarding the signal to interference plus noise ratio,energy consumption and the communication utility are provided based on the Nash equilibrium of the game against jamming,and the computational complexity of the proposed schemes is analyzed.Simulation results show that the proposed schemes improve the energy efficiency and decrease the BER compared with the benchmark.

Cognitive J^(2)SAC:Joint Jamming,Sensing,and Communication Under Antagonistic Environment

Integrated sensing and communication(ISAC)is regarded as a recent advanced technology,which is expected to realize the dual functions of sensing and communication simultaneously in one system.Nevertheless,it still faces the challenges of the information security and transmission robustness caused by the openness of wireless channel,especially under antagonistic environment.Hence,this article develops a generalized framework,named cognitive joint jamming,sensing and communication(cognitive J2SAC),to empower the current sensing/communication/jamming system with a“brain”for realizing precise sensing,reliable communication and effective jamming under antagonistic environment.Three kinds of gains can be captured by cognitive J2SAC,including integrated gain,cooperative gain and cognitive gain.Moreover,we highlight the enabling mechanism among jamming,sensing,and communication,as well as illustrating several typical use cases of cognitive J2SAC.Furthermore,several key enabled technologies are analyzed and a typical sensing enhance integrated communication and jamming case study is discussed to verify the effectiveness of the proposed method.Last but not the least,the future directions are listed before concluding this article.Integrated sensing and communication(ISAC)is regarded as a recent advanced technology,which is expected to realize the dual functions of sensing and communication simultaneously in one system.Nevertheless,it still faces the challenges of the information security and transmission robustness caused by the openness of wireless channel,especially under antagonistic environment.Hence,this article develops a generalized framework,named cognitive joint jamming,sensing and communication(cognitive J2SAC),to empower the current sensing/communication/jamming system with a“brain”for realizing precise sensing,reliable communication and effective jamming under antagonistic environment.Three kinds of gains can be captured by cognitive J2SAC,including integrated gain,cooperative gain and cognitive gain.Moreover,we highlight the enabling mechanism among jamming,sensing,and communication,as well as illustrating several typical use cases of cognitive J2SAC.Furthermore,several key enabled technologies are analyzed and a typical sensing enhance integrated communication and jamming case study is discussed to verify the effectiveness of the proposed method.Last but not the least,the future directions are listed before concluding this article.

Jamming Monitoring Technology of the Space Situational Awareness Facilities:A Comprehensive Survey

Complicated electromagnetic environments of the space situational awareness facilities(i.e.,satellite navigation systems,radar)would significantly impact normal operations.Effective monitoring and the corresponding diagnosis of the jamming signals are essential to normal opera-tions and the innovations in anti-jamming equipment.This paper demonstrates a comprehensive survey on jamming monitoring algorithms and applications.The methods in dealing with jamming signals are summarized primarily.Subsequently,the jamming detection,identification,and direc-tion finding techniques are addressed separately.Based on the established studies,we also provide some potential trends of the demonstrated jamming monitoring issues.

Sinusoidal FM Fuze's Channel Leak and Its Jamming Mechanism

Aim To get the theory base of designing FM fuze's jamming signal, its jamming mechanism was studied. Methods A sinusoidal FM fuze was analyzed in time domain and frequency domain and the concept of channel leak was presented. Results It was proved that information channel leak exists in FM fuze because of the nonlinear property of the mixer. The jamming signal was designed based on the channel leak and the jamming mechanism was analyzed in detail. Conclusion This kind of jamming signal can jam the sinusoidal FM fuzes effectively just depending on the jamming signal's feature itself. It's different from the traditional jamming way of simulating echo. Though the sinusoidal FM fuze was just analyzed, the principle is applicable to all FM fuzes. At the same time, it may be used as the reference for FM radar and communication countermeasures.

Polarization-space joint mainlobe jamming countermeasure technique based on divided dimensions

In order to solve the problem that the traditional space jamming countermeasure cannot deal with the mainlobe self-protecting jammings,a polarization-space joint mainlobe jamming countermeasure technique based on divided dimensions is proposed.Specifically,the digital beam of each row and column is firstly formed by using dual polarization digital receiving in multi-channel.Then,the polarization-space joint cancellation in both azimuth and elevation dimensions is carried out based on the polarization-space joint difference between the target echo and the jamming,as well as the divided dimension feature of the row and column beams.Finally,the sum and difference beams of the full array in the elevation or azimuth dimension are formed by the beams after jamming cancelling,and the monopulse angle measurement is further employed to obtain target angles.The effectiveness of the proposed technique is verified by simulations,indicating that the self-protecting jamming and multiple mainlobe following jammings can be both cancelled simultaneously with the angle measurement unchanged.

Optimal Periodic Pulse Jamming Signal Design for QPSK Systems

The problem of optimal periodic pulse jamming design for a quadrature phase shift keying（QPSK）communication system is investigated.First a closed-form bit-error-rate（BER）of QPSK system under the jamming of pulse signal is derived.Then the asymptotic performance of the derived BER is analyzed as the signal-to-noise ratio（SNR）grows to infinity.In order to maximize the BER of the QPSK system,the optimal parameters of periodic pulse jamming signal,including the duty cycle and signal-tojamming power ratio（SJR）,are found out.Numerical results are presented to verify our analytical results and the optimality of our design.

无线传感器网络中基于几何覆盖的Jamming攻击定位算法

提出一种基于几何覆盖理论的Jamming攻击定位(GCL,geometry-covering based localization)算法。GCL算法利用计算几何中的凸壳理论,特别是最小包容圆方法,对Jamming攻击者进行定位。理论证明了该算法的正确性和较低的时间复杂度(O(nlogn));模拟实验表明,该算法在攻击者攻击范围、网络节点密度以及攻击者位置等度量值变化的情况下,比已有算法具有更好的定位准确度。

Tolerance analysis of multiple-element linear retrodirective cross-eye jamming

Tolerance sensitivity limits the practical application of the cross-eye jammer.Previous literature has demonstrated that retrodirective cross-eye jamming with multiple antenna elements possesses the advantage of loose tolerance requirements compared to traditional cross-eye jamming.However,the previous analysis was limited,because there are still some factors affecting the parameter tolerance of the multiple-element retrodirective cross-eye jamming(MRCJ)system and they have not been investigated completely,such as the loop difference,the baseline ratio and the jammer-to-signal ratio.This paper performs a comprehensive tolerance analysis of the MRCJ system with a nonuniformspacing linear array.Simulation results demonstrate the tolerance effects of the above influence factors and give reasonable advice for easing tolerance sensitivity.

Cross-eye gain distribution of multiple-element retrodirective cross-eye jamming

The total cross-eye gain of multiple-element retrodirective cross-eye jamming(MRCJ) in the presence of the platform skin return is a distribution rather than a constant value, due to the random variation in the phase of the skin return. Although the median value of the total cross-eye gain distribution had been analyzed in previous studies, the extreme values providing useful indications of the upper and lower bounds of the total cross-eye gain have not been analyzed until now. In this paper, the cumulative distribution function and the extreme values of the total cross-eye gain of MRCJ are derived. The angular error induced in threat monopulse radar as a figure of merit is used to analyze the performance of MRCJ system. Simulation results demonstrate the variation of the angular error and discuss the proper value of jamming-to-signal ratio(JSR) making the MRCJ system more effective in consideration of the whole distribution of the total cross-eye gain.

Performance analysis of multi-group three-tuple cross-eye jamming

Monopulse radar is widely used in military.Jamming monopulse radar has always been a research hotspot in electronic warfare(EW).Cross-eye jamming has always been considered as the most effective measures to jam with monopulse radar.In this paper, we propose a multi-group three-tuple crosseye jamming structure where each group contains three antenna elements with a definite phase and an amplitude relationship.Then, based on the principle of monopulse angle measurement, the error angle is deduced theoretically.Simulations show that such a multi-group three-tuple cross-eye jamming structure performs better than the multi-element cross-eye jamming structure previously proposed, and the analysis of the centroid shows that the centroid of the structure proposed in this paper is more widely distributed in space.