Complex Interference Environment Research Articles

Self-Supervised Transformers for Unsupervised SAR Complex Interference Detection Using Canny Edge Detector

As the electromagnetic environment becomes increasingly complex, a synthetic aperture radar (SAR) system with wideband active transmission and reception is vulnerable to interference from devices at the same frequency. SAR interference detection using the transform domain has become a research hotspot in recent years. However, existing transform domain interference detection methods exhibit unsatisfactory performance in complex interference environments. Moreover, most of them rely on label information, while existing publicly available interference datasets are limited. To solve these problems, this paper proposes an SAR unsupervised interference detection model that combines Canny edge detection with vision transformer (CEVIT). Using a time–frequency spectrogram as input, CEVIT realizes interference detection in complex interference environments with multi-interference and multiple types of interference by means of a feature extraction module and a detection head module. To validate the performance of the proposed model, experiments are conducted on airborne SAR interference simulation data and Sentinel-1 real interference data. The experimental results show that, compared with the other object detection models, CEVIT has the best interference detection performance in a complex interference environment, and the key evaluation indexes (e.g., Recall and F1-score) are improved by nearly 20%. The detection results on the real interfered echo data have a Recall that reaches 0.8722 and an F1-score that reaches 0.9115, which are much better than those of the compared methods, and the results also indicate that the proposed model achieves good detection performance with a fast detection speed in complex interference environments, which has certain practical application value in the interference detection problem of the SAR system.

A Novel Method Based on Proximate Wavelet Coefficient Recovery for Magnetic Resonance Sounding Signal Denoising in Complex Interference Environments

A Novel Method Based on Proximate Wavelet Coefficient Recovery for Magnetic Resonance Sounding Signal Denoising in Complex Interference Environments

Robust Signal Detection in Complex Noise and Interference Environment Based on MoG Modeling

Robust Signal Detection in Complex Noise and Interference Environment Based on MoG Modeling

Implementation and analysis of 5G network identification operations at low signal-to-noise ratio

The article investigates the operations of identifying a cellular network and searching for a cell at various signal-to-noise ratios. The estimation of frequency and time displacement, criteria for detecting the primary synchronization signal are presented. The main contribution of this article is the consideration of the step-by-step execution of the 5G cell search procedure in a complex interference environment. The decoding steps of the primary and secondary synchronization signals are being investigated. This is achieved by analyzing the signals at each step of the correlation algorithm for different signal-to-noise ratios. In order to verify the adequacy of the proposed models, a sequence operation for synchronizing 5G mobile networks with base station signals is considered. The dependence the magnitude of the error vector modulus on the signal-to-noise ratio of a physical broadcasting channel is investigated for three different channel profiles without line of sight. As a result of the experiment, the error vector of the physical broadcast channel changes from 55% to 10%, when the signal-to-noise ratio changes from 0 to 20 dB. In the multiple-input multiple-output (MIMO) mode, we received a 3 dB increase in communication energy efficiency. The findings will be useful for 5G system designers to troubleshoot synchronization problems.

A Novel Visible-Depth-Thermal Image Dataset of Salient Object Detection for Robotic Visual Perception

Visual perception plays an important role in industrial information field, especially in robotic grasping application. In order to detect the object to be grasped quickly and accurately, salient object detection (SOD) is employed to the above task. Although the existing SOD methods have achieved impressive performance, they still have some limitations in the complex interference environment of practical application. To better deal with the complex interference environment, a novel triple-modal images fusion strategy is proposed to implement SOD for robotic visual perception, namely visible-depth-thermal (VDT) SOD. Meanwhile, we build an image acquisition system under variable lighting scene and construct a novel benchmark dataset for VDT SOD (VDT-2048 dataset). Multiple modal images will be introduced to assist each other to highlight the salient regions. But, inevitably, interference will also be introduced. In order to achieve effective cross-modal feature fusion while suppressing information interference, a hierarchical weighted suppress interference (HWSI) method is proposed. The comprehensive experimental results prove that our method achieves better performance than the state-of-the-art methods.

Model of a Self-Organizing Radio Network, Operating in a Complex Signal and Interference Environment.

Radio communication networks, including those that use adaptation, are designed for information exchange between individual correspondents and are usually built via radio routes, functioning ones in a complex signal and interference environment. It is necessary to take into account the degree of influence values adaptive parameters for indicators that describe accordance requirements communication requirements, the energy component of the radio link, as well as the amount of radio link resources spent on maintaining and restoring communication. Getting estimates of the boundaries of primary and secondary user traffic service characteristics in a self-organizing radio network, functioning in difficult signal-to-noise conditions it is relevant. The aim of the research is to increase the reliability of the simulation results by obtaining the boundary values of the throughput when transmitting information in a self-organizing radio communication network. Modeling of processes occurring in the radio communication network is carried out, and the following parameters are determined: boundary parameters of delay and loading; parameters of the output stream in a complex signal-interference environment. Conclusions about the advantages of the network calculus method based on the results of a series of calculations are presented. Analytical estimates of the quality of service provision in the radio communication system are obtained using the theory of network calculus. The developed mathematical model makes it possible to study the delay and load indicators in a self-organizing radio network during the information exchange of traffic of various types under the influence of intentional and unintentional interference. The results of analytical calculations obtained by applying the network calculus method can be used in the formation of control actions, as well as solving problems of increasing the stability of radio links.

Частотно-поляризационная обработка сигналов для борьбы с многолучевостью в локальных системах местоопределения

The properties of a local positioning system operating in the 2.4 GHz ISM band, which is capable of supplementing the constellation with local system signals to achieve high positioning accuracy in a complex interference environment, are investigated. In this case, global navigation satellite systems (GNSS) signal receivers often also implement other methods for estimating the position or parameters associated with it: inertial systems, ultra-wideband systems, radars, etc. In this paper, the study of the properties of a local positioning system operating in the 2.4 GHz ISM band , capable of supplementing the constellation with local system signals to achieve high positioning accuracy in difficult conditions. The emphasis here is on indoor operation of the system when GNSS signals are unavailable. In addition, there are a large number of reflected signals in the room. The paper presents a method for describing reflected signals using the Jones vector, as well as the synthesis of optimal algorithms for estimating signal parameters under complex conditions for simplified scenarios. With the help of modeling, it is shown that the optimal methods are poorly applicable to real situations, however, they allow a better understanding of the physics of processes. Based on this understanding, a signal shaping technique is proposed to create a large redundancy of measurements in the receiver, as well as an empirical method for rejecting false measurements. With the help of this method, it has been experimentally shown that indoors in difficult conditions and in the presence of multipath, it is possible to achieve the RMS positioning error of less than 10 centimeters.

Method of 128-position quadrature amplitude-polarization manipulation

The functioning of modern digital communication systems tends to occur in a complex interference environment. The communication system is affected by various types of jamming: both natural noises associated with the conditions of radio waves propagation, and artificial interference concerned with electromagnetic compatibility of radio equipment, characteristics of communication channels, etc. Applied issues of enhancing digital communication systems interference insusceptibility are quite relevant at the present time. Concurrently, it is advisable to achieve an increase in interference insusceptibility by rational methods that do not require a significant increase in the emitted signals energy. The techniques based on the use of algorithms for processing special types of signals are the most promising to this date. Radio specialists address the methods for digital processing of polarization-manipulated signals which, while maintaining the communication system carrying capacity, allow us to obtain an essential gain in the parameters of the communication system interference insusceptibility. At the same time, a successful combination of these methods with the already known techniques of digital signal processing is noted. This article considers the multi-position method of quadrature amplitude-polarization manipulation (M-QAPM), where the number of positions M = 27 = 128 (128-QAPM). The modulation symbol at 128-QAPM consists of a 7-bit digital code. The purpose of this article is to describe analytically the method of 128-position quadrature amplitude-polarization manipulation when transmitting 7-bit binary modulation symbols over a communication channel. During mathematical modeling, a signal constellation was formed and visualized. The structural diagram of the modulator was given. The practical significance of the given paper lies in the fact that quadrature amplitude-polarization manipulation can be considered as a universal type of digital modulation, which can be applied instead of the currently known quadrature types of manipulation.

Study of the Service Quality of Real Time Traffic in a Complex Interference Environment

The process of servicing traffic in a radio communication network in a complex interference environment is studied based on analytical and simulation modeling. A developed analytic-simulation model for servicing real-time traffic in a complex interference environment is described along with an algorithm for calculating a single-channel queuing system with an exponential time distribution between incoming requests and gamma distribution of service time in a channel.

The Novel Method of Magnetic Anomaly Recognition Based on the Fourth Order Aperiodic Stochastic Resonance

In the background of strong interference noise, it is one of the crucial technologies of magnetic anomaly detection system to effectively detect and identify weak magnetic anomaly signals (MAS) gene- rated by targets. The detection and recognition of target signal under very low signal-to-noise ratio(SNR)below −10dB have not been achieved in the existing magnetic anomaly detection technology. To tackle these challenges, this paper proposes a magnetic anomaly recognition method based on fourth-order aperiodic stochastic resonance with the aid of sto- chastic resonance theory. The main nature of new algorithm is a four-layer fusion of single potential well stochastic resonance and has real-time recognition ability for MAS without prior information. When simulated magnetic anomaly signal of single object and mutil-targets were assumed in different condition, effect of parameters of algorithm was analyzed and range of optimal parameters was obtained. Through simulation and experimental verification of targets data, the new algorithm could realize target signal recognition in complex interference environment with SNR lower than −15dB,which demonstrates the efficacy of our proposed method and offer some useful design insights to practical MAD system.

Electromagnetic Interference Effects of Continuous Waves on Memristors: A Simulation Study.

As two-terminal passive fundamental circuit elements with memory characteristics, memristors are promising devices for applications such as neuromorphic systems, in-memory computing, and tunable RF/microwave circuits. The increasingly complex electromagnetic interference (EMI) environment threatens the reliability of memristor systems. However, various EMI signals’ effects on memristors are still unclear. This paper selects continuous waves (CWs) as EMI signals. It provides a deeper insight into the interference effect of CWs on the memristor driven by a sinusoidal excitation voltage, as well as a method for investigating the EMI effect of memristors. The optimal memristor model is obtained by the exhaustive traversing of the possible model parameters, and the interference effect of CWs on memristors is quantified based on this model and the proposed evaluation metrics. Simulation results indicate that CW interference may affect the switching time, dynamic range, nonlinearity, symmetry, time to the boundary, and variation of memristance. The specific interference effect depends on the operating mode of the memristor, the amplitude, and the frequency of the CW. This research provides a foundation for evaluating EMI effects and designing electromagnetic protection for memristive neuromorphic systems.

VHF BALANCED AMPLIFIER WITH LOSSLESS FEEDBACKS

Today’s practice of developing VHF radio systems paths widely uses MMIC as low-noise amplifiers. This approach is acceptable for radio systems operating in a relatively quiet electromagnetic environment. However, for systems operating in a complex interference environment of the VHF band, low-noise amplifiers with a lower gain and increased overload capacity are desirable. This requires maintaining a low noise figure and manufacturability of the device. Therefore, the solution to this problem requires the development of a low-noise amplifier of the VHF band with increased overload capacity, made on commercially available MMIC. This paper presents the results of a logical-heuristic synthesis of a VHF low-noise high-linear amplifier performed on an MMIC, utilising noiseless negative feedback technique. Analytical expressions are given for calculating the gain, the input gain compression point, input intercept points of the J-th order, and the noise figure of the structure. The analysis of the performance of the amplifier implemented on the MGA 62563 MMIC showed that, in comparison with other integrated solutions, increased overload capacity and structure linearity are provided. The high noise immunity and ease of manufacture of the device using commercially available components, make it a promising element in the design and modernization of VHF receiving and amplifying paths operating in a complex electromagnetic environment.

Fault Detection of Resilient Navigation System Based on GNSS Pseudo-Range Measurement

Because of the resilient frame structure, the factor graph is often used in navigation systems to solve the sensor asynchrony problem and realize plug-and-play effectively in the navigation information fusion method. To improve the fault detection performance of resilient integrated navigation systems under complex interference environments, a fault detection method in factor graph navigation framework based on INS measurements and GNSS pseudo-range measurements is proposed in this paper. The proposed method can effectively locate the fault satellite pseudo-range information based on the Chi-square fault detection method. Due to the plug-and-play characteristic of the factor graph framework, this method can quickly isolate faults to improve navigation accuracy. Finally, the effect of the method is verified by simulation and experiment. Compared with the Chi-square fault detection method, positioning accuracy is improved by more than 40%.

Marine SINS Self-Alignment Method in Complex Interference Environment Based on MEEMD Algorithm

It is difficult to rapidly and accurately achieve alignment under complicated interferential environmental conditions with a marine strapdown inertial navigation system (SINS) subject to angular swaying interference and linear motion interference. To solve this problem, an SINS self-alignment algorithm in a complex interference environment is presented in this article. For the angular motion disturbance problem, we used the attitude-updating algorithm in the coagulation inertial coordinate system to reflect the carrier’s attitude change in real time under the swaying interference so as to eliminate the influence of angular motion disturbance. To solve the problem of linear motion interference, we first use Fourier transform analysis (FFT) to analyze the frequency characteristics of linear motion interference signals. We then adaptively decompose the original signal into a series of signal components with different time scales and local characteristics according to the amplitude and frequency using the modified ensemble empirical mode decomposition (MEEMD) algorithm. Finally, we remove and reconstruct the disturbing signal components according to the frequency characteristics of the disturbing signal to filter the line motion disturbing signal. We use the MEEMD algorithm to conduct a ship alignment test. After pre-filtering by MEEMD, high accuracy can be achieved after 100 s of alignment, and the mean square error of the heading angle is 2.85′. The test results show that the MEEMD method has a good noise removal effect. The anti-jamming initial alignment algorithm based on the MEEMD algorithm has the ability to suppress the interference of angular motion and linear motion and achieve high-precision anti-jamming initial alignment under the complicated interferential environmental conditions with angular swaying interference and linear motion interference.

GF-KCF: Aerial infrared target tracking algorithm based on kernel correlation filters under complex interference environment

Aerial infrared target automatic tracking technology is the core technology of the photoelectric coun-termeasure system of infrared imaging missiles. The correlation filter (CF) tracker has attracted considerable attention in the field of aerial target tracking owing to its excellent performance in tracking accuracy and timeliness. We propose a correlation filter tracking based on Gabor filter (GF) features (GF-KCF) in the frequency domain for aerial infrared target tracking. This tracker constructs a set of frequency-domain GFs, which effectively suppress background noise and highlight target texture information. In view of the large overload maneuver and rapid deformation of aerial infrared targets in the process from near to far distance, we propose a scale estimation method in the frequency-domain based on GF features. The eigenvectors of the target spectrum scale are extracted to improve the accuracy of target scale information estimation. To address the problem of partial occlusion of targets by infrared decoy flares, we propose an anti-interference tracking strategy based on a high-confidence patch model. High-confidence patches are used to track the reliable part of the target, which provide more target information and improve the robustness of the algorithm in case of reappearance of the occluded target. Compared with other trackers, the average accuracy of the proposed tracker was improved by 15.2%, and the frame frequency reached above 110 Hz.

SF 6 decomposition and insulation condition monitoring of GIE: A review

The statistics of the Conference International des Grands Reseaux Electriques (CIGRE) indicate that the operational reliability of SF6 gas-insulated equipment (GIE) is very high; however, the failure rate of the GIE in operation is much higher than that of the IEC standard, and the fault occurs frequently in the GIE at a high voltage level. The reason is due to the complex and strong on-site electromagnetic interference environment and fully enclosed structure of GIE. The key method and technology for effective on-line monitoring and fault diagnosis of GIE are still lacking. Given the partial strong electromagnetic energy and high temperature induced by early latent insulation faults in the equipment, SF6 gas insulation presents different degrees of decomposition. The decomposition products mainly include SO2F2, SOF2, SO2, HF, and H2S. The decomposition characteristics of SF6 are closely related to the property of insulation faults. At present, this area is attracting attention from the power industry and research institutes. This study summarises the current research on SF6 decomposition component analysis (DCA). The content mainly includes the latest progress of SF6 decomposition characteristics and mechanism under fault conditions, and fault diagnosis methods based on decomposition components.

Air Target Recognition Algorithm based on Mixed Depth Features in the Interference Environment

Infrared aircraft target recognition technologies under complex interference conditions have been a research hotspot. The development of infrared countermeasure technologies has made the air combat environment increasingly polymorphic, thus hindering the accurate recognition of infrared targets. In particular, a complex artificial interference can severely obscure target, resulting in the loss of continuity and saliency of target features, and the inability to fully describe the characteristics of a target object, thus making aerial target recognition inaccurate. To overcome this problem, we propose an anti-interference recognition algorithm for air targets based on mixed depth features. First, to improve the ability of the algorithm accurately in selecting candidate regions in a full trajectory, an improved fuzzy C-means (FCM) adaptive segmentation algorithm is developed to extract the target candidate region. Second, a deep convolutional feature (convolutional neural network) and the histogram of gradient feature are used to construct hybrid depth features for a more comprehensive representation of the target. Finally, to consider the diverse confrontation scenarios between the target and the interference in a combat scene, a three-class support vector machine model is proposed to deal with the target, interference, and interference adhesion states. The experimental results show that in a complex interference environment, the air target anti-interference recognition algorithm based on the mixed depth features exhibits an accuracy rate of 92.29%, which represents an accurate target anti-interference recognition.

Target Detection in Clutter/Interference Regions Based on Deep Feature Fusion for HFSWR

High-frequency surface wave radar (HFSWR) is of great significance for maritime detection, but in the HFSWR echo signal, ship targets are often submerged in a variety of clutter and interference, making it difficult to detect vessels. In this paper, we propose an intelligent detection algorithm for targets concealed in strong clutter and complex interference environments. The algorithm has two stages: preprocessing and target detection. In the preprocessing stage, faster region-based convolutional neural networks Faster R-CNN are designed to identify and locate clutter and interference regions in the range Doppler spectrum; in the target detection stage, a two-level cascade algorithm is proposed. First, an extremum detection algorithm is proposed to identify suspicious target points in the clutter/interference regions, including real and false target points, to quickly obtain potential target positions. Second, in consideration of the characteristics of radar targets, two lightweight networks are designed to extract the CNN features and the stacked autoencoder features of the potential target locations. Then, fusion features are obtained and sent to an extreme learning machine that acts as a second-level classifier to distinguish between real and false target points. Experiments show that the proposed HFSWR target-detection algorithm has better performance for vessel detection in clutter/interference regions than the current mainstream detection algorithms.

Application of permutation frequency modulation signals manipulated with a constant weight code to increase the noise immunity of decameter radio communications

Introduction: The operation of radio lines in the decameter range, as a rule, occurs in a complex interference environment, characterized by the presence of fast and slow fading. Therefore, one of the most relevant areas of research in this subject area is the development of new technical solutions aimed at improving the noise immunity of reception. Purpose: Development of signals with permuted frequency modulation that allow detecting single errors at the physical level by selecting combinations of subcarriers of each character in accordance with the alphabet of the code with a constant weight. Results: Theoretical aspects of formationof the permutation signals with frequency modulation, the choice manipulating code to select subcarriers within a signal symbol, presents an analytical approach for the derivation of the generalized expression evaluation of noise immunity of the developed signals of permutation modulation in a channel with variable parameters in incoherent processing, we obtained the estimation of the values of probability of bit error for new signals in comparison with the known results. Practical relevance: The developed signal with permuted frequency modulation is proposed to be used in decameter radio communication systems operating in a narrow frequency band in the ionospheric channel. Discussion: Further research is associated with optimization of decision-making procedures for demodulating the developed signals, as well as the search for effective ways to encode signals with permuted frequency modulation at the physical level, allowing to increase the data transfer rate while maintaining the noise immunity of reception.

Обнаружение сверхширокополосных квазирадиосигналов на фоне помехи с линейной частотной модуляцией.

In this paper, we synthesize and analyze algorithms for detecting ultra-wideband quasi-radio signals against the background of Gaussian white noise and interference with linear frequency modulation under various a priori uncertainty conditions. Among the many UWB signals, a separate most promising class was identified – UWB QRS, whose structure is similar to narrowband radio signals, but the condition of relative narrowband for them is not fulfilled. A linear frequency modulation signal is considered as an interference when estimating the effectiveness of the detector of a UWB QRS. The selected interfering signal can be either intentional or unintentional, and is of the greatest interest to consider, since it has a similar structure to a useful signal and have the greatest destructive effect on correct reception. The dependence of the signal omission probability on the interference parameter and the interference-to-signal ratio is obtained, which allows to increase the detection efficiency by several orders of magnitude. A comparative analysis of the resistance to interfering signals of various detector circuits is performed. Recommendations are formulated to improve the efficiency of detectors operating in a complex interference environment, destabilizing information and technical influences, or attempts to unauthorized access to information.