Jamming Model Research Articles

Impact of cooperative jamming of dual stealth aircraft formation on detection performance of monopulse radar

To effectively test the detection performance of the monopulse radar under cooperative jamming of dual stealth aircraft formation, a blinking jamming model based on the interval of time-varying dual-aircraft formation is established for the first time in this study. By geometric modeling of the blinking jamming mode of the dual-aircraft formation, the authors solved the equivalent time-varying dynamic radar cross section of the penetration operation of the dual-aircraft formation; then, by taking the signal-to-interference ratio of the aircraft fuselage target echo in the actual formation as a parametric variable, we derived the equations for instantaneous detection distance, instantaneous detection probability, and cumulative detection probability of the monopulse radar in the formation projectile, and these equations were applicable to calculation under the actual jamming mode of dual-aircraft formation. Through simulation, the authors concluded for the first time that as the supersonic endurance speed increased, releasing jamming could reduce the radar detection probability considerably by more than 60%, while releasing projectiles could increase the formation’s risk of being detected by the radar by 30.37%. Thus, to effectively reduce the stability of the radar’s detection and tracking performance, the jamming power of the dual stealth aircraft formation should be no smaller than 0.5 kW and the signal gain of the formation should be no less than 20 dB.

Survey on cognitive anti‐jamming communications

In this study, the authors review various jamming and anti-jamming strategies in the context of cognitive radios (CRs). The study explores different jamming models and classifies them according to their functionality. Furthermore, a study of jamming detection techniques is provided to enable a CR to identify different jamming signals. Finally, anti-jamming communications are discussed in detail to encounter different types of jamming attacks. The focus of the study is on advanced anti-jamming approaches that are based on learning strategies including, for example, game theoretic learning, reinforcement learning and deep learning. They show differences and similarities between these approaches and the conditions under which each of the algorithms can be useful.

Design and implementation of reinforcement learning‐based intelligent jamming system

Here the intelligent jammer issue is studied. With the rapid development of cognitive radio technology, current cognitive terminals can adaptively or intelligently switch channel by spectrum sensing and decision-making. Most of the traditional jamming methods, such as swept jamming and comb jamming, generally work in a relatively fixed pattern, which are not able to effectively jam the terminals empowered with cognition and spectrum decision-making capability. In view of this problem, the authors propose an intelligent jamming decision-making system based on reinforcement learning. First, in order to jam a pair of transmitter and receiver with adaptive frequency hopping capability, a jammer with spectrum sensing, offline training and learning scheme is proposed. Second, a reinforcement learning-based algorithm for jamming decision-making is proposed and simulated. A special feature of the proposed scheme is that considering the reward is difficult to obtain in the actual communication system, a virtual jamming decision-making method is used to enable the jammer to learn and jam efficiently without the user's prior information. Finally, the proposed jamming model and algorithm are implemented and verified on Universal software radio peripheral testbed.

Target Localization With Jammer Removal Using Frequency Diverse Array

A foremost task in frequency diverse array multiple-input multiple-output (FDA-MIMO) radar is to efficiently obtain the target signal in the presence of interferences. In this paper, we employ a novel "low-rank + low-rank + sparse" decomposition model to extract the low-rank desired signal and suppress the jamming signals from both barrage and burst jammers. In the literature, the barrage jamming signals, which are intentionally interfered by enemy jammer radar, are usually assumed Gaussian distributed. However, such assumption is oversimplified to hold in practice as the interferences often exhibit non-Gaussian properties. Those non-Gaussian jamming signals, known as impulsive noise or burst jamming, are involuntarily deviated from friendly radar or other working radio equipment including amplifier saturation and sensor failures, thunderstorms and man-made noise. The estimation performance of the existing estimators, relied crucially on the Gaussian noise assumption, may degrade substantially since the probability density function (PDF) of burst jamming has heavier tails that exceed a few standard deviations than the Gaussian distribution. To capture a more general signal model with burst jamming in practice, both barrage jamming and burst jamming are included and a two-step "Go Decomposition" (GoDec) method via alternating minimization is devised for such mixed jamming signal model, where the $a$ $priori$ rank information is exploited to suppress two kinds of jammers and estimate the desired target. Simulation results verify the robust performance of the devised scheme.

Incorporating sediment non‐stationarity into ice‐affected flood‐risk projections

AbstractSediment deposition and ice jams can both increase river stages. Ice and sediment both reduce channel conveyance, affecting the flow‐stage relationship and flood risk. Classic hydrologic statistics systemically under‐predict flood risk in depositional rivers or reaches with frequent ice jams. However, when both processes influence not only flood stage but each other, the interacting processes can complicate flood risk assessment. The Big Rapids reach of the Muskegon River developed ice jams in at least 16 of the last 81 years and is actively aggrading. In reaches like this, contemporary flood risk analysis must consider ice impacts (often without local gage data) and future flood risk analysis must consider of the non‐stationary impacts of deposition on channel capacity and ice‐jam frequency. This work used hydraulic, ice jam, and sediment transport models to calculate contemporary, ice‐affected flood risk (without local stage data) and quantify the impact of deposition on future ice jams and flood risk. Accounting for ice jams increased the flood stage associated with the 1% annual flood by 0.5‐1.1 m. Sediment deposition increased future flood risk between 0.06 m (on the topset slope of a reservoir delta) and 2 m (at the advancing foreset slope).

UAV-Aided Cellular Communications with Deep Reinforcement Learning Against Jamming

Cellular systems have to resist smart jammers that can optimize their selection of jamming channels and powers based on the estimated ongoing network states. In this article, we present an unmanned aerial vehicle (UAV) aided cellular framework against jamming, in which an UAV uses reinforcement learning to choose the relay policy for a mobile user whose serving base station is attacked by a jammer. More specifically, the UAV applies deep reinforcement learning and transfer learning to help cellular systems resist smart jamming without knowing the cellular topology, the message generation model, the server computation model and the jamming model, based on the previous anti-jamming relay experiences and the observed current communication status. The performance bound in terms of the bit error rate and the UAV energy consumption is derived from the Nash equilibrium of the studied dynamic relay game and verified via simulations. Simulation results show that this scheme can reduce the bit error rate and save the UAV energy consumption in comparison with the benchmark.

Research on Jamming to RF Screening Radar Based on Signal Reconstruction

Aiming at the problem that the jamming effect to RF screening radar by active jammer is not satisfactory, this paper provides one jamming method based on signal reconstruction. That jamming method conducts signal reconstruction based on estimation to radar signal parameters, which can achieve effective jamming to RF screening radar. The method at first, establishes jamming theory model based on signal reconstruction, and conducts simulation research accordingly. This paper makes simulation to that method. The results indicate that the relative intensity of main peak after pulse compression decreases with increase of frequency deviation or relative FM slope deviation, the decrease distribution caused by positive/negative deviation is symmetric, if frequency or FM slope of reconstructed jamming signal is closer to radar signal, the gain is higher after pulse compression. So overall consideration should be conducted during jamming design to select proper frequency deviation and FM slope according to jamming power. The method provided in this paper has important reference value for engineering research.

High-Fidelity SAR Intermittent Sampling Deceptive Jamming Suppression Using Azimuth Phase Coding

The high-fidelity deceptive jamming contaminated synthetic aperture radar (SAR) images are very confusing when they are interpreted for target recognition. In this letter, a novel azimuth phase coding (APC)-based method is proposed for deceptive jamming suppression, especially with characteristics of high fidelity and intermittent sampling. The deceptive jamming model is detailedly formulated, and the difference and relation related to the real target are also discussed. Then, the APC-based suppression method is proposed, where the original APC principle and how it is to be introduced into deceptive jamming suppression are deduced and analyzed. Considering the delay feature of deceptive jamming retransmission, azimuth phase modulation, azimuth phase demodulation, and azimuth filtering are successively implemented. Then, parameters discussion is carried out for a deeper understanding. Simulation results demonstrate the superiority of the proposed method.

Composite towed jamming countermeasure method based on polarization channel expansion and blind source separation

In order to jam phased array radar effectively and reduce its target detection and recognition probability, modern jammers usually release “compound towing jamming” to achieve the purpose of “hiding the truth and revealing the false”. Because the jamming signal and the target signal come from the same direction, the radar receives a single channel signal, which can not be solved by the traditional blind source separation (BSS) algorithm. To solve this problem, the compound towing jamming model and the polarization channel expansion signal model are established in this paper. Furthermore, a signal separation method based on polarization channel expansion and BSS is proposed. Theoretical derivation and simulation results show that the proposed algorithm can achieve better separation performance in a wide range of signal-to-noise ratio and jam-to-signal ratio conditions, so that it can track the target and the towed jamming at the same time, and the radar will not lose the target when encountering jamming.

Light nuclei production in Au+Au collisions at [formula omitted] = 5–200 GeV from JAM model

Light nuclei production is sensitive to the baryon density fluctuations and can be used to probe the QCD phase transition in relativistic heavy-ion collisions. In this work, we studied the production of proton, deuteron, triton in central Au+Au collisions at sNN = 5, 7.7, 11.5, 14.5, 19.6, 27, 39, 54.4, 62.4 and 200 GeV from a transport model (JAM). Based on the coalescence production of light nuclei, we calculated the energy dependence of rapidity density dN/dy and particle ratios (d/p, t/p, and t/d). More importantly, the yield ratio Nt×Np/Nd2, which is sensitive to the neutron density fluctuations, shows a flat energy dependence and cannot describe the non-monotonic trend observed by the STAR experiment. Based on the nucleon coalescence, this work can provide constraint and reference to search for the QCD critical point and/or first order phase transition with light nuclei production in future heavy-ion collision experiments.

Effects of resonance weak decay and hadronic rescattering on the proton number fluctuations in Au+Au collisions at sNN=5GeV from a microscopic hadronic transport (JAM) model

Proton number fluctuation is sensitive observable to search for the QCD critical point in heavy-ion collisions. In this paper, we studied rapidity acceptance dependence of the proton cumulants and correlation functions in most central Au+Au collisions at $\sqrt{s_\mathrm{NN}} = 5$ GeV from a microscopic hadronic transport model (JAM). At mid-rapidity, we found the effects of resonance weak decays and hadronic re-scattering on the proton cumulants and correlation functions are small, but those effects get larger when further increasing the rapidity acceptance. On the other hand, we found the baryon number conservation is a dominant background effect on the rapidity acceptance dependence of proton number fluctuations. It leads to a strong suppression of cumulants and cumulant ratios, as well as the negative proton correlation functions. We also studied those two effects on the energy dependence of cumulant ratios of net-proton distributions in most central Au+Au collisions at $\sqrt{s_\mathrm{NN}} = 5-200$ GeV from JAM model. This work can serve as a non-critical baseline for future QCD critical point search in heavy-ion collisions at high baryon density region.

Effects of Pauli blocking on pion production in central collisions of neutron-rich nuclei

Pauli blocking is carefully investigated for the processes of $NN \rightarrow N \Delta$ and $\Delta \rightarrow N \pi$ in heavy-ion collisions, aiming at a more precise prediction of the $\pi^-/ \pi^+$ ratio which is an important observable to constrain the high-density symmetry energy. We use the AMD+JAM approach, which combines the antisymmetrized molecular dynamics for the time evolution of nucleons and the JAM model to treat processes for $\Delta$ resonances and pions. As is known in general transport-code simulations, it is difficult to treat Pauli blocking very precisely due to unphysical fluctuations and additional smearing of the phase-space distribution function, when Pauli blocking is treated in the standard method of JAM. We propose an improved method in AMD+JAM to use the Wigner function precisely calculated in AMD as the blocking probability. Different Pauli blocking methods are compared in heavy-ion collisions of neutron-rich nuclei, ${}^{132}\mathrm{Sn}+{}^{124}\mathrm{Sn}$, at 270 MeV/nucleon. With the more accurate method, we find that Pauli blocking is stronger, in particular for the neutron in the final state in $NN \rightarrow N \Delta$ and $ \Delta \to N\pi$, compared to the case with a proton in the final state. Consequently, the $\pi^-/\pi^+$ ratio becomes higher when the Pauli blocking is improved, the effect of which is found to be comparable to the sensitivity to the high-density symmetry energy.

Chromatic neuronal jamming in a primitive brain

Jamming models developed in inanimate matter have been widely used to describe cell packing in tissues1–7, but predominantly neglect cell diversity, despite its prevalence in biology. Most tissues, animal brains in particular, comprise a mix of many cell types, with mounting evidence suggesting that neurons can recognize their respective types as they organize in space8–11. How cell diversity revises the current jamming paradigm is unknown. Here, in the brain of the flatworm planarian Schmidtea mediterranea, which exhibits remarkable tissue plasticity within a simple, quantifiable nervous system12–16, we identify a distinct packing state, ‘chromatic’ jamming. Combining experiments with computational modelling, we show that neurons of distinct types form independent percolating networks barring any physical contact. This jammed state emerges as cell packing configurations become constrained by cell type-specific interactions and therefore may extend to describe cell packing in similarly complex tissues composed of multiple cell types. An imaging study of planarian flatworm brains demonstrates that densely packed neural tissues seem to have packing configurations commensurate with a jammed state.

Method of Four-Element Retrodirective Cross-Eye Jamming Based on DoA

The cross-eye method is commonly used to interfere monopulse radars. To overcome the strict tolerance and the range limitation of the traditional retrodirective cross-eye method and the multi-loop method, a novel four-element retrodirective cross-eye based on Direction of Arrival (DoA) is proposed. The mathematical model of the four-element retrodirective cross-eye jamming is derived based on the method of expansibility analysis, and the general formulas of indication angle are obtained. Based on the DoA information, the antenna layout of jamming loops is optimized, and the influence of the modulation parameters on cross-eye jamming effect are analyzed. The orthogonal four-element retrodirective cross-eye is compared with the traditional cross eye jamming, the results show that the the proposed method is superior to the traditional and the orthogonal four-element retrodirective cross-eye in terms of the jamming effect and the modulation parameter tolerance.

Research on Rebound Jamming Against Multi-Input Multi-Output Synthetic Aperture Radar

Multi-Input Multi-Output Synthetic Aperture Radar (MIMO-SAR) emits orthogonal waveform, which reduces the probability of signal interception. Using multiple antennas to receive echoes, spatial filtering can be performed to avoid interference. MIMO-SAR waveform and structure characteristics determine that it has a certain anti-jamming ability with good prospect of application. For effective jamming MIMO-SAR, a theoretical model of rebound jamming against MIMO-SAR is established by taking the space-borne MIMO-SAR as object, the similarities and differences of rebound jamming against MIMO-SAR and conventional SAR are analyzed. Then, the effects of different signal systems on rebound jamming are discussed. Finally, the interference parameter selection for rebound jamming against the MIMO-SAR is analyzed. Simulation result verifies the validity and correctness of the proposed jamming method.

Virial models and anisotropy of velocity dispersion in E-galaxies

A tensor virial approach is used to construct detailed models of 22 flattened ellipticals. The models are combined with the new observational data: extended surface brightness distributions, the profiles of isophotes flattening and their twisting, the rotation curves and the velocity dispersion profiles. A key feature of these models is a rigorous consideration of the influence of the spatial shape of galaxies (oblate spheroid or triaxial ellipsoid) on the dynamics, as well as the structure of the internal density layers in these systems. For each galaxy the ratio of the rotational energy to the potential energy was found. Comparing this ratio with the observed it is concluded that the majority of these systems cannot have isotropic velocity dispersion tensors. The anisotropy parameter limited to the interval 0.0-0.224. A correlation was found between and flattening of the outer regions for giant E-galaxies. Our results are compared with the results of other researchers. It was found that for small fast rotators our values \b{eta} are in good agreement with those, obtained in the ATLAS project. However, for giant E-galaxies, our models provide better agreement with observations, than axisymmetric JAM models. In addition, our velocity dispersion anisotropy results are in satisfactory agreement with the results of high resolution cosmological simulations in the Illustris project

Fast target deception jamming method against spaceborne synthetic aperture radar based on equivalent bistatic scattered fields

To achieve verisimilar target deceptive jamming effect, the jamming signals from different targets in different kinds of situation must be acquired. However, it is difficult to be implemented by the methods using deception-template model. In this letter, a novel target deception jamming method against spaceborne synthetic aperture radar based on electromagnetic (EM) simulation is presented. To improve the computational efficiency, an equivalent bistatic scattered fields are used to simulate the scattering characteristics of false target. The proposed method, which consists of the computer-aided-design model, the deceptive jamming model and the involved EM scattered fields, improves the performance of deceptive target in achieving the jamming results. The simulation results demonstrate the validity of the proposed method.

Deceptive jamming against multi‐channel SAR‐GMTI

Aimed at the problem that the deceptive jamming against synthetic aperture radar ground moving target indication generated by single jammer cannot work effectively in multi-channel SAR, a novel deceptive jamming against multi-channel SAR-GMTI based on two jammers is studied. First, signal model of the novel deceptive jamming is built. Then, based on three-channel clutter suppression and interferometry processing, the amplitude and interferometric phase of deceptive moving target generated by the novel deceptive jamming are derived. Last, simulation experiment validates that the novel deceptive jamming can generate false moving targets with the controllable radial velocity and located azimuth position in the multi-channel SAR.

Numerical prediction of ice-jam profiles in lower Athabasca River

A recent study of dynamic ice breakup processes and their erosional potential in the Lower Athabasca River concluded that breakup can result in very large sediment loads, which cannot be predicted at present. As a first step towards building suitable modelling capability, a user-friendly, public-domain, ice jam model is calibrated and validated using 2013 and 2014 water level measurements as well as historical data sets by others. The calibrated model is shown to reliably compute the profiles of different ice jams occurring in a 60 km reach that extends both above and below Fort McMurray. The model also enabled development of an ice jam stage-flow relationship for the city of Fort McMurray, which can help assess present and future, climate-modified, flood risk.

Research on deception jamming of chaotic composite short-range detection system based on bispectral analysis and genetic algorithm–back propagation

The chaotic compound short-range detection system is a new type of short-range detection system, which has strong anti-jamming ability. However, for the deception jamming, the characteristics of the complex short-range detection system are very similar to the detection echo, which poses a serious threat to the detection system. In order to analyze and extract the different characteristics between deceptive jamming and target echo signal, so as to realize the anti-deceptive jamming of chaotic compound short-range detection system, this article analyzes and simulates the mathematical model of deceptive jamming and target echo, and analyzes the bispectral characteristics of the simulated echo and jamming signal, and a set of anti-deception jamming feature parameters has been constructed. The identification of deceptive interference is realized by genetic algorithm–back propagation neural network, and the recognition accuracy is high and the real-time performance is good.