An anti-main-lobe jamming algorithm for airborne early warning radar based on APC-SVRGD joint optimization

Main lobe jamming seriously affects the detection performance of airborne early warning radar.The joint processing of polarization-space has become an effective way to suppress the main lobe jamming.To avoid the main beam distortion and wave crest migration caused by the main lobe jamming in adaptive beamforming,a joint optimization algorithm based on adaptive polarization canceller(APC)and stochastic variance reduction gradient descent(SVRGD)is proposed.First,the polarization plane array structure and receiving signal model based on primary and auxiliary array cancellation are established,and an APC iterative algorithm model is constructed to calculate the optimal weight vector of the auxiliary channel.Second,based on the stochastic gradient descent principle,the variance reduction method is introduced to modify the gradient through internal and external iteration to reduce the variance of the stochastic gradient estimation,the airspace optimal weight vector is calculated and the equivalent weight vector is introduced to measure the beamforming effect.Third,by setting up a planar polarization array simulation scene,the performance of the algorithm against the interference of the main lobe and the side lobe is analyzed,and the effectiveness of the algorithm is verified under the condition of short snapshot number and certain signal to interference plus noise ratio.

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.

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.

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.

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.

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.

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.

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.

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.

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。

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.

Deceptive jamming suppression in multistatic radar based on coherent clustering

This paper proposes a suppression method of the deceptive false target(FT) produced by digital radio frequency memory(DRFM) in a multistatic radar system. The simulated deceptive false targets from DRFM cannot be easily discriminated and suppressed with traditional radar systems. Therefore, multistatic radar has attracted considerable interest as it provides improved performance against deception jamming due to several separated receivers. This paper first investigates the received signal model in the presence of multiple false targets in all receivers of the multistatic radar. Then, obtain the propagation time delays of the false targets based on the cross-correlation test of the received signals in different receivers. In doing so, local-density-based spatial clustering of applications with noise(LDBSCAN) is proposed to discriminate the FTs from the physical targets(PTs) after compensating the FTs time delays, where the FTs are approximately coincident with one position, while PTs possess small dispersion.Numerical simulations are carried out to demonstrate the feasibility and validness of the proposed method.

A jamming method against bistatic SAR based on modulation theory

This paper focuses on the jamming problem of bistatic synthetic aperture radar (BiSAR), and a jamming method against BiSAR based on modulation theory is proposed. The proposed jamming method modulates the BiSAR signal with the cosinusoidal phase to generate multi-false targets in range, and further rotates the jammer to generate multi-false targets in azimuth. The range multi-false targets and azimuth multi-false targets form the two-dimensional cover jamming or deception jamming, which can protect the important targets efficiently. The number of false targets, the interval of false targets, and the jamming square can be adjusted flexibly by setting different range jamming parameters and azimuth jamming parameters. The jamming performance and the choosing criteria of jamming parameters are also discussed. Finally, the simulated data verify the effectiveness of the jamming method.

Examining the effect of adverse geological conditions on jamming of a single shielded TBM in Uluabat tunnel using numerical modeling

Severe shield jamming events have been reported during excavation of Uluabat tunnel through adverse geological conditions, which resulted in several stoppages at advancing a single shielded tunnel boring machine(TBM). To study the jamming mechanism, three-dimensional(3D) simulation of the machine and surrounding ground was implemented using the finite difference code FLAC3D. Numerical analyses were performed for three sections along the tunnel with a higher risk for entrapment due to the combination of overburden and geological conditions. The computational results including longitudinal displacement contours and ground pressure profiles around the shield allow a better understanding of ground behavior within the excavation. Furthermore, they allow realistically assessing the impact of adverse geological conditions on shield jamming. The calculated thrust forces, which are required to move the machine forward, are in good agreement with field observations and measurements. It also proves that the numerical analysis can effectively be used for evaluating the effect of adverse geological environment on TBM entrapments and can be applied to prediction of loads on the shield and preestimating of the required thrust force during excavation through adverse ground conditions.

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.

Cooperative Jamming for Physical Layer Security in Hybrid Satellite Terrestrial Relay Networks

To integrate the satellite communications with the LTE/5G services, the concept of Hybrid Satellite Terrestrial Relay Networks(HSTRNs) has been proposed. In this paper, we investigate the secure transmission in a HSTRN where the eavesdropper can wiretap the transmitted messages from both the satellite and the intermediate relays. To effectively protect the message from wiretapping in these two phases, we consider cooperative jamming by the relays, where the jamming signals are optimized to maximize the secrecy rate under the total power constraint of relays. In the first phase, the Maximal Ratio Transmission(MRT) scheme is used to maximize the secrecy rate, while in the second phase, by interpolating between the sub-optimal MRT scheme and the null-space projection scheme, the optimal scheme can be obtained via an efficient one-dimensional searching method. Simulation results show that when the number of cooperative relays is small, the performance of the optimal scheme significantly outperforms that of MRT and null-space projection scheme. When the number of relays increases, the performance of the null-space projection approaches that of the optimal one.

Fuzzy Jamming Pattern Recognition Based on Statistic Parameters of Signal’s PSD

In order to recognize the jamming pattern in anti-jamming, a novel fuzzy jamming recognition method based on statistic parameters of received signal’s power spectral density (PSD) is proposed. It exploits PSD’s shape factor and skewness of received signal as classified characters of jamming pattern. After the mean center and variance of each jamming pattern are calculated by using some jamming samples, an exponential fuzzy membership function is used to calculate the membership value of the recognized sample. Finally, the jamming pattern of received signal is recognized by the maximum membership principle. The simulation results show that the proposed algorithm can recognize common eight jamming patterns accurately.

Parameters Design of Pull-off Deceptive Jamming to Terminal Guidance Radar

A deceptive pull-off jamming method to terminal guidance radar is put forward in this paper.The design rules about the important jamming parameters are discussed in detail,including the number of the decoy targets in range dimension,the velocity of the range gate pull-off,and the number of the decoy targets in velocity dimension and the velocity of the Doppler frequency pull-off.Also,the steps to design these parameters are brought out.The rules and design procedure discussed in this paper have important meaning for the choice of the reasonable jamming parameters in the practical applications,which can help to obtain good jamming effect.