Jamming Mitigation Research Articles

Mainlobe Deceptive Jammer Mitigation With Multipath in EPC-MIMO Radar Exploiting Matrix Decomposition

Mainlobe Deceptive Jammer Mitigation With Multipath in EPC-MIMO Radar Exploiting Matrix Decomposition

Adaptive Jamming Mitigation in Single-Antenna Receivers With Spectral Analysis and Switchable Filtering

Adaptive Jamming Mitigation in Single-Antenna Receivers With Spectral Analysis and Switchable Filtering

A Cross-eye Jamming Mitigation Approach for Polarized Monopulse Radars

A Cross-eye Jamming Mitigation Approach for Polarized Monopulse Radars

Traffic jam mitigation by the policy of maximum velocity limitation

This study explored whether a policy with maximum velocity limitation prior to each jam point in a traffic flow system can mitigate jam situations in a highway. To quantify this question, a new cellular automata traffic model based on the Revised S-NFS model was established. We perused two specific scenarios: a jam naturally brought by a high traffic density, and one brought by a lane-closed section placed as an explicit bottleneck. The result of multi-agent simulation (MAS) reveals that such maximum velocity limitation policy can certainly mitigate jam situations when each jam is naturally bought up not by a bottleneck, as proved by several statistics, and cannot improve the traffic flux.

Application of Artificial Intelligence (AI) to Enhance Satellite Security

The security of satellite systems is paramount for maintaining the integrity and reliability of critical infrastructure and national defense. This paper explores the application of artificial intelligence (AI) to enhance satellite security. AI technologies can significantly improve anomaly detection, cyber security, signal jamming mitigation, space situational awareness, predictive maintenance, secure communication, and autonomous satellite operations. By leveraging machine learning algorithms, AI can detect and respond to cyber threats in real-time, differentiate between benign and malicious signal interference, and predict potential system failures. Additionally, AI enhances space situational awareness by processing vast amounts of sensor data to track objects in space and predict collision risks. The integration of AI with encryption techniques and block chain technology further strengthens the security framework, ensuring robust and tamper-proof satellite communications. This multidisciplinary approach demonstrates the potential of AI to provide dynamic and proactive defense mechanisms, ensuring the continuous and secure operation of satellite systems in an increasingly complex and threat-prone environment.

Performance analysis of subspace projection algorithm with respect to projection length for GNSS jamming mitigation

Non-stationary jamming signals broadcast by jammers severely threaten the reliability of global navigation satellite systems (GNSS). The instantaneous frequency (IF) based subspace projection algorithm is an attractive solution for GNSS jamming mitigation. However, its theoretical performance analysis is rare and not well discussed. To better apply subspace projection, we develop the theoretical post-correlation signal-to-interference-plus-noise power ratio (SINR) of receivers incorporating subspace projection to facilitate performance analysis. Different from existing work, this paper assumes that IF errors are independent and identically distributed instead of instantaneous phase errors, which is more reasonable. Numerical simulation results validate the derived theoretical SINR. The results show that the performance of subspace projection highly depends on the selection of projection length. Subspace projection with a well-designed projection length can perform much better than a conventional long projection length. Utilizing the theoretical SINR, the jamming mitigation performance of subspace projection with different projection lengths can be quickly evaluated, which provides an important theoretical guidance for the application of the algorithm.

Active Jamming Mitigation for Short-Range Detection System

Active Jamming Mitigation for Short-Range Detection System

Narrowband Jamming Mitigation Based on Multi-Resolution Analysis for Land Vehicles

Narrowband Jamming Mitigation Based on Multi-Resolution Analysis for Land Vehicles

Interpolation-Based Subspace Projection for Sparsely Sampled Non-Stationary Jamming Mitigation

Non-stationary jamming signals broadcasted by jammers seriously affect the reliability of Global Navigation Satellite Systems (GNSS). What is worse, GNSS signals may be sparsely sampled or missing some samples in some situations. In this context, applying conventional anti-jam methods can lead to interference leakage. This letter proposes an interpolation-based subspace projection algorithm for non-stationary jamming mitigation in the presence of missing samples. To reduce interference leakage caused by missing samples, we propose to perform interpolation before applying subspace projection. The effectiveness of the algorithm is analyzed briefly. Numerical simulations show that the proposed algorithm can suppress interference very well in the presence of missing samples.

A Defensive Strategy Against Beam Training Attack in 5G mmWave Networks for Manufacturing

Millimeter-wave (mmWave) carriers are an essential building block of fifth-generation (5G) systems. Satisfactory performance of the communications over the mmWave spectrum requires an alignment between the signal beam of the transmitter and receiver, achieved via beam training protocols. Nevertheless, beam training is vulnerable to jamming attacks, where the attacker intends to send jamming signals over different spatial directions to confuse legitimate nodes. This paper focuses on defending against this attack in smart factories where a moving Automated Guided Vehicle (AGV) communicates with a base station via a mmWave carrier. We introduce a defensive strategy to cope with jamming attacks, including two stages: jamming detection and jamming mitigation. Developed based on autoencoders, both algorithms can learn the characteristics/features of the received signals at the AGV. They can be employed consecutively before performing the downlink data transmission. In particular, once a jamming attack is identified, the jamming mitigation can be utilized to retrieve the corrupted received signal strength vector, allowing a better decision during the beam training operation. In addition, the proposed algorithm is straightforward and fully compliant with the existing beam training protocols in 5G New Radio. The numerical results show that not only the proposed defensive strategy can capture more than 80% of attack events, but it also improves the average signal-to-interference-plus-noise-ratio significantly, i.e., up to 15 dB.

Jam Mitigation for Autonomous Convoys via Behavior-Based Robotics

Autonomous ground vehicle convoys heavily rely on wireless communications to perform leader-follower operations, which make them particularly vulnerable to denial-of-service attacks such as jamming. To mitigate the effects of jamming on autonomous convoys, this paper proposes a behavior-based architecture, called the Behavior Manager, that utilizes layered costmaps and vector field histogram motion planning to implement motor schema behaviors. Using our proposed Behavior Manager, multiple behaviors can be created to form a convoy controller assemblage capable of continuing convoy operations while under a jamming attack. To measure the performance of our proposed solution to jammed autonomous convoying, simulated convoy runs are performed on multiple path plans under different types of jamming attacks, using both the assemblage and a basic delayed follower convoy controller. Extensive simulation results demonstrated that our proposed solution, the Behavior Manager, can be leveraged to dramatically improve the robustness of autonomous convoys when faced with jamming attacks and can be further extended due to its modular nature to combat other types of attacks through the development of additional behaviors and assemblages. When comparing the performance of the Behavior Manager convoy to that of the basic convoy controller, improvements were seen across all jammer types and path plans, ranging from 13.33% to 86.61% reductions in path error.

Mitigation of transmission line jamming by price intrusion technique in competitive electricity market

ABSTRACT In the past years of the electric market, very big corporation companies enjoyed domination or monopoly and takes complete responsibility for generating the electric power. In the new-age market electricity grid faces several techno-commercial challenges like power outage, conductor snag, equipment rundown, transmission congestion, financial constraint, price settlement issue, etc, so this cause transfer of generated electricity from generating station to load becomes a challenge. Also, transmission jamming or congestion is an issue that leads to catastrophe if not mitigated. Therefore to avoid such issues different techno-financial methods are adopted in a particular electricity zone with a large network. In this paper, we adopted an innovative technique to control the electricity transfer limit. Here an analytic tool based on the price-sensitive algorithm is developed to determine a suitable combination of Financial Transmission Rights (FTR) and Location-based low prices with curtailments in a competitive electricity market. The significant objective of this technique is to minimise the dispatch of low-cost generators and overall operational expenses thereby mitigating the traffic issue in a particular load node or zone. Finally, the transmission congestion mitigation is discussed with price sensitivity technique and with a proper financial mechanism like FTR with location pricing in a particular zone.

High-Resolution Spectral Estimation for Continuous Wave Jamming Mitigation of GNSS Signals in Autonomous Vehicles

Future autonomous vehicles will rely mainly on global navigation satellite system (GNSS) receivers for positioning services. However, GNSS cannot maintain an accurate, continuous and reliable navigation solution in the presence of jamming. The widespread availability of in-car jammers or personal privacy devices (PPDs) made GNSS receivers an attractive target for signal jamming. Jammers not only jeopardize current positioning and timing services; they can indeed endanger the safety of the evolving intelligent transportation, autonomous road vehicles and critical infrastructure. The disruption of GNSS signal in some applications, especially safety-critical ones can lead to crucial consequences and risks such as loss of time synchronization and potential loss of life, to name a few. Thus, it is essential for future autonomous vehicles and transport service providers to deploy reliable GNSS anti-jamming techniques. This paper introduces a novel anti-jamming technique based on a high-resolution spectral estimation that utilizes fast orthogonal search (FOS) algorithm in which the jamming signal is modeled using a set of candidate functions and then eliminated from the received signal. The performance of the proposed method is assessed using experiments obtained from Spirent_TM GSS6700 simulation system. The jamming signal is either obtained from a real jammer or simulated using interference signal generator that is connected to Spirent_TM system. The results showed that the developed anti-jamming algorithm was able to successfully suppress the continuous wave (CW) interference signal, thus, the performance of the acquisition, tracking and navigation modules within a GPS software receiver were all enhanced.

Advanced protocols for the mitigation of friendly jamming in mobile ad-hoc networks

Mobile Ad-hoc Networks (MANETs) play a critical role for wireless communications within mission-critical applications. Wireless communications have the drawback of being susceptible to jamming. Jamming disturbs the normal reception of signals on the physical layer. While MANETs can adapt to continuous jamming, intermittent jamming can seriously disrupt the routing protocol and the traffic flow. In the intermittent case, the network topology during non-jamming is generally quite different from that during jamming. Much of the recent work on jamming mitigation has focused on how to adjust the transmitter-receiver system once an adversarial jamming attack has been detected. However, jamming need not be only adversarial in nature. Friendly jammers are supposed to disturb the adversarial networks but not the friendly ones. In this paper, we propose jamming-aware routing and MAC protocols for the friendly jamming scenario, where the jamming schedule is known to the friendly mobile nodes but hidden from all adversarial ones. In one scheme, the routing and MAC protocols freeze during jamming but resume during non-jamming. In another scheme, the routing protocol uses two sub-protocols: one for jamming and another for non-jamming. We have named the friendly-jamming-aware routing protocols as JOLSR, because their implementations have been based on OLSR, and the friendly-jamming-aware MAC protocol as JTDMA, as its implementation has been based on TDMA. We have shown through extensive simulations that these proposed protocols can significantly improve the packet delivery ratio and other metrics compared to off-the-shelf proactive unicast and reactive multicast routing protocols and a schedule based (TDMA) MAC protocol.

Hybrid anti‐jamming algorithm for Indian Regional Navigation Satellite System receivers using variational mode decomposition and wavelet packet transform

SummaryContinuous wave interference has found to be one of the major menaces that deter the performance of the Indian Regional Navigation Satellite System (IRNSS) receivers for seamless positioning and navigation. In this paper, a novel hybrid jamming mitigation method based on variational mode decomposition (VMD) and wavelet packet transform (WPT) has been proposed. VMD is used to decompose the received signal into various components referred to as intrinsic mode functions (IMFs). To have an optimum decomposition of the signal, the mode decomposition number of VMD is determined by employing the kurtosis principle. Then, a threshold based on the mutual information index is constructed to differentiate the information dominant and interference dominant modes. The information dominant modes are then processed by the wavelet packet filter to eliminate the remaining effects of jamming and noise present. Finally, the filtered modes and the retained modes are used to reconstruct the desired signal. The performance of the technique is analyzed in the presence of single‐tone, multitone, and chirp jamming scenarios with different levels of jamming power. The proposed method has been tested by simulations in comparison with the standard algorithms. Results show that the proposed hybrid algorithm outperforms the standard algorithms in reducing the jamming signal effectively.

Securing ZigBee Communications Against Constant Jamming Attack Using Neural Network

ZigBee is a wireless communication technology that has been widely used to provide low-bandwidth wireless services for Internet-of-Things applications, such as building automation, medical data collection, and industrial equipment control. As ZigBee operates in the industrial, scientific and medical radio frequency bands, it may suffer from unintentional interference from coexisting radio devices (e.g., WiFi and Bluetooth) and/or radio jamming attacks from malicious devices. Although many results have been produced to enhance ZigBee security, there is no technique that can secure ZigBee against jamming attack. In this article, we propose a new ZigBee receiver by leveraging MIMO technology, which is capable of decoding its desired signal in the presence of constant jamming attack. The enabler is a learning-based jamming mitigation method, which can mitigate the unknown interference using an optimized neural network. We have built a prototype of our proposed ZigBee receiver on a wireless testbed. Experimental results show that it is capable of decoding its packets in the face of 20-dB stronger jamming. The proposed ZigBee receiver offers an average of 26.7-dB jamming mitigation capability compared to off-the-shelf ZigBee receivers.

Channel-Hopping-Based Jamming Mitigation in Wireless LAN Considering Throughput and Fairness

Because of the popularity of wireless technology, jamming attack is one of the most critical issues in wireless networks. Wireless jamming attack is one type of denial-of-service attacks where attackers send malicious messages or signal on a legitimate channel by causing intentional interference in the network. In order to avoid jamming attacks, various jamming defense schemes have been proposed. One of the popular methods is a channel-hopping scheme. However, the main challenge of this method is generating a common channel number between the users and the access point without leaking that information to the jammer. We propose a new channel-hopping scheme where the access point shares a separate key with each user to isolate the damage on the network when a key has been compromised, while maintaining high throughput and fairness. We evaluate the proposed scheme through experiment on a test bed.

A Method for Realizing Antifollower Jamming in Communication and Its Experimental Verification

The technical difficulty of antifollower jamming in communication systems is a wide concern in the peer. In order to solve the problem of difficulty to achieve antifollower jamming, a new identification method of follower jamming is proposed in this paper based on the characteristics of it and then follower jamming is cancelled out. A hardware-in-the-loop simulation platform is built by using FPGA. Then, experimental verification for mitigating performance of follower jamming is conducted based on the platform and the proposed method. Results show that signal-interference ratio (SIR) promotion is different for different jamming frequencies and the jamming mitigation performance is affected by interference intensity. The average SIR promotion can reach 10 dB when variance of jamming signal is between 0.75 and 1.5. In other cases, average SIR promotion is less than 10 dB. The proposed suppression method provides a useful way to antifollower jamming in frequency hopping (FH) communication.

Adaptive Complex Filtering for Narrowband Jamming Mitigation in Resource-Constrained Wireless Networks

Jamming attacks present a major challenge for the physical layer security of wireless communication systems. Among the large number of existing methods for jamming mitigation, filtering is a simple but promisingly effective solution that can be applied in resource-constrained and low-power wireless networks. In this article, a first-order adaptive complex narrowband notch filter is proposed for use against high-power narrowband jamming attacks. The central frequency of the filter is adaptively adjustable to match the interfering frequency. This enables the proposed solution to perform effectively in the presence of a jammer whose frequency varies in fixed or random time periods. The simulation results demonstrate the filter's behavior and the efficiency of the proposed technique.

Counter-measures to spoofing and jamming of drone signals

Technological revolution has done wonders in Aeronautics. With the evolution Unmanned Aerial vehicle, not only the military sector but also the commercial and industrial sectors use drones for various purposes. The global Unmanned Aerial Vehicle (UAV) market size is projected to reach $133.5 billion by 2026, from $25.9 billion in 2019, at a compound annual growth rate of 26.4% during 2021-2026. As the technology usage increases, its security plays a vital role in research. The idea behind this paper is to discuss definite and efficient countermeasures to spoofing and jamming of drone signals. The detection and mitigation of spoofing and jamming using new cyber security techniques including blockchain, deep learning using multiclass SVM, Co-operative localisation, Hardware sandboxing and Visual Odometry are explored. It also presents a deep analysis of all techniques along with the pros and cons of each method.