Improve Noise Immunity Research Articles

Wideband circularly polarized high accuracy survey active antenna for global navigation satellite systems applications

AbstractThis letter presents a new circularly polarized (CP) active antenna for global navigation satellite systems (GNSS) operating in the L1‐band (1.164–1.28 GHz) and L2‐band (1.525–1.615 GHz). The active antenna consists of a passive antenna and a two‐channel low‐noise amplifier (LNA) circuit. To achieve wideband coverage of the L1/L2 bands while maintaining a low profile, a new electroplating process is utilized in fabricating the passive antenna. Additionally, to realize CP performance, the passive antenna is sequentially fed by four ports with a wideband feeding network. To minimize phase variations, a 90° phase shifter loaded with open‐short‐stub is integrated into the feeding network. Furthermore, to improve noise immunity, out‐of‐band rejection, and amplify GNSS signals, the LNA circuit cascades two‐stage dielectric bandpass filters and three‐stage LNAs. Consequently, the circuit features a low noise figure of below 1.65 dB, a maximum out‐of‐band rejection level of 60 dB, and a stable active gain of 30 dB. The performance of the active antenna is evaluated in an outdoor open field using a GNSS receiver.

Design of an Embedded Test Bench for Organic Photovoltaic Module Testing

In this article, a multipurpose embedded system for testing organic photovoltaic modules is presented. It is designed to include all the features for real-time monitoring, data acquisition, and power conversion based on a Ćuk converter, providing useful data for scientific investigation of the outdoor operation of organic photovoltaic modules. The embedded system allows both the scan of the I–V curve and the continuous operation of the organic photovoltaic module, such as at its maximum power. Voltage and current at the terminals of the organic photovoltaic module under test and up to four temperatures are continuously measured and stored on a Secure Digital card. The communication interface allows the embedded system to connect with other instruments, such as irradiance sensors, with digital serial output. The embedded system is designed both for laboratory and in-the-field use: it can be powered either by the AC electrical grid or a battery, which can also operate as a backup battery. Galvanic isolation divides the embedded system into the field-side and the logic-side functional sections, providing improved noise immunity and safe operation. The main power distribution system within the embedded system is a +9 V bus; ultra-low-noise linear low dropout regulators provide the +3.3 V and +5 V regulated voltages to supply the analog and digital circuits within the logic-side section, and a flyback converter supplies the field-side section of the board. The proposed embedded solution is validated using an experimental setup built at SolarTechLab, Politecnico di Milano. The experimental results report the feasibility of the proposed embedded system.

Development of methods for generating examples that train a neural network to detect and classify interference in the structure of a useful signal

The main purpose of the information transmission system is to transfer useful information between its users reliably and accurately. At the same time, it would be advisable to supplement the functionality of the information transmission system with the ability to analyze interference in the communication channel during the transmission of a message. In the case of analysis of damage to the useful signal, which may occur due to interference of various types in the propagation medium, the information transmission system can use the results of such analysis to improve noise immunity, to collect statistics, to control electromagnetic compatibility. It is known that optimal processing of noise-like signals is carried out using a correlator or a matched filter, but these classical devices might be complemented with a neural network, and then in addition to determining the correlation function, it is the neural network that is able to analyze a signal damaged by interference, as shown by the authors in their previous works. In this case, for the correct training of a neural network, samples of a useful signal damaged by various types of jamming are needed. This article discusses methods for the formation of training images for a neural network designed to determine the period of pulse interference acting on an M-sequence as a known signal. Two techniques are suggested. They are digital modelling and experimental (laboratory) method. The first one is based on the inverting some elements (chips) of the original M-sequence located in certain segments whose lengths are random. The inversion is performed by the program written in C++ language. The second approach involves a special installation that consists of a personal computer, an Arduino microcontroller, a useful signal transmitter, a receiver and a periodic interference generator. The objective of each method is to obtain a matrix of damaged chips in a chain of M-sequences. Such matrix was called an “error profile” by the authors. The characteristics of the error profile obtained for certain interference parameters (jamming pulse period and duration) according to suggested methods can be used as training data for the neural network designed for jamming classification.

An Ensemble Classification Model for Depression Based on Wearable Device Sleep Data.

Depression is one of the most common mental disorders, with sleep disturbances as typical symptoms. With the popularity of wearable devices increasing in recent years, more and more people wear portable devices to track sleep quality. Based on this, we believe that depression detection through wearable sleep data is more intelligent and economical. However, the majority of wearable devices face the problem of missing data during the data collection process. Otherwise, most existing studies of depression identification focus on the utilization of complex data, making it difficult to generalize and susceptible to noise interference. To address these issues, we propose a systematic ensemble classification model for depression (ECD). For the missing data problem of wearable devices, we design an improved GAIN method to further control the generation range of interpolated values, which can achieve a more reasonable treatment of missing values. Compared with the original GAIN approach, the improved method shows a 28.56% improvement when using MAE as the metric. For depression recognition, we use ensemble learning to construct a depression classification model which combines five classification models, including SVM, KNN, LR, CBR, and DT. Ensemble learning can improve the model's robustness and generalization. The voting mechanism is used in several places to improve noise immunity. The final classification model performed great on the dataset, with a precision of 92.55% and a recall of 91.89%. These results illustrate how efficient this method is in automatically detecting depression.

S-method based on modified group delay for time-frequency analysis

A noise robust time-frequency representation based on the S-method (SM) and modified group delay (MGD) (S-MGD) is proposed in this article. The SM is free from cross-terms as it is the sum of individual Wigner distributions of different signal components and provides high-energy concentration both in time and frequency. The MGD reduces the Gibbs ripple and spurious spectral peaks because of noise, without using any frequency smoothing, and thus maintains the best frequency resolution as that of rectangular window. Hence,a combination of SM and MGD provides the desirable features of both the methods. The proposed method is tested for different signals like time varying random process, frequency shift keying, synthesized car engine sound/pressure signals using a solo combustion and a real-time echolocation pulse emitted by a big brown bat (Eptesicus fuscus) which indicate that the new S-MGD has improved noise immunity and frequency resolution compared to the method that uses frequency smoothing to suppress noise and Gibbs effects.

Inverter and Universal Gates Implementation Using Novel Core Insulator Double Gate (CIDG) MOSFETs

The Core Insulator Double Gate (CIDG) MOSFET has been explored for digital applications in which the presence of core insulator diminishes the bulk conduction and reduces the off state current. The drain currents of n- and p-type CIDG MOSFETs are matched by tuning gate work functions to deliver the symmetrical pull-up and pull-down characteristics. The inverter and universal logic gates (NAND and NOR) have been designed and implemented to show the usability of the CIDG MOSFETs for digital applications. The DC and transient characteristic of the inverter along with Static Noise Margin (SNM) and time delay parameters have been examined. The designed Inverter shows steeper voltage transfer characteristics, reduced short circuit power dissipation and improved noise immunity. The CIDG MOSFET based NAND and NOR gate implementation and validation by transient analysis have been shown for the first time to the best knowledge of the authors. Also, the rise and fall times of the inverter, NAND and NOR gates have been found to be improved as compared to the DG MOSFET counterparts. The present analysis establishes that CIDG MOSFETs are useful in designing digital circuits with improved performance.

Low-Pass Image Filtering to Achieve Adversarial Robustness.

In this paper, we continue the research cycle on the properties of convolutional neural network-based image recognition systems and ways to improve noise immunity and robustness. Currently, a popular research area related to artificial neural networks is adversarial attacks. The adversarial attacks on the image are not highly perceptible to the human eye, and they also drastically reduce the neural network's accuracy. Image perception by a machine is highly dependent on the propagation of high frequency distortions throughout the network. At the same time, a human efficiently ignores high-frequency distortions, perceiving the shape of objects as a whole. We propose a technique to reduce the influence of high-frequency noise on the CNNs. We show that low-pass image filtering can improve the image recognition accuracy in the presence of high-frequency distortions in particular, caused by adversarial attacks. This technique is resource efficient and easy to implement. The proposed technique makes it possible to measure up the logic of an artificial neural network to that of a human, for whom high-frequency distortions are not decisive in object recognition.

Improving the stability of phase retrieval algorithm in speckle autocorrelation imaging by Huber penalty sparsity constraint

One of the most widely used methods for reconstructing images through a scattering medium is the Hybrid Input Output (HIO) phase retrieval algorithm. However, the stability and noise robustness of the HIO method are poor, as they are affected by initial values and noise during the imaging process. This paper presents an optimized HIO phase retrieval algorithm that utilizes the Huber penalty as a sparsity constraint to effectively enhance the quality and stability of the reconstruction algorithm. The introduced constraint is designed to guide the iteration process away from local optimal solutions, ensuring superior recovery images even with random initial values. Additionally, an adaptive step size parameter is incorporated to control the iterations and convergence steps, resulting in stronger robustness against noise effects. Moreover, the error criterion for image restoration is defined as the sum of the Fourier transform amplitude of the gradient. Experimental results demonstrate that the proposed phase retrieval algorithm achieves superior quality in the recovered images, while significantly improving noise immunity and stability for randomly selected initial values.

Hybrid SOC and SOH estimation method with improved noise immunity and computational efficiency in hybrid railroad propulsion system

The fuel-cell and lithium-ion battery (LIB) hybrid railroad propulsion system (HRPS) technologies are actively being researched to reduce greenhouse gas (GHG) emissions. It is becoming increasingly important to accurately estimate the state-of-charge (SOC) and state-of-health (SOH) to enhance the safety and efficiency of the system. For a real-time embedded system, computational efficiency and the effect of noise are crucial challenges for SOC and SOH estimation. To overcome these problems, a method is required that improves computational efficiency and minimizes the effect of noise.To reduce computational cost and the effect of noise, the adaptive extended Kalman filter (AEKF) and specific partial capacity with single forgetting factor recursive least square (SPCSFFRLS) methods were combined to estimate SOC and SOH. In AEKF-based SOC estimation, the state and measurement noise covariance matrices were corrected by the mean square error (MSE) of the difference between measured voltage and modeled voltage. Thus, AEKF is effective in conquering measurement noise. The battery capacity was obtained by the SPCSFFRLS using station-to-station operation data. To calculate true specific partial capacity (SPC) without noise, the partial capacity method and SFFRLS were used to update the battery capacity. However, as the current accumulation period becomes longer, an accumulation error due to measurement noise may occur. Therefore, a specific period was analyzed to reduce accumulation error caused by measurement noise in the HRPS load profile. Finally, SOC and SOH co-estimation was demonstrated for a single cell and a parallel-connected battery pack (1S18P). As a result, it was found that the proposed method can reduce the computational time by about 33.0 % average while keeping the SOC and SOH estimation accuracy compared to DEKF. Thus, the proposed method is suitable for real-time embedded system such as HRPS to estimate SOC and SOH.

Enhanced phase sensitive amplification towards improving noise immunity

Quantum states are essential resource for quantum-enhanced applications. Loss incurred in the distribution channel, however, dissipates the high signal-to-noise ratio advantage enjoyed by the squeezed state. Here, we first demonstrate noise immunity enhancement by using phase-sensitive amplifier (PSA) with measurement-based noiseless linear amplifier (MB-NLA). We explore the signal transfer capability with the amplifier in a noisy channel. The MB-NLA enhanced PSA has obvious suppression effect on channel noises, especially it has improvement for the noise contaminated signal. Better performance can be achieved by flexibly adjusting amplifier parameters. With the amplifier, it is promising to overcome the entanglement-distribution loss and show its superiority in squeezing based quantum sensing.

АЛГОРИТМ ОБРАБОТКИ ПРОСТРАНСТВЕННО-ВРЕМЕННЫХ СИГНАЛОВ НА ОСНОВЕ СИСТЕМЫ MIMO-OFDM В УСЛОВИЯХ АКТИВНЫХ ПОМЕХ

An algorithm for processing space-time signals based on a MIMO-OFDM communicationsystem in the presence of active interference is described. Theoretical calculations are given, thedetection of approaches that often cause the bandwidth of the communication channel when leavinga point source of active interference. The task is relevant in the conditions of dense urban development,as well as the steadily growing need to improve noise immunity and communicationquality without bandwidth coverage. To process information in a MIMO-OFDM system withoutinterference, engineers mainly use the criterion of maximum signal-to-noise ratios, however, in thepresence of active interference, the Wiener criteria. It measures the minimum RMS pilot measurementerror in OFDM. In this case, a signal receipt of a monetary amount, an eigenvector is detected,weight processing is performed, a signal is received that occurs according to the minimumerror criterion. An orthogonal frequency division multiplexing technology with pilot subcarriers isreduced at the receive frequency in frequency and modulation code. Thresholding was found in thedecrypted code, produced by the RMS comparison. The arrival of big money comes from this ownnumber. Pilot-based enumeration searches for the minimum acceptable error. The eigenvector ofthe found signal will be for weight processing. Experiments are carried out to detect a signal in acommunication channel with and without adaptation using the Wiener criterion and the presenceof interference with two types of modulation (QAM-4, BPSK). The results show that the adaptationimproves the BER (bit error rate) state along the entire line of the curve and for all SNRs.The developed algorithm can be used for communication and control systems of unmanned aerialvehicles in the presence of active interference.

Development of Transmitter and Receiver With Set Partitioning 64APSK Coded Modulation Designed on Basis of Channel Capacity

In this paper, we present a prototype transmitter and receiver with set partitioning (SP)-64 amplitude and phase shift keying (APSK) coded modulation we developed for expanding satellite transmission capacity. SP-multi-level coded modulation is a transmission scheme that can improve noise immunity by properly combining a modulation scheme, bit allocation, and error-correction codes. We designed SP-64APSK coded modulation on the basis of channel capacity for expanding satellite transmission capacity. We confirmed that it has higher robustness to additive white Gaussian noise (AWGN) than DVB-S2X’s 64APSK modulation with Gray mapping through computer simulation. We also developed a prototype transmitter and receiver to implement our SP-64APSK coded modulation and evaluated its transmission performances in an AWGN channel and in a non-linear channel simulating 12-GHz-band satellite transponder characteristics. We describe the method of designing our SP-64APSK coded modulation through computer simulation, the modulation/demodulation process, and transmission performances of the prototype transmitter and receiver. We also indicate that 8K ultra-high definition television (UHDTV) with an encoded bit rate of 150 Mbps can be transmitted using the prototype within 34.5 MHz, which is the bandwidth of a single transponder for satellite broadcasting in Japan.

О технических методах снижения числа сбоев в работе основных локомотивных устройств безопасности

Violations in operation of receiving equipment of safety locomotive major devices due to the hindering effect of electromagnetic interference (failures) are a rather frequent phenomenon on the railway network of the Open Joint Stock Company «Russian Railways» in the conditions of electromagnetic environment that has changed dramatically with active introduction of modern electric rolling stock. On the one hand, failures are the result of discrepancy of own parameters and operation algorithm of receiving equipment of safety locomotive major devices opposite interference, existing in inductive coupling channel of automatic locomotive signaling. On the other hand, it is a consequence of the lack of regulatory documentation with uniform established requirements for interference parameters under the influence of which, safety locomotive major devices, primarily built on a relay element base, shall provide for regular operation. Over the past decades, numerous and different by their technical essence attempts have been made to resolve these antagonistic contradictions. This work is one of the first attempts to generalize and analyze the results of pursued research and developments. The work is based on the results of a patent study conducted by the authors in order to identify trends in technical measure development to improve noise immunity in operation of safety locomotive major devices. On their basis, the authors proposed, described in detail and substantiated main technical methods for reducing failure number in the operation of safety locomotive major devices. The obtained results may be of interest to specialists involved in technical servicing, repairment, development and improvement of safety locomotive major devices and will be used further in the development of the theory of locomotive automatic signaling numerical code.

Comprehensive Analysis and Improvement Methods of Noise Immunity of Desat Protection for High Voltage SiC MOSFETs With High DV/DT

This paper comprehensively analyzes desaturation (desat) protection for high voltage (>3.3 kV) silicon carbide (SiC) MOSFETs and especially how to build in noise immunity under high <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">dv/dt</i> . This study establishes a solid foundation for understanding the trade-offs between noise immunity and response speed of desat protection. Two implementations of the desat protection for high voltage SiC MOSFETs are examined, including desat protection based on discrete components and desat protection realized with a gate driver integrated circuit (IC). Both positive <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">dv/dt</i> and negative <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">dv/dt</i> are investigated. Analysis results show that the high <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">dv/dt</i> with long duration caused by high voltage SiC MOSFETs’ switching results in strong noise interference in the desat protection circuitry. The impact of numerous influencing factors is investigated analytically, such as parasitic capacitances, parasitic inductance, damping resistance, and clamping impedance. Under high positive <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">dv/dt</i> , extremely small parasitic capacitances (<0.01 pF) between the drain terminal and protection circuitry could still compromise noise immunity of the desat protection circuitry that has a high-impedance voltage divider. Comprehensive design guidelines are summarized to boost the noise immunity, including circuit design, component selection, and PCB layout. The noise immunity margin under the positive <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">dv/dt</i> is also derived quantitatively to guide the noise immunity improvement. The noise immunity analysis results and noise immunity improvement methods are validated with simulation and experimental results obtained from a phase leg based on 10 kV/20 A SiC MOSFETs.

Enhancing digital rock image resolution with a GAN constrained by prior and perceptual information

In digital rock physics, pore distribution and microstructure of rocks affect the flow properties and elastic characteristic of rocks. It is difficult to accurately characterize these parameters in low-resolution images due to rock heterogeneity, and improving with instrument is costly. Traditional interpolation method to enhance the image resolution only enriches the low frequency information of the image without focusing on the boundary which is rich in high frequency information, and conventional deep-learning methods cannot perform a satisfying result in different-level instrument noise. To address these issues, a generative adversarial network of an image segmentation network as discriminator constrained by perspective information and prior information (SCPGAN) is proposed to improve images resolution by enhancing medium-high frequency information of images and improving network anti-noise capacity. The perceptual information is extracted by VGG19 to enrich boundary and texture information and the porosity is built by discriminator as prior information to guide generator to improve noise immunity. Traditional interpolation and CNN are used to verify that perceptual information can be augmented with medium-high frequency information, and GAN-based models are used to verify that prior information can improve network performance. The result shows the network with perceptual information can significantly improve images resolution and outperform the traditional interpolation on structural similarity index (SSIM), peak signal-to-noise ratio (PSNR), and multiple-point connectivity (MPC), while GAN-based model with prior information shows an excellent anti-noise capacity, especially high-level noise, and has similar physical properties to the high-resolution model in the permeability simulation.

A neuro-genetic Hopfield associative memory (HAM) with improved noise immunity

Artificial Neural Network (ANN) is a form of computation inspired by the arrangement and purpose of the brain. Pattern Recognition is one of the demanding areas under Artificial Neural Network and pattern association is one of the major tasks through which pattern recognition is realized. Nowadays researchers are taking interest in the combination of evolutionary algorithms and ANN. In the present work, an attempt is being made to analyze the performance of Hopfield Associative Memory with Monte Carlo adaptation rule and evolutionary searching (Genetic Algorithm) for pattern storage and recall. The training pattern set has been taken a set of five Greek alphabet letters as different objects. The aim is to store Patterns with MC adaptation rule and get the best weight matrices for efficient recalling of any given set patterns. The neural networks architectures have been taken up for storing the given set of inputs, for which conventional Hebbian and Monte Carlo adaptation rule is considered. During the mutation process, various mutation probabilities are supposed to be evaluated. The detailed simulated results thus obtained will be presented with the help of tables and graph.

Deterministic vs. Random Modulated Interference on G3 Power Line Communication

Power line communication (PLC), which is often used in advanced metering infrastructure (AMI), may be disturbed by adjacent high-power converters. Due to the inherent features of this type of communication, classic methods of improving communication reliability (filtration and circuit separation) cannot be fully applied. Information coding (modulation) methods are used in PLC to increase the data transfer rate and improve noise immunity. Random modulations (RanM) are used in converters to lower emission levels. Therefore, we investigate how the converters’ modulation parameters and coding methods may affect PLC communication reliability in the paper. To this end, we employ an experimental approach. In particular, the analysis of the influence of deterministic modulation (DetM) and (RanM) on the performance of narrowband G3-PLC is shown. We emulated an actual situation where EMI generated by the DC/DC converter disturbed the PLC transmission. The experimental results show the transmission error rates for different operating scenarios. The natural (experimental) system results, due to the complexity of the disturbing signals, differ from the literature data obtained by simulation for normalized signals.

Improving noise immunity of homography superposition for television signals

The algorithm of homography superposition of the television signals was shown in this article. The algorithm allows improving noise immunity for homography parameters of television signal with textural fragments. The core of the estimation procedure of homography parameters for image superposition is the matching of the feature points. The feature points are local extremes of the pixel brightness of the image. The matching is defined by the maximum correlation coefficient between a region of the image of a neighbor area of the feature point. The log-polar system of the images provides an invariant correlation of scale and rotate are proportional offsets along the axis in this coordinate system. The noise immunity is provided due to the developing procedure of removing feature points in the textural region. This procedure leads to decreasing probability of error matching of the feature points. The numerical modeling shows high noise immunity of the developed procedure in comparing the current researches.

Improvement of Noise Immunity of Biomedical Monitoring Systems with Biofeedback

Improvement of Noise Immunity of Biomedical Monitoring Systems with Biofeedback

ПОМЕХОЗАЩИТА РАДИОЛОКАТОРА С СИНТЕЗИРОВАННОЙ АПЕРТУРОЙ КОСМИЧЕСКОГО БАЗИРОВАНИЯ НА ОСНОВЕ ЦИФРОВОЙ АФАР

The article deals with General questions about the definition of parameters, the calculation of which is necessary for choosing a method for organizing interference protection of a synthetic aperture radar (RSA), analyzes and notes the features of the construction and functioning of the RSA. The features of noise protection on radars of various companies are considered: COSMO-SkyMed -4 (Constellation of Small Satellites for Mediterranean basin Observation) X-band (made in Italy), TerraSAR-X/TanDEM-X (Germany), “Kasatka-R” (Russia). The subject of the study is a synthetic aperture radar, which is a coherent radar system that uses the flight path of the platform to simulate extremely large obstacles or objects electronically, and which generates high-resolution remote sensing images. Over time, individual transmit / receive cycles are completed, and data for each cycle is stored electronically. When the signal processing uses the amplitude and phase of the received signals in successive pulses from elements of a synthetic aperture. After a set number of cycles, the stored data is re-combined (taking into account the Doppler Effect inherent in different transmitters for the target geometry in each subsequent cycle) to create a high-resolution image of the terrain over which the flight is performed. The analysis of the RSA parameters that affect the radar noise immunity is performed. Objective: to analyze the interference protection of a space-based synthetic aperture radar based on digital AFAR. It is necessary to identify the type of interference that has an effective interfering effect on the protected object and determine their degree of impact depending on the parameters of the interference source. Noise immunity refers to the ability of a radio system to resist interference. Radars from various manufacturers have differential methods for improving noise immunity. The calculation of the radar range is given for the purpose of detailed consideration of the parameters of the maximum range of radio interference. The paper focuses on the main radar interference and options for improving noise immunity for this type of radar. Methodology: analysis of existing literature, analysis of technical characteristics of radars from various manufacturers, modeling of possible types of interference, deduction, induction, comparison of used radars with synthesized aperture, formalization.