Jamming Conditions Research Articles

Effect of submergence of sacrificial piles on local scour reduction at a bridge pier under U-type debris jam conditions

Effect of submergence of sacrificial piles on local scour reduction at a bridge pier under U-type debris jam conditions

3D position deployment and performance optimization of mmWave UAV-assisted HetIoT under jamming condition

Heterogeneous Internet of Things (HetIoT) has received widespread attention due to its provision of various convenient services in fields such as smart cities, intelligent transportation, environmental monitoring and security systems. Due to HetIoT inherently demands high data rates, bandwidth, and low latency, the application of millimeter-wave (mmWave) unmanned aerial vehicle (UAV) as emergency aerial base station (ABS) providing services to HetIoT users has become a low-cost and efficient means. However, due to the sensitivity of mmWave to obstacles and jamming, guaranteeing network performance has become a pressing issue. This paper considers a mmWave UAV-assisted HetIoT under jamming conditions, where auxiliary ABSs serve multiple ground users (GUs) who generate a large amount of sensor data. We establish a coverage maximization problem under the constraints of signal-to-interference ratio (SIR) threshold, maximum power of ABSs and maximum number of GUs that the base station can serve, and propose a novel ABS hovering deployment algorithm M-HiAPSO that combines the artificial potential field (APF) method and the improved particle swarm optimization (PSO) algorithm in a hierarchical manner. Specifically, the multi-element APF method is used to characterize the horizontal force between nodes, combined with the improved hierarchical adaptive PSO algorithm to adjust the horizontal position of the ABS to obtain the optimal UAV hovering position and power allocation strategy. Numerical results show that the coverage rate reached 96.2% when the number of iterations was 283, and it can reach up to 99.6%.

Jamming problems and the effects of compliance in dual peg-hole disassembly

Disassembly is a crucial step in remanufacturing and is currently mainly performed by humans. Automating disassembly can reduce labour costs and make remanufacturing more economically attractive. This paper focuses on identifying and characterizing a common disassembly task, dual peg-hole disassembly, with the aim of building a robotic disassembly system for this task. We enumerate the possible contact states and their geometric conditions during the extraction of two studs in a dual peg-hole. This paper focuses on jamming in the extraction and conducts geometrical and quasi-static analyses to determine the boundary conditions of jamming. Based on the analyses, this paper also investigates the role of active compliance as a solution to avoid jamming. We also simulate critical variables and examine key parameters such as the degree of compliance, the location of the compliance centre and initial position errors. Finally, we conduct experimental studies on dual peg-hole extraction with different compliance centres obtained using active compliance.

Analysis of Road Infrastructure Problems in Urban City, Karachi

Road infrastructure is a significant part of the economic development of countries. Better performance of road communication system is significant part of all over the world. Developed countries make a significant effort for designing a well-managed traffic arrangement for the individuals. Furthermore, an efficient transport system is the key element for improving the country's economic conditions. Sustainable and efficient traffic management system is the backbone for humanizing the economic growth of developing countries. In case of Pakistan, Karachi is the main industrial hub for whole country's economy and accommodates enormous number of migrants. Due to this reason the population of city is increasing day by day. This paper presents the current situation of road infrastructure troubles in Karachi. The urban city is facing several numbers of issues that were already documented by researchers such as traffic congestion and road safety problems. On an urgent basis an efficient mass transit system is required to reduce the traffic jam conditions. The transport system of Karachi requires instant proper management rules and designed transport facilities. The aim of the paper is to identify the main traffic problems of the large urban city, Karachi, which is faced by the people in their daily life and to suggest recommendations for reducing the current situation related to traffic management strategies. The research methodology for this paper will be based on qualitative analysis of the road infrastructure troubles that are identified by the individuals through interviews and detailed group meetings.

Effects of polydispersity on the plastic behaviors of dense two-dimensional granular systems under shear.

We study particle-scale motion in sheared highly polydisperse amorphous materials, in which the largest particles are as much as ten times the size of the smallest. We find strikingly different behavior from the more commonly studied amorphous systems with low polydispersity. In particular, an analysis of the nonaffine motion of particles reveals qualitative differences between large and small particles: The smaller particles have dramatically more nonaffine motion, which is induced by the presence of the large particles. We characterize how the nonaffine motion changes from the low- to high-polydispersity regimes. We further demonstrate a quantitative way to distinguish between "large" and "small" particles in systems with broad distributions of particle sizes. A macroscopic consequence of the nonaffine motion is a decrease in the energy dissipation rate for highly polydisperse samples, which is due both to a geometric consequence of the changing jamming conditions for higher polydispersity and to the changing character of nonaffine motion.

On the correctness of using two-dimensional representations in the analysis of cylindrical peg–hole insertion and withdrawal

The cylindrical peg–hole system is a popular model in the study of assembly and disassembly operations. The analysis of peg–hole systems is customarily performed using simplified two-dimensional representations, viz . a vertical sectional view. However, evidence that this simplification accurately represents the system is lacking. This paper investigates the correctness of using two-dimensional instead of three-dimensional models for peg–hole system analysis, studying their geometrical and kinematic equivalence. Geometrical equivalence implies the contact points between the peg and hole are on a vertical sectional view plane. Kinematic equivalence requires that the forces and torques acting on the peg lie in the same sectional plane. The analysis indicates that while geometrical equivalence can be proven, kinematic equivalence is in general not verified. The severity of the error introduced by the two-dimensional simplification depends on the geometrical configuration and kinematic parameters of the peg–hole system. The effects of kinematic non-equivalence on the boundary conditions of jamming and wedging are discussed. The results of the analysis show that a two-dimensional peg–hole model may give wrong predictions on jamming. Also, the extra lateral error of the three-dimensional model reduces the boundary condition and the possibility of peg–hole wedging.

Anti-Jamming Communication Using Slotted Cross Q Learning

Most of the existing intelligent anti-jamming communication algorithms model sensing, learning, and transmission as a serial process, and ideally assume that the duration of sensing and learning timeslots is very short, almost negligible. However, when the jamming environment changes rapidly, the sensing and learning time can no longer be ignored, and the adaptability of the wireless communication system to the time-varying jamming environment will be significantly reduced. To solve this problem, this paper proposes a parallel Q-learning (PQL) algorithm. In the case of long sensing and learning time, by modeling sensing, learning, and transmission as parallel processes, the time that the transmitter remains silent during sensing and learning is reduced. Aiming at the situation that the PQL algorithm is susceptible to jamming when the jamming changes faster, this paper proposes an intelligent anti-jamming algorithm for wireless communication based on Slot Cross Q-learning (SCQL). In the case of rapid change of jamming channel, the system can sense and learn the jamming patterns in multiple successive jamming periods at the same time in the same timeslot, and use multiple Q-tables to learn the jamming patterns in different jamming periods, so as to achieve the effect of reliable communication in the environment with rapid change of jamming. The simulation results show that the jamming collision rate of the proposed algorithm under the condition of intelligent blocking jamming is equivalent to that of the traditional Q-learning (QL), but the timeslot utilization rate is higher. Compared with PQL, the proposed algorithm has the same slot utilization and lower jamming collision rate. Compared with random frequency hopping (RFH) anti-jamming, the proposed algorithm not only has higher timeslot utilization, but also has lower jamming collision rate.

Machine learning‐based anti‐jamming technique at the physical layer

AbstractThe reliance on wireless services to exchange critical data is associated with various threats and attacks, which must be mitigated to ensure integrity and security of those wireless services. Posing a serious challenge to wireless systems, jamming is among these attacks. In order to mitigate jamming, directive antennas are used to minimize the signals that are received from the jammer, while maximizing the received legitimate signal from the authorized transmitter. In this paper, we propose a machine learning‐based anti‐jamming framework to provide a spatially dynamic and instantaneous anti‐jamming performance that is achieved at the physical layer. The proposed framework incorporates a dataset that can be deployed in the hardware of a receiver with a massive Multiple‐Inputs Multiple‐Outputs–(MIMO) antenna. Our extensive performance evaluation results demonstrate the effective performance of the proposed framework in preserving integrity of a massive–MIMO communication system despite the presence of a hostile jammer. Particularly, due to the tabular nature of the generated dataset, tree‐based random forest models achieved the best performance with a signal‐to‐interference‐plus‐noise ratio accuracy of and fast anti‐jamming response in around 1.66 s under sever jamming conditions.

The simulation of ice jam profiles in multi-channel systems using a one-dimensional network model

This paper presents a new modelling method for simulating ice jam profiles in channel networks, implemented in the University of Alberta's public-domain hydrodynamic and river ice process model, River1D. The method includes provisions for handling junctions when solving the ice jam stability equation within a channel network. At junction elements, the solution of the ice jam stability equation is calculated as a function of the junction water discharge ratio. The model was first compared to a series of idealized test cases from a previous study that sought to investigation the impact of islands on ice jam profiles. Seventeen tests were performed in rectangular channels with islands of different length. The results from River1D agreed well with the results from the previous study, showing the same stage reduction along the length of the island and minimum depth at the upstream end of the island. The model was then applied to the Hay River Delta in the Northwest Territories of Canada. The model was first validated for open water scenarios (with surveyed data and 2D modelling results) and was then used to simulate a series of ice jam profiles and validated using data collected within the Hay River Delta during the 2009 breakup. Using just a single value of 0.055 for the under ice jam roughness, the modelled ice jam profiles agreed favourably with the surveyed levels. However, the model did have a tendency to under predict levels in the East Channel for the profile that was collected after an upstream ice jam release wave had passed through the delta. When jam consolidation was considered in the simulation, the model was able to more accurately simulate the surveyed levels. The model results suggest that ice jamming conditions during the 2009 breakup reduced the percentage of flow entering the East Channel compared to open water conditions.

Analysis of outboard cross‐eye jamming using an unmanned platform

To address the problem and reduce the risk wherein a ship-based cross-eye jammer could set a protected ship as a target, an unmanned platform equipped with a jammer is proposed to be used. However, the jamming situation violates the original cross-eye jamming conditions and introduces some new elements. In this regard, the impact of outboard cross-eye jamming in the presence of ship echoes is derived in detail. The analysis shows that the outboard cross-eye jamming combines the characteristics of outboard active and traditional cross-eye jamming gains. It can reduce the standard cross-eye jamming requirement of the jamming-to-signal ratio (JSR) and improve the jamming effect. The phase difference of a cross-eye jammer can be controlled at 0° or 180° to obtain a larger angular positioning deviation based on the JSR requirement, thus providing a theoretical basis for applications of unmanned outboard cross-eye jamming.

Airborne Radar Anti-Jamming Waveform Design Based on Deep Reinforcement Learning.

Airborne radars are susceptible to a large number of clutter, noise and variable jamming signals in the real environment, especially when faced with active main lobe jamming, as the waveform shortcut technology in the traditional regime can no longer meet the actual battlefield radar anti-jamming requirements. Therefore, it is necessary to study anti-main-lobe jamming techniques for airborne radars in complex environments to improve their battlefield survivability. In this paper, we propose an airborne radar waveform design method based on a deep reinforcement learning (DRL) algorithm under clutter and jamming conditions, after previous research on reinforcement-learning (RL)-based airborne radar anti-jamming waveform design methods that have improved the anti-jamming performance of airborne radars. The method uses a Markov decision process (MDP) to describe the complex operating environment of airborne radars, calculates the value of the radar anti-jamming waveform strategy under various jamming states using deep neural networks and designs the optimal anti-jamming waveform strategy for airborne radars based on the duelling double deep Q network (D3QN) algorithm. In addition, the method uses an iterative transformation method (ITM) to generate the time domain signals of the optimal waveform strategy. Simulation results show that the airborne radar waveform designed based on the deep reinforcement learning algorithm proposed in this paper improves the signal-to-jamming plus noise ratio (SJNR) by 2.08 dB and 3.03 dB, and target detection probability by 26.79% and 44.25%, respectively, compared with the waveform designed based on the reinforcement learning algorithm and the conventional linear frequency modulation (LFM) signal at a radar transmit power of 5 W. The airborne radar waveform design method proposed in this paper helps airborne radars to enhance anti-jamming performance in complex environments while further improving target detection performance.

Closed‐form expressions and statistical analysis of constant false alarm rate detection in multiple false target jamming condition

Multiple false target jamming is an effective electronic attack measurement that will deteriorate the detection performance of radar constant false alarm rate (CFAR) detector, but its effects lack sufficient exploration. To solve the problem, an upgraded Bernoulli experiment model (BEM) is established and deduced using direct integral method. Given the number of jamming pulses in different cells, the detection performance can be obtained analytically. BEM can provide a meaningful physical view of CFAR from energy perspective, unveiling the mechanism how jamming deteriorate CFAR performance. Real multiple false target jamming is an extension of BEM where pulses are randomly located. This can be solved by integrating the distribution of jamming pulses into BEM which is named as statistical model (SM). Numerical examples validate that BEM and SM are more accurate and thousands of times faster than Monte-Carlo results. Influential parameters are discussed and some valuable suggestions for radar counter-countermeasurement are obtained.

Analysis of ADAS Radars with Electronic Warfare Perspective.

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

РЕЗУЛЬТАТИ ЕКСПЕРИМЕНТАЛЬНИХ ДОСЛІДЖЕНЬ БАГАТОДІАПАЗОННОГО ІМІТАТОРА ПОСТАНОВНИКА АКТИВНИХ ШУМОВИХ ПЕРЕШКОД

The article provides information on the results of experimental studies of a multi-band hardware and software complex for simulating the action of an active noise jammer, which has been created for the training of operators of radar stations of radio engineering troops. One of the important elements of the professional training of the radar stations operators of the air defense radio engineering forces is their ability to work in difficult target and jamming conditions. The existing simulators for training operators do not fully meet the requirements of the quality of training, since they form only secondary bearing marks on the jammer manufacturer and do not reproduce the situation of deterioration of target detection conditions as a result of the simultaneous action of active and passive noise jammer, as well as the influence of the autocompensator of jammer on the quality of the radar, as it happens in real situation. The offered device for simulating the influence of active jammer has been built according to the modular principle and implemented using software-defined radio technology, which allows to quickly change both the type of signal and its parameters. Power amplifiers and antenna systems have been designed to operate in the 140–190 MHz, 470–900 MHz, and 2500–3500 MHz bands, and for experimental research radar stations in the meter, decimeter, and centimeter wave ranges have been involved. The method of using the simulator has been substantiated, and the conducted studies showed that for radar stations in which the angular beams of the directional pattern have different operating frequencies, there is an additional possibility of simulating the action of the active jammer by changing the frequency of the jammer in the case of operation of the complex directly near the suppression object, where the directional pattern of the radar station antenna has not yet been formed. The method of using the complex both for training sessions and during tactical exercises of the radio technical troops unit to simulate the action of an air-based jamming device or a dropped jamming transmitter has been substantiated. Keywords: active noise jammer; simulation; hardware and software complex; radar station; programmed radio.

Robot assembly theory and simulation of circular-rectangular compound peg-in-hole

AbstractIn this paper, the assembly problem of circular-rectangular compound peg and hole parts in automatic assembly is proposed for the first time, and an automatic assembly method based on six-dimensional force sensor is summarized. Firstly, according to the quasi-static equilibrium condition, the contact states are summarized. It is concluded that there are 7 categories of 44 contact states in insertion stage and the forces conditions to maintain each contact state; Secondly, according to the analysis of the force/moment relationship, the jamming diagram is drawn, and the conditions of jamming are analyzed. Thirdly, the assembly strategy is discussed, including contact state recognition strategy, hole searching strategy, and pose adjustment strategy. Finally, combined with impedance control, the assembly theory is verified in ADAMS, and the assembly with minimum clearance of 0.1 mm is achieved.

Joint channel and power optimisation for multi‐user anti‐jamming communications: A dual mode Q‐learning approach

In view of the anti-tracking-jamming problem, traditional online learning methods usually cannot analyse the jamming behaviour, and find an effective way to prevent the jamming attacks. To cope with these challenges, a novel communication/deception dual mode mechanism is proposed in this paper. Deception users are selected to send high-power signal for jamming attraction, and form collaborative relationships with communication users. The corresponding collaborative anti-jamming model is then constructed as a Markov game to analyse the multi-agent decision. Based on that, a joint channel and power optimisation for multi-user anti-jamming communications based on dual mode Q-learning scheme is proposed. Compared with two traditional online learning algorithms, the proposed DCAJ-QL algorithm effectively achieves 146.5% and 80.4% higher maximum communication rate under tracking jamming conditions, and achieves 40.7% and 53.6% higher maximum communication rate under fixed jamming conditions.

A multi‐agent reinforcement learning anti‐jamming method with partially overlapping channels

This paper investigates the problem of multi-user anti-jamming channel access with partially overlapping channels (POC). Compared with traditional anti-jamming systems that use non-overlapping channels, POC improve the spectral efficiency. However, the partial overlap of channels also brings more serious interference. For this, physical distance and channel separation on the interference intensity under partially overlapping channels are first considered and the malicious jamming and interference among users are formulated as a hierarchical binary model. Secondly, to cope with multi-user decisions under dynamic jamming conditions, the Markov game framework is adopted to analyse the problem. Thirdly, a multi-user collaborative anti-jamming channel selection algorithm based on reinforcement learning is proposed as well as the optimal anti-jamming strategy can be obtained. Finally, the simulation results validate that the proposed algorithm helps users cope with jamming and eliminate mutual interference. Compared with the non-overlapping channel access scheme, the POC access scheme achieves higher network throughput.

Characterization of Carrier Phase-Based Positioning in Real-World Jamming Conditions

GNSS signals arriving at receivers at the surface of the Earth are weak and easily susceptible to interference and jamming. In this paper, the impact of jamming on the reference station in carrier phase-based relative baseline solutions is examined. Several scenarios are investigated in order to assess the robustness of carrier phase-based positioning towards jamming. Among others, these scenarios include a varying baseline length, the use of single- versus dual-frequency observations, and the inclusion of the Galileo and GLONASS constellations to a GPS only solution. The investigations are based on observations recorded at physical reference stations in the Danish TAPAS network during actual jamming incidents, in order to realistically evaluate the impact of real-world jamming on carrier phase-based positioning accuracy. The analyses performed show that, while there are benefits of using observations from several frequencies and constellations in positioning solutions, special care must be taken in solution processing. The selection of which GNSS constellations and observations to include, as well as when they are included, is essential, as blindly adding more jamming-affected observations may lead to worse positioning accuracy.

Research on radar behavior recognition method under the condition of electronic jamming

In the course of ECM, the attacker needs to grasp the working state of the target radar by identifying its behaviors, so as to adopt the best attack strategy. Based on the correlation characteristics between nodes of the networked combat system, the proposed method processes the electromagnetic radiation parameters of the target radar and its cooperative radar, uses the support vector machine multi-classifier algorithm to identify the target radar's behaviors, and determines the influence of jamming on the radar's working states. The simulation results show that the proposed method has higher accuracy than the traditional method which only considers the target radar radiation parameters, and the selection of kernel function and electromagnetic radiation parameters are closely related to the accuracy of behavior recognition.

On Jamming Attacks in Crowdsourced Air Traffic Surveillance

Wireless jamming has been a long-standing issue both in critical infrastructure research and real-world applications, with particular importance in systems that deal with long communication distances and low received signal strength. Air traffic control is one such system, experiencing a rising number of reports of outside interference with the underlying wireless technologies. In this article, we discuss the particular issue of malicious wireless jamming on crowdsourced networks of low-cost ADS-B receivers, which increasingly support modern air traffic management. Using both simulation and laboratory trials, we first show the practical impact of reduced reception and coverage of typical receivers in a crowdsourced sensor network. Following this, we investigate network-wide countermeasures based on redundant coverage, which can defend at most 50.74% of the evaluated real-world network. To improve jamming resilience in nonredundant areas, we analyze and implement a low-cost multichannel receiver and show that it can effectively recover up to 50% of the messages even under heavy jamming conditions.