Frequency Hopping Research Articles

Classification and Identification of Frequency-Hopping Signals Based on Jacobi Salient Map for Adversarial Sample Attack Approach

Frequency-hopping (FH) communication adversarial research is a key area in modern electronic countermeasures. To address the challenge posed by interfering parties that use deep neural networks (DNNs) to classify and identify multiple intercepted FH signals—enabling targeted interference and degrading communication performance—this paper presents a batch feature point targetless adversarial sample generation method based on the Jacobi saliency map (BPNT-JSMA). This method builds on the traditional JSMA to generate feature saliency maps, selects the top 8% of salient feature points in batches for perturbation, and increases the perturbation limit to restrict the extreme values of single-point perturbations. Experimental results in a white-box environment show that, compared with the traditional JSMA method, BPNT-JSMA not only maintains a high attack success rate but also enhances attack efficiency and improves the stealthiness of the adversarial samples.

Remotely Controlled Armed Surveillance Rover

A remotely operated ground vehicle was designed and developed for use in counter terrorism and counter-insurgency operations by the Indian Army. The Rover can traverse difficult terrain, extreme slopes, inspect suspicious objects (e.g. improvised explosive devices) with a robotic weapon with a camera(even when hidden under a bridge), and give visual feedback to an operator away at a safe distance of certain range. It can be operated using mobile and can be self-triggered when a command is given. Militaries are now equipped with various types of rovers. Rover for assistance and spy purposes are developing. This project represents an application of Rover in the military. This rover is 4-wheeled developed on a rocker-bogie mechanism. According torecent Rover developments, rovers with rocker-bogie mechanismscan glide on rough surfaces, sand, and loose soil easily. Thedegree of freedom for the rover is 4 with the ability to rotate 360°.This rover is equipped with frequency hopping which makes it ananti-hack device. This project is useful for attacking the opponentsin the war without losing our army officers. So by using thisproject we can do war without losing human life on our side.

Generation of frequency-shift keying (FSK) and amplitude-shift keying (ASK) RF signals by diode-tuned Fourier domain mode-locked opto-electronic oscillator

An approach to the generation of frequency-shift keying (FSK) and amplitude-shift keying (ASK) RF signals with a diode-tuned Fourier domain mode-locked opto-electronic oscillator (FDML OEO) is proposed and demonstrated. We use a low-cost varactor diode tuned phase shifter to form a high speed tunable bandpass filter (TBF) to implement the FDML-OEO. When a square wave modulation signal is used to drive the TBF, FSK RF signals are generated, with the flexibility to easily change the center frequency and tuning bandwidth of the FSK signals. For the ASK RF signal generation, a band-pass filter (BPF) with a bandwidth less than the TBF tuning range is added to the FDML OEO RF feedback loop. When the TBF center frequency hops in and out of the BPF bandwidth within a mode locking period, the FDML OEO generates ASK RF signals. The phase noises of the FSK and ASK RF signals generated by our FDML-OEO are both measured to be −123dBc/Hz at 10 kHz offset frequency. The key significance of this approach is that no microwave source is required to generate the ASK signal and reconfigurable FSK and signals, which may find wide applications in future radar and communications systems.

An adaptive hexagonal deployment model for resilient wireless sensor networks in precision agriculture

This study presents an innovative hexagonal deployment model designed specifically for wireless sensor networks (WSNs) with a primary application in precision agriculture. The proposed protocol integrates advanced features, notably an adaptive frequency-hopping spread spectrum (AFHSS) mechanism and a decentralized real-time adaptation strategy to optimize data transmission in dynamic agricultural environments. The simulation study, conducted in diverse terrains with realistic sensor node distributions, meticulously evaluates the protocol’s performance using comprehensive Quality of Service (QoS) metrics. The hexagonal deployment model operates by strategically positioning sensor nodes in a hexagonal grid pattern, ensuring uniform coverage of the agricultural field. The AFHSS mechanism dynamically adjusts frequency channels, mitigating interference and fortifying the network’s robustness against external disruptions. Complementing this, the decentralized real-time adaptation empowers individual nodes to autonomously respond to the ever-changing environmental conditions, optimizing data transmission efficiency. Quantitative results from the simulations exhibit outstanding performance metrics. The protocol achieves an average latency of 50 milliseconds, a packet loss rate below 2%, a success rate exceeding 95%, and highly efficient obstacle management, with adjusted nodes accounting for less than 5%. These compelling outcomes underscore the protocol’s exceptional ability to deliver responsive and reliable data transmission, positioning it as a promising solution for enhancing environmental monitoring in precision agriculture. This study provides quantitative evidence of the protocol’s prowess and delves into the nuanced working mechanisms, offering a deeper understanding of its potential impact. The findings contribute significant insights to the field, serving as a robust foundation for researchers and practitioners engaged in designing and implementing resilient WSNs tailored for precision agriculture applications.

A Time-Frequency Domain Analysis Method for Variable Frequency Hopping Signal.

A variable frequency hopping (VFH) signal is a kind of frequency hopping (FH) signal that varies both in frequency and dwell time. However, in radio surveillance, the existing methods for unidentified signals using VFH cannot be effectively handled. In this paper, we proposed an improved joint analysis method based on time-frequency domain features, which adopts multi-level processing to solve the time-frequency domain feature analysis problem of the VFH signal. First, the received signal is pre-processed by Short-Time Fourier Transform (STFT) and binarization, and a highly discriminative time-frequency image is obtained; then, the fixed frequency signal is removed based on the feature of connected domains, and the conventional frequency hopping (CFH) signal is removed by density-based spatial clustering of applications with noise (DBSCAN); finally, the overlapping region is cropped by the joint energy peak time-domain continuity properties. After the above multi-level joint processing method, the problem of VFH signal processing is effectively solved. The simulation result shows that the Mean Square Error (MSE) between the output results and the time-frequency image of the original VFH signal tends to be close to 0 when the Signal-to-Noise ratio (SNR) is 5 dB.

Long-Time Coherent Integration Method for Passive Bistatic Radar Using Frequency Hopping Signals.

Long-time coherent integration using frequency hopping signals is a challenging problem for passive bistatic radar due to its frequency hopping characteristics. Apart from range walk, range curve, and Doppler frequency migration, Doppler diffusion caused by frequency hopping characteristics occurs within the observation time, which also lowers the detection performance. To deal with this problem, a novel coherent integration method for frequency hopping signals based on passive bistatic radar is proposed in this paper. In this novel method, range curve and range walk are eliminated by applying generalized Keystone transform. Then, Doppler frequency migration caused by the target's acceleration is compensated for by a parameter search with a designed search scope. Finally, Doppler frequency migration caused by frequency hopping characteristics is compensated for by designing a new acceleration compensation function and a revised rotation factor for Fourier transform. Since migration effects caused by frequency hopping characteristics are considered and compensated for when using frequency hopping signals, the weak target echo can be better integrated in the observation time compared to when using the existing methods. The simulation results and performance analysis illustrate the effectiveness of the proposed method.

Energy Performance of LR-FHSS: Analysis and Evaluation.

Long-range frequency hopping spread spectrum (LR-FHSS) is a pivotal advancement in the LoRaWAN protocol that is designed to enhance the network's capacity and robustness, particularly in densely populated environments. Although energy consumption is paramount in LoRaWAN-based end devices, this is the first study in the literature, to our knowledge, that models the impact of this novel mechanism on energy consumption. In this article, we provide a comprehensive energy consumption analytical model of LR-FHSS, focusing on three critical metrics: average current consumption, battery lifetime, and energy efficiency of data transmission. The model is based on measurements performed on real hardware in a fully operational LR-FHSS network. While in our evaluation, LR-FHSS can show worse consumption figures than LoRa, we find that with optimal configuration, the battery lifetime of LR-FHSS end devices can reach 2.5 years for a 50 min notification period. For the most energy-efficient payload size, this lifespan can be extended to a theoretical maximum of up to 16 years with a one-day notification interval using a cell-coin battery.

Low‐complexity algorithms for generating frequency hopping sequences with good aperiodic hamming correlation property

AbstractIn this letter, novel methods for quickly generating frequency hopping (FH) sequences with good out‐of‐phase peak aperiodic Hamming auto‐correlation (PAHAC) property are proposed. Compared with brute‐force search algorithm, the proposed algorithms have an obvious advantage on their time complexity. Results show that the algorithms can generate FH sequences with optimal/quasi‐optimal PAHAC performance in all tested cases.

Multiple‐nodes based cooperative jamming detection for reactive follower jamming in ISAC

AbstractAccurate jamming detection is a prerequisite and important support for efficient anti‐jamming communication in integrated sensing and communications. In recent years, the reactive follower jamming, characterized by the high jamming efficiency and the difficulty of detection, is seen as the main opponent for frequency hopping spread spectrum communication, which poses a threat to the reliability of wireless communication. Based on the background, a multiple‐nodes based cooperative jamming detection scheme is proposed for accurately detecting the reactive follower jamming. Specifically, the secondary nodes send the average energy of the suspected attacked symbols to the primary user as the uplink data in each detection period, and then the detection result is provided by the detection threshold. The optimal detection threshold is derived for the primary user according to the uplink data and channel conditions. In addition, the theoretical probability of detection under the optimal threshold is derived, and the complexity of the scheme is analysed. Simulation results show that the proposed multiple‐nodes based cooperative jamming detection scheme for reactive follower jamming can effectively improve the probability of detection.

Unveiling robust security: Chaotic maps for frequency hopping implementation in FPGA

Frequency hopping is a main technique for wireless communication, avoiding interference and interception. This paper provides novel hardware design for frequency-hopping pseudorandom bit generator (PRBG).PRBG design by chaotic maps on FPGA.Two proposed methods in this work first combine chaotic maps in a cascade manner called fixed point cascade chaotic maps (FPCCM-FHSS), and second, the conjunction of chaotic maps done in an XORed manner called fixed point an XOR chaotic method (FPXORCM-FHSS).The results were the first eight NIST randomness tests.Frequency indicates that all p-values larger than 0.01 are needed to achieve better randomness,Second and third were die-hard tests, many distribution tests with significant p-values (p <0.01) that meet high standards of statistical randomness, making them suitable for channel security.Last were the FPGA results between the proposed methods for speed and hardware resources).The works implemented on XILINX ZC702 achieved 2 Gbps to meet the speed requirements of the change of the carrier frequency.

The Fast and Reliable Detection of Multiple Narrowband FH Signals: A Practical Framework.

Frequency hopping (FH) is a well-known technique that is commonly used in communication systems owing to its many advantages, including its strong anti-jamming capability. In this technique, basically, radio signals are transmitted by switching the carrier between different frequency channels. As a result, the FH signal is not stationary; hence, its spectrum is expected to change over time. Therefore, the task of detection and parameter estimation of FH signals is very challenging in practice. To address this challenge, the study presented in this article proposes a method that detects and estimates the parameters of multiple narrowband FH signals. In the proposed method, first, short-time Fourier transform (STFT) is utilized to analyze FH signals, and a practical binarization process based on thresholding is used to detect FH signals. Then, a new algorithm is proposed to ensure that the center frequencies of the detected signals are successfully separated. Next, another algorithm is proposed to estimate the parameters of the detected signals. After estimating the parameters for the entire spectrum, an approach is used to detect FH signals. Lastly, the hop-clustering process is applied to separate the hops into groups without time overlap. The simulation results show that the proposed method can be an efficient way for the fast and accurate parameter estimation and detection of multiple narrowband FH signals.

Frequency-hopping along with resolution-turning for fast and enhanced reconstruction in ultrasound tomography

The distorted Born iterative (DBI) method is considered to obtain images with high-contrast and resolution. Besides satisfying the Born approximation condition, the frequency-hopping (FH) technique is necessary to gradually update the sound contrast from the first iteration and progress to the actual sound contrast of the imaged object in subsequent iterations. Inspired by the fact that the higher the frequency, the higher the resolution. Because low-frequency allows for low-resolution object imaging, hence for high-resolution imaging requirements, using low-frequency to possess a high-resolution image from the first iteration will be less efficient. For an effective reconstruction, the object’s resolution at low frequencies should be small. And similarly, with high frequencies, the object resolution should be larger. Therefore, in this paper, the FH, and the resolution-turning (RT) technique are proposed to obtain object images with high-contrast and -resolution. The convergence speed in the initial iterations is rapidly achieved by utilizing low frequency in the frequency-turning technique and low image resolution in the resolution-turning technique. It is crucial to ensure accurate object reconstruction for subsequent iterations. The desired spatial resolution is attained by employing high frequency and large image resolution. The resolution-turning distorted Born iterative (RT-DBI) and frequency-hopping distorted Born iterative (FH-DBI) solutions are thoroughly investigated to exploit their best performance. This makes sense because if it is not good to choose the number of iterations for the frequency f1 in FH-DBI and for the resolution of N1 × N1 in RT-DBI, then these solutions give even worse quality than traditional DBI. After that, the RT-FH-DBI integration was investigated in two sub-solutions. We found that the lower frequency f1 used both before and after the RT would get the best performance. Consequently, compared to the traditional DBI approaches, the normalized error and total runtime for the reconstruction process were dramatically decreased, at 83.6% and 18.6%, respectively. Besides fast and quality imaging, the proposed solution RT-FH-DBI is promised to produce high-contrast and high-resolution object images, aiming at object reconstruction at the biological tissue. The development of 3D imaging and experimental verification will be studied further.

Intelligent decision-making for a “Three-Variable” frequency-hopping pattern based on OC-CDRL

The frequency hopping pattern of the existing frequency hopping communication system is not designed according to the electromagnetic interference environment, resulting in blind anti-jamming. Therefore, to address this problem, a “three-variable” frequency-hopping pattern is proposed, where the frequency, hopping rate, and instantaneous bandwidth of the frequency-hopping signal vary randomly based on the background electromagnetic interference. The decision-making problem of the “three-variable” frequency-hopping pattern is modeled as a Markov decision process (MDP) by constructing the state-action-reward tuple. The designed frequency varies continuously within a small frequency band selected from a pseudo-random sequence to alleviate the problem of dimension explosion in decision-making. At the same time, discrete values for the hopping rate and instantaneous bandwidth are designed. To solve this MDP problem efficiently, a combined deep reinforcement learning algorithm (OC-CDRL) based on optimistic exploration and conservative estimation is proposed, which combines the features of TD3 and D3QN algorithms and designs the corresponding states, actions, and rewards to deal with continuous and discrete action spaces, respectively. To address the problem that the D3QN algorithm tends to fall into local optimal solutions, an optimistic exploration strategy (OES) for action selection is proposed to improve the degree of exploration. Moreover, the loss function is improved by conservatively estimating state–action pairs outside the experience replay buffer, reducing the overestimation of the optimistic action-value function and increasing the stability and convergence of the algorithm. Comparative simulation results of the algorithms in different electromagnetic interference environments show that the OC-CDRL algorithm effectively avoids most regions with higher interference and has better adaptability and anti-jamming capability.

Design and implementation of Frequency Hopping Spread Spectrum (FHSS) system using FPGA

Design and implementation of Frequency Hopping Spread Spectrum (FHSS) system using FPGA

Adaptive Joint Carrier and DOA Estimations of FHSS Signals Based on Knowledge-Enhanced Compressed Measurements and Deep Learning.

As one of the most widely used spread spectrum techniques, the frequency-hopping spread spectrum (FHSS) has been widely adopted in both civilian and military secure communications. In this technique, the carrier frequency of the signal hops pseudo-randomly over a large range, compared to the baseband. To capture an FHSS signal, conventional non-cooperative receivers without knowledge of the carrier have to operate at a high sampling rate covering the entire FHSS hopping range, according to the Nyquist sampling theorem. In this paper, we propose an adaptive compressed method for joint carrier and direction of arrival (DOA) estimations of FHSS signals, enabling subsequent non-cooperative processing. The compressed measurement kernels (i.e., non-zero entries in the sensing matrix) have been adaptively designed based on the posterior knowledge of the signal and task-specific information optimization. Moreover, a deep neural network has been designed to ensure the efficiency of the measurement kernel design process. Finally, the signal carrier and DOA are estimated based on the measurement data. Through simulations, the performance of the adaptively designed measurement kernels is proved to be improved over the random measurement kernels. In addition, the proposed method is shown to outperform the compressed methods in the literature.

Enhancing energy efficiency in tyre pressure and temperature monitoring systems

This study addresses the pivotal challenge of enhancing power efficiency in tyre pressure and temperature monitoring systems (TPMS) for heavy vehicles and trailers. Employing field-programmable gate arrays (FPGA) and adaptive channel frequency hopping in bluetooth low energy (BLE) communication, the research focuses on mitigating power consumption issues specific to heavy vehicles with multiple tyres. The proposed solution incorporates strategic BLE channel blocking and adaptive frequency hopping on the FPGA platform to alleviate channel congestion and interference, ultimately reducing TPMS power consumption. The FPGA's adaptability tailors frequency hopping strategies to automotive TPMS nuances, optimizing channel selection and minimizing energy-intensive processes. Empirical results showcase a significant reduction in power consumption, with the TPMS operating at 100 MHz during active mode consuming 66 mW, dropping to 11 mW in sleep mode, and reaching 0 mW in hibernate mode for the majority of operational time. This research establishes a practical FPGA-based approach for power optimization in commercial TPMS, promising heightened reliability, safety improvements, and environmental impact reduction in the automotive sector.

AK-MADDPG-Based Antijamming Strategy Design Method for Frequency Agile Radar.

Frequency agility refers to the rapid variation of the carrier frequency of adjacent pulses, which is an effective radar active antijamming method against frequency spot jamming. Variation patterns of traditional pseudo-random frequency hopping methods are susceptible to analysis and decryption, rendering them ineffective against increasingly sophisticated jamming strategies. Although existing reinforcement learning-based methods can adaptively optimize frequency hopping strategies, they are limited in adapting to the diversity and dynamics of jamming strategies, resulting in poor performance in the face of complex unknown jamming strategies. This paper proposes an AK-MADDPG (Adaptive K-th order history-based Multi-Agent Deep Deterministic Policy Gradient) method for designing frequency hopping strategies in frequency agile radar. Signal pulses within a coherent processing interval are treated as agents, learning to optimize their hopping strategies in the case of unknown jamming strategies. Agents dynamically adjust their carrier frequencies to evade jamming and collaborate with others to enhance antijamming efficacy. This approach exploits cooperative relationships among the pulses, providing additional information for optimized frequency hopping strategies. In addition, an adaptive K-th order history method has been introduced into the algorithm to capture long-term dependencies in sequential data. Simulation results demonstrate the superior performance of the proposed method.

Retraction Note: Enhancing throughput using channel access priorities in frequency hopping network using federated learning

Retraction Note: Enhancing throughput using channel access priorities in frequency hopping network using federated learning

Carrier Phase Dual One-Way Ranging Method Based on a Frequency Hopping Signal

With the development of navigation satellite constellation systems, to improve navigation service and orbit determination performance, the accuracy requirements for maintaining temporal references have increased rapidly. Among the current navigation satellites, a dual one-way ranging (DOWR) approach based on intersatellite links (ISLs) is widely adopted in the BeiDou system and global positioning system (GPS) to transmit satellite time reference information. However, the accuracy of DOWR is restricted by the pseudonoise (PN) code rate. To improve the accuracy of DOWR, the PN code measurement must be replaced by the carrier phase measurement. This paper introduces an algorithm that utilizes frequency hopping to achieve carrier phase ranging. In addition to the high-precision advantages of carrier phase measurements, the anti-interference performance of the ranging signal is also improved due to the characteristics of the frequency hopping signal itself. Ultimately, at a carrier-to-noise ratio of 40 dB-Hz, the measurement accuracy is 9.54 μm, while the PN code measurement accuracy in the same environment is 0.13 m. As the carrier-to-noise ratio increases, the measurement accuracy further improves.

A back‐to‐back coordination‐based learning scheme for deceiving reactive jammers in distributed networks

AbstractReactive jammers select jamming strategies according to the users’ responses; thus, conventional anti‐jamming methods such as frequency hopping are inadequate to defeat the jamming attack. In this article, the authors propose a novel uncoupled deception scheme to trap the reactive jammer into attacking a decoy channel in distributed networks. Specifically, the authors design a multi‐functional network utility for every user to mislead the jammer with a minimum energy consumption while achieving the highest network throughput. Based on the network utility, the anti‐jamming problem is formulated as an exact potential game such that the existence of Nash equilibrium can be guaranteed theoretically. The authors further propose a back‐to‐back coordination‐based learning algorithm to reach the optimal channel selection and power adaption in a non‐cooperative way. To alleviate the lack of mutual information exchange, the back‐to‐back coordination mechanism derives all users to deceive the jammer by inferring others’ strategies based on a shared belief. Simulation results show that the proposed algorithm yields higher network throughput and efficiency‐cost ratio compared to the state‐of‐the‐art cooperative schemes.