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The noises embedded in signals will degrade the signal processing quality. Traditional denoising algorithms might not work in practical systems since the statistical characteristics of noises might not be learned. To address this issue, we propose an efficient residual shrinkage convolutional neural network (RSCNN) aided denoiser based on the principle of the domain transformation, shrinking and inverse transforming operations conducted by the traditional denoiser. The proposed RSCNN is composed by the batch normalization layer, domain transformation layers, the shrinkage module and inverse transformation layers, wherein transformation layers consist of convolutional layers and the nonlinear activation function. Moreover, we propose a thresholds learning subnetwork to automatically determine the thresholds, so as to enhance noise suppressing performances. Furthermore, we compose the data set by preprocessing the received signals, and design the loss function according to different denoising requirements. To validate the efficiency and universality of the RSCNN aided denoiser, we apply the proposed RSCNN denoiser to three different application scenarios, including the modulation recognition, detection and decoding. After the offline training, at the online deployment stage, we utilize the RSCNN denoiser to reduce the noise power and improve the signal to noise ratios. Simulation results demonstrate that the proposed intelligent denoiser can efficiently improve the signal processing capabilities to achieve higher modulation recognition accuracy, better detection and decoding performances with lower complexity than benchmark schemes.

We propose a photonic method for flat spectrum millimeter-wave (mm-wave) noise generation. Specifically, the flat spectrum mm-wave noise is obtained by slicing the broadband ASE optical spectrum into multiple Gaussian-shaped spectra with different central wavelengths, then beating in a wideband photomixer. Our simulation demonstrates that flat spectrum mm-wave noise can be generated in a very large range of frequency of F-band (90-140 GHz) and G-band (140-220 GHz). For the quantitative comparison of the quality of generated mm-wave noise, we define the relative flatness ( $\eta$ ) as the ratio of the generated noise power fluctuation to its average power within a certain frequency range. Our experimental results show that the relative flatness of the generated mm-wave noise is as low as 0.46 (@35 ± 15 GHz).

This article considers a cyber-physical system with multiple remote state estimation subsystems under denial-of-service (DoS) attack. Suppose that there are multiple distributed estimation systems, in each of which, a sensor monitors the system and sends its local estimation to a remote estimator over one of multiple wireless channels. A DoS attacker emits noise power to jam the wireless channels. A scheduler is installed to dispatch each sensor to transmit information through the specific channel to minimize the total estimation error covariance on account of energy-saving. Whereas, the DoS attacker attempts to jam a channel to realize an opposite objective. With considering interference from other individuals, a multisensor multichannel remote state estimation model is constructed. A myopic policy and a long-term online interaction strategy under varying network environment are investigated and compared by solving a two-player zero-sum game and a Markov game, respectively. Simulations are provided to demonstrate our results.

In this article, we present the novel hardware and software architecture of a smart optical force–torque sensor. The proposed configurable, modular, and compact electronics lead to performance characteristics that cannot be reached by currently available sensors: ultra-low noise with average noise power spectral density of 15 nV/ $\sqrt{\text{Hz}}$ over a signal bandwidth of 500 Hz, a resolution of 0.0001% full scale at a 95% confidence level, and a hardware latency of less than 100 $\mu$ s. Performance is achieved by local synchronized oversampling of the sensor's optical transducers and parallel hardware processing of the sensor data using a field-programmable gate array (FPGA). The FPGA's reconfigurability provides for easy customization and updates; for example, by increasing the FPGA system clock rate to a maximum of 160 MHz, latency can be decreased to 50 $\mu$ s, limited by the current analog-to-digital converter. Furthermore, the approach is generic and could be duplicated with other types of transducers. An inertial measurement unit and a temperature sensor are integrated into the sensor electronics for gravity, inertia, and temperature compensations. Two software development kits that allow for the use of the sensor and its integration into the robot operating system have been developed and are discussed.

Introduction. Modern digital phased array antenna (DPAA) systems incorporate a large number of identical transceiver modules (TMs). These modules require real-time calibration with a high level of accuracy. In a previous work, we proposed a real-time calibration method for all receiver channels, which is based on the use of a calibration signal (CalSig) of the same frequency spectrum as the reflected signal and modulated in phase and amplitude by BPSK and OOK codes, respectively. This method was found to have a number of advantages over conventional approaches. However, the use of the same CalSig sample for all receiving channels increases the noise power gain at the output of a digital beam-forming unit (DBU). To overcome this limitation, we set out to improve the structure of CalSigs by making them pseudo-orthogonal. As a result, the noise power gain at the DBU output can be significantly reduced compared to that obtained in our previous work.Aim. To propose an improved design of a controlled amplitude modulation code OOK generator, which allows creation of pseudo-orthogonal CalSigs. As a result, the noise power gain at the output will increase insignificantly, thus having no negative effect on the quality of digital beam forming, signal processing and calibration.Materials and methods. Theory of system engineering and technology; theory of digital signal processing; system analysis; mathematical modeling.Results. An improved CalSig for calibrating the receiving channels of TMs was obtained. A structural diagram allowing the formation of pseudo-orthogonal CalSigs was synthesized.Conclusions. We proposed a new approach to improving the structure of signals used for real-time calibrating the DPAA receiving channels. A structural diagram of an amplitude-modulated OOK code generator for pseudo-orthogonal CalSigs was developed.

The purpose of the study is to evaluate the effect of energy level on the modulation transfer functions (MTF) and noise power spectra (NPS) of virtual monochromatic images (VMIs) obtained using four types of computed-tomographic (CT) scanners: Revolution, SOMATOM, IQon, and Aquilion. VMIs were obtained at 70, 60, and 50 kiloelectron volts (keV), and also at the lowest keV available in each scanner. We evaluated the MTF and NPS in the VMIs obtained at each keV. No significant effect of the energy level on the MTF was observed in IQon, whereas the spatial resolution decreased as the energy level decreased in the other types of scanners. The NPS curves tended to increase as the energy levels decreased with three types of scanners other than Aquilion. The spatial resolution and noise frequency characteristics of VMIs may be affected by the energy level, and the effects of energy level on these characteristics differ depending on the type of CT scanners.

OBJECTIVE. Previous advances over filtered back projection (FBP) have incorporated model-based iterative reconstruction. The purpose of this study was to characterize the latest advance in image reconstruction, that is, deep learning. The focus was on applying characterization results of a deep learning approach to decisions about clinical CT protocols. MATERIALS AND METHODS. A proprietary deep learning image reconstruction (DLIR) method was characterized against an existing advanced adaptive statistical iterative reconstruction method (ASIR-V) and FBP from the same vendor. The metrics used were contrast-to-noise ratio, spatial resolution as a function of contrast level, noise texture (i.e., noise power spectra [NPS]), noise scaling as a function of slice thickness, and CT number consistency. The American College of Radiology accreditation phantom and a uniform water phantom were used at a range of doses and slice thicknesses for both axial and helical acquisition modes. RESULTS. ASIR-V and DLIR were associated with improved contrast-to-noise ratio over FBP for all doses and slice thicknesses. No dose or contrast dependencies of spatial resolution were observed for ASIR-V or DLIR. NPS results showed DLIR maintained an FBP-like noise texture whereas ASIR-V shifted the NPS to lower frequencies. Noise changed with dose and slice thickness in the same manner for ASIR-V and FBP. DLIR slice thickness noise scaling differed from FBP, exhibiting less noise penalty with decreasing slice thickness. No clinically significant changes were observed in CT numbers for any measurement condition. CONCLUSION. In a phantom model, DLIR does not suffer from the concerns over reduction in spatial resolution and introduction of poor noise texture associated with previous methods.

Deep learning-based speech enhancement algorithms have shown their powerful ability in removing both stationary and non-stationary noise components from noisy speech observations. But they often introduce artificial residual noise, especially when the training target does not contain the phase information, e.g., ideal ratio mask, or the clean speech magnitude and its variations. It is well-known that once the power of the residual noise components exceeds the noise masking threshold of the human auditory system, the perceptual speech quality may degrade. One intuitive way is to further suppress the residual noise components by a postprocessing scheme. However, the highly non-stationary nature of this kind of residual noise makes the noise power spectral density (PSD) estimation a challenging problem. To solve this problem, the paper proposes three strategies to estimate the noise PSD frame by frame, and then the residual noise can be removed effectively by applying a gain function based on thedecision-directedapproach. The objective measurement results show that the proposed postfiltering strategies outperform the conventional postfilter in terms of segmental signal-to-noise ratio (SNR) as well as speech quality improvement. Moreover, the AB subjective listening test shows that the preference percentages of the proposed strategies are over 60%.

Electroencephalogram (EEG) is a biomedical technique for capturing the human brain’s electrical information to process its activities and actions. EEG is one of the main methods commonly used in neuroscience, from clinical analysis to the design of brain–computer interfaces. The first one of the many challenges in an EEG system design regards the ultra-low amplitude of signals (i.e., of the order of $$20~\upmu \hbox {V}$$ ) and their susceptibility to several kinds of interferences. Electromagnetic interference (EMI) omnidirectionally irradiated by the power line supplies disturbs the EEG instrumentation system with a noise power mostly concentrated from 50 to $$60\,\hbox {Hz}$$ . Our paper investigates the energy efficiency of adaptive filtering (AF) techniques based on the least mean square (LMS), normalized LMS, and set-membership (SM) families for meeting the protection against EMI in EEG systems. The results demonstrate that the LMS algorithm presents an unstable behavior with unsatisfactory results against the normalized LMS filters when subject to noisy scenarios. Therefore, we herein explore dedicated VLSI hardware architectures for the following filters: (a) normalized LMS (NLMS), (b) SM-NLMS, (c) partial update NLMS (PU-NLMS), and (d) SM bi-normalized LMS (SM-BNLMS). PU-NLMS architecture offers the best trade-off between the capability of eliminating the EMI versus its power dissipation, circuit area, and maximum clock frequency. PU-NLMS provides an artifact reduction level of up to $$8.8\,\hbox {dB}$$ , with low energy consumption of 0.62 nJ/operation and just $$1.41\%$$ larger circuit area than the NLMS architecture.

Optical beam center position on an array of detectors is an important parameter that is essential for estimating the angle-of-arrival of the incoming signal beam. In this paper, we have examined the beam position estimation problem for photon-counting detector arrays, and to this end, we have derived and analyzed the Cramer-Rao lower bounds on the mean-square error of unbiased estimators of beam position. Furthermore, we have also derived the Cramer-Rao lower bounds of other system parameters such as signal peak intensity, and dark current noise power, on the array. In this sense, we have considered robust estimation of beam position in which none of the parameters are assumed to be known beforehand. Additionally, we have derived the Cramer-Rao lower bounds of beam and noise parameters for observations based on both pilot and data symbols of a pulse position modulation (PPM) scheme. Finally, we have considered a two-step estimation problem in which the signal peak and dark current noise intensities are estimated using a method of moments estimator, and the beam center position is estimated with the help of a maximum likelihood estimator.

For multi-microphone speech enhancement, different microphones might have different contributions, assome are even marginal. This is more likely to happen in wireless acoustic sensor networks (WASNs), where somesensors might be distant. In this work, we therefore consider sensor selection for linearly-constrained beamformers. Theproposed sensor selection approach is formulated by minimizing the total output noise power and constraining thenumber of selected sensors. As the considered sensor selection problem requires the relative acoustic transfer function(RTF), the covariance whitening based RTF estimation or a direct-path RTF approximation is exploited. For a singletarget source, we can thus substitute the estimated RTF or the assumed RTF to the original problem formulation in orderto design a minimum variance distortionless response (MVDR) beamformer. Alternatively, we can integrate the two RTFsto design a linearly constrained minimum variance (LCMV) beamformer in order to alleviate the effects of RTFestimation/approximation errors. By leveraging the superiority of LCMV beamformers, the proposed approach can beapplied to the multi-source case. An evaluation using a simulated large-scale WASN demonstrates that the integration ofRTFs for the sensor selection based LCMV beamformer can be beneficial as opposed to relying on either of theindividual RTF steered sensor selection based MVDR beamformers. We conclude that the sensors that are close to thetarget source(s) and also some around the coherent interferers are more informative.

In wireless relay systems, interference often leads to system rate loss. Recently, the research on radio-frequency signal energy harvesting makes it possible to use interference energy. In this paper, based on the time switching (TS) relay operation strategy and amplify-and-forward protocol, the simultaneous wireless information and power transfer relay system under strong interference is studied. Firstly, we propose an interference energy harvesting (IEH) scheme to reduce the rate loss. Three theorems are proved, and the approximate optimal interference energy allocation factor is obtained. Secondly, we propose two relay operation schemes under strong interference, namely static optimal TS ratio scheme and adaptive optimal TS ratio scheme. Then, the expressions of the two schemes are derived, and the corresponding optimization problems are established. The algorithms for solving these two problems are given. The numerical simulation results show that the IEH schemes with static and adaptive optimal TS ratio can effectively improve the system rate, while the latter has better performance than the former. In addition, the effects of interference power and antenna noise power on the system rate are also studied. The results show that the performance of the two schemes is better than that of the scheme without IEH under different interference power and noise power.

Edge traps in the gate oxide of silicon nanowire MOSFETs have been extracted from tunnel current noise measurement in a gated diode like arrangement. We have found that, low frequency noise in tunnel current results from collective response of the edge traps available within the gate oxide surrounding band-to-band generation (BTBG) region of silicon nanowire, and when the BTBG region is accessed by favorable terminal biases. From detail modeling of the phenomenon, we derived a closed form expression of the tunneling current noise power spectral density (PSD) employing which oxide edge trap density in nanowire MOSFET had been extracted through its fit with the experimental noise PSD data. We furthermore validated our model for different BTBG biases, and contrasted our result with the bulk oxide trap density in identical MOSFET, while the latter was separately estimated from the gate current noise PSD measurement. Mismatch between the oxide bulk trap and edge trap concentrations has been found, whereby actual edge trap density remains otherwise hidden from the widely employed gate current noise measurement technique. It is because, the present scheme improves the resolution of the extracted oxide edge trap concentration in surrounded gate MOSFET owing to constricted tunnel current flow near the corner of the gate which imposes selectivity on the oxide edge traps

This article presents the validation of a digital signal processing technique that can be used to estimate radiometric sky noise, and hence atmospheric absorption, within existing digital receivers at little/no additional cost. To demonstrate this, a receiver was constructed that simultaneously records the beacon signal power from the ALPHASAT Aldo Paraboni technology demonstration payload, as well as the integrated noise power in the adjacent band. Calibration from the digital radiometer is performed using tip-curve calibration procedures. Atmospheric fading is then obtained by observing the beacon as well as the radiometric signals. This enables the comparison of fading obtained by the two techniques and provides a means to calibrate the received beacon power level to obtain total atmospheric attenuation. It is shown that for low levels of fading, up to a few dB, the two techniques provide good agreement. This approach can, therefore, provide a low-cost option for geostationary mm-wave satellite channel measurements in the low fading regime, which can be useful in the design and operation of the feeder links in emerging satcom systems.

The automatic identification of the modulation format of a detected signal is a major task of an intelligent receiver in both military and civilian applications. It is well known that the maximum likelihood (ML) classifier requires a priori knowledge of the incoming signal and channel (including amplitude, timing information, noise power, and the roll-off factor of the pulse-shaping filter). To relax this requirement, we introduce a novel estimator to estimate the parameters required by the ML classifier which is blind to the modulation scheme of the received signal, and this gives rise to a new blind modulation classifier for digital amplitude-phase modulated signals. While the proposed classifier is completely blind, the simulation results show that the performance of this classifier is very close to the optimal non-blind classifier.

This study addresses an analogue method for mitigating the non-linearities introduced by discrete supply modulation of a high-efficiency power amplifier (PA). A 10 W two-stage X-band gallium–nitride monolithic microwave integrated circuit ( PA with a peak power-added efficiency of 55%, is tested with drain supply modulation from 10 to 20 V with an increase in efficiency and substantial degradation in linearity. In this work, the authors characterise the two-stage PA dynamically to develop shaping functions for both gate bias voltages. They demonstrate that gate modulation can improve back-off gain and linearity, specifically when gate biases of the two stages of a PA are independently modulated. Simultaneous gate and drain modulation results in 15 percentage point improvement in efficiency over a static supply, and a consistent improvement in noise power ratio over a static supply, for a 20 MHz noise-like signal. Results with a 20 MHz long-term evolution signal show comparable improvement in efficiency while maintaining adjacent channel power ratio near the level of the PA with a static supply.

The $\omega $ – $k$ synthetic aperture radar (SAR) algorithm is a computationally efficient algorithm for near-field 3-D monostatic SAR imaging in nondestructive testing (NDT) applications. However, bistatic measurements are preferred in order to obtain high dynamic range, in particular when real-time imaging arrays are used. This article investigates the image distortion caused by using an equivalent monostatic imaging algorithm for bistatic measurements. Simulations and measurements at millimeter-wave frequencies in the Ka-band (26.5–40 GHz) are used to investigate the resultant image distortion. Furthermore, the image distortion is quantified through the root-mean-square (rms) error, which is calculated as a function of the bistatic transmitter–receiver separation distance, range, and noise power. Simulations and measurements are conducted for imaging using the raster scanning of a pair of antennas and for nonuniform imaging arrays. In addition, an approximate method for phase compensation is introduced to improve the image error from the monostatic approximation of bistatic measurement.

This paper presents a high-efficiency linear GaN K-band transmitter for broadband high peak-average power ratio (PAPR) signals. A GaN MMIC 18.5–24 GHz three-stage power amplifier with over 4 W peak output power, 20 dB saturated gain, and 40% peak PAE is supply-modulated with a four-level discrete dynamic supply GaN MMIC. For 100 MHz signals with ${\rm PAPR}\gt 10\, {\rm dB}$, we demonstrate an average efficiency improvement from 14 to 20% with a simultaneous linearity improvement in noise power ratio (NPR) from 23 to 26 dB through a shaping function focused on gain linearization. For 250 MHz signal bandwidth, there is no observed degradation in NPR and the efficiency is improved by 5 percentage points. For discrete supply modulation, the switching transients between levels are experimentally investigated for wideband signals.

Introduction. The Gate-All-Around (GAA) Nanowire (NW) or nanosheet (NS) architecture provides superior short-channel effects control and is widely considered as one of the most promising candidates to replace finFETs in advanced Logic technology nodes. Compared with their horizontal implementation, vertical NWs (or NSs) FETs [1] offer some clear advantages, appearing promising devices to overcome some of the limitations encountered by conventional CMOS scaling as it reaches its physical limits and faces interconnect routing congestion. They have the potential to yield smaller circuits with reduced power consumption [2], allowing relaxed Lgate without impacting the device footprint. While their fabrication is challenging, several schemes have been proposed for improved process control and device performance [1]. In this work, the static parameters of vertical NW junctionless (JL) nMOSFETs have been studied for devices with two different Replacement Metal Gate (RMG) cap layer widths (see schematics in figure 1), encapsulating the top part of the pillars during processing at the RMG module. It will be shown that this strongly impacts the static device parameters: the threshold voltage (VT), the maximum transconductance (gmmax) and the dynamic output resistance (rout). Moreover, a correlation is shown with the input-referred voltage noise Power Spectral Density (PSD) SVG at 10 Hz, which could be explained in terms of a process-induced variation in the diameter D of the NWs. Experimental. A detailed process description has been recently reported [1]. A 55 nm in situ P-doped n+ layer is deposited by CVD on a low-resistivity silicon substrate (source contact), followed by 90 nm undoped silicon and again 55 nm n+ Si. The RMG stack consists of IL-SiO2/HfO2/TiN/W. An RMG cap consisting of SiO2 is used to encapsulate the top of the pillars. Here, devices with two different cap widths and 100 wires in parallel are compared. On-wafer DC and low-frequency noise measurements have been performed using a BT1500 Parameter Analyzer and an E4727A Advanced Low-Frequency Noise Analyzer from Keysight, respectively. Measurements have been performed in linear operation at a drain voltage VDS=50 mV, while the gate voltage VGS is stepped from weak to strong inversion. Results and Discussion. Figure 1 and 2 compares the linear input ID-VGS characteristics of a set of narrow and wide cap vertical NW nFETs. While there is obvious device-to-device variability, the wide-gap devices (Fig. 2) clearly exhibit a lower VT than their narrow-gap counterparts in Fig. 1. The transconductance (gm) plots of Figs 3 and 4 reveal another trend: devices with a high VT generally exhibit a lower gmmax and vice versa. This is even so within each flavour of devices in Figs 3 and 4. As will be shown, nFETs with a high(er) VT and lower gmmax also tend to exhibit a higher rout. Finally, Figs 5 and 6 demonstrate that the corresponding SVG at f=10 Hz is smaller for the wide-cap devices, especially around VT, where the minimum noise PSD is found. As will be shown, the noise spectra are dominated by 1/f-like noise (fVG could suggest a difference in oxide/interface trap density, but this is not reflected in the subthreshold swing nor in the PBTI behaviour [1]. On the other hand, it has been reported before that the VT of NW transistors increases for reduce D [3]. This could well explain also the lower gmmax (scales with D) and the higher SVG (scales with 1/D). The different NW diameter could result from the different dummy dielectric removal [1]. References [1] A. Veloso et al., to be published in the Proc. of IEDM 2019. [2] T. Huyng-Bao et al., SPIE 2016, 978102 [3] A. Veloso et al., J. Phys: Condens. Matter, 30, 384002 (2018). Figure 1

It is estimated that the emergence of digital businesses, and growing dynamic traffic demands for Internet applications, including cloud computing and the Internet of Things, will impact the traffic at unprecedented rates. Thus, to cost-efficiently accommodate these challenging requirements, network operators are motivated to maximize the achieved capacity over deployed links, and design more efficient networks capable of handling a wide range of applications, as well as operate more closely to optimality. On the other hand, as the network elements age, nonlinear impairments increases (which can be translated to increasing the network load) and hence, the system margin and maximum achievable rate decrease. Therefore, in order to increase the capacity of optical networks and extend their life time, an accurate physical model is required to estimate the quality of signal and quantify the margin of lightpaths. In this regard, a machine learning (ML) method is proposed based on the modular neural networks to account the cross channel nonlinear effects in estimating noise power and OSNR of lightpaths. For this, the dependence of the contributed nonlinear component of noise power on the transmitted powers as well as the modulation formats of all channels are considered in this data-model. Indeed, this ML-based model provides a useful tool for per-lightpath power management, as a fundamental element for reducing margins. Results of evaluating various proposed modular models show that, in general, all modular models are able to estimate OSNR of lightpaths, with average accuracy of more than 96.6%. However, the proposed $$ MM_{4} $$ modular model is the model presenting better generalization, being able to correctly estimate OSNR of lightpaths, with average accuracy of 99.2%. Also, $$ MM_{3} $$ model performs better for partially loaded network scenarios (99.3%).

In the automotive industry, electromagnetic susceptibility (EMS) difficulties are often identified in late stages of product development, causing unexpected additional costs of vehicles, electronic control units (ECUs), and integrated circuits (IC). To reduce such undesired costs, this letter presents an early stage placeEMS simulation of automotive IC which can be performed even before IC fabrication. Simulation before IC fabrication is important not only for IC vendors but also for first users of a new IC product because they often start the development of their own products (vehicles or ECUs) in the design stage of the new IC. An analog-to-digital converter (ADC) is chosen as the target circuit of this letter. It is a challenging target because the circuit is too complex to run numerous simulations for many diverse noise power and frequency points. The target is also sensitive even to very small (several-millivolt) noise. To run such challenging simulations with practical time and satisfactory accuracy, four key points are implemented: (1) consideration of the possible noise propagation paths, (2) simplified ADC model, (3) handling of nonlinearity, and (4) calculation of forward power. Simulation results show good consistency with measurement results obtained for two printed circuits boards (PCBs) by approximately 8 dB error in most frequency points. Consequently, the proposed simulation is helpful to reduce unexpected additional costs by predicting EMS risks and assessing the effects of the improvement method quantitatively in early product design stages.

Low-frequency 1/f voltage noise has been employed to probe stochastic charge dynamics in AlOx-based non-volatile resistive memory devices exhibiting both resistive switching (RS) and magneto-resistive (MR) effects. A 1/f noise power spectral density is observed in a wide range of applied voltage biases. By analyzing the experimental data within the framework of Hooge’s empirical relation, we found that the Hooge’s parameter and the exponent exhibit a distinct variation upon the resistance transition from the low resistance state (LRS) to the high resistance state (HRS), providing strong evidence that the electron trapping/de-trapping process, along with the electric field-driven oxygen vacancy migration in the AlOx barrier, plays an essential role in the charge transport dynamics of AlOx-based RS memory devices. post-print 973 KB

For wireless systems, interfering signals from the surrounding environment is a serious threat to the performance of the system. A measurement system with the aim to autonomously detect and log interference incidents, particularly in the GPS bands, has been developed and used to collect data. Three measurement systems were placed in various locations at an international airport in Sweden, and have continuously recorded both background noise and interference incidents on GPS L1. In this paper, recordings from measurements performed during one year, starting in November 2019, are presented. Variations in noise levels over both time and between measurement locations have been investigated. All locations showed a diurnal variation in the mean noise power, with slightly higher mean noise at night. In contrast, the number of detected interference incidents were higher during daytime.

This paper is focused on the extraction of the noise parameters of a linear active device by exploiting both forward and reverse noise power measurements associated with different terminations. In order for load-pull measurements to yield a significant marginal improvement (as compared to forward measurements only) it is expected that the device under test should appreciably deviate from unidirectionality. For this reason, the source/load-pull technique is applied to frequencies at which the considered devices are still usable but their reverse noise factor exhibits a measurable dependence on the output terminations. Details on the test bench set up to the purpose, covering the 20–40 GHz frequency range, are provided. A characterization campaign on a 60 nm gate length, 4×35 µm GaN-on-Si HEMT fabricated by OMMIC is illustrated.

Made available in DSpace on 2022-04-28T19:40:55Z (GMT). No. of bitstreams: 0 Previous issue date: 2021-09-01 In this paper, the noise Power Spectral Density (PSD) of AlGaN/GaN High-Electron-Mobility Transistors (HEMTs) has been experimentally investigated in linear operation (VD = 50 mV) for different channel lengths (L) and widths (W) at different temperatures (5.32 °C till 100 °C). The origin of the noise will be analyzed to understand the physical mechanisms involved. It is shown that the Low-Frequency (LF) noise is dominated by 1/f noise, originating from number fluctuations. Additionally, in shorter devices, a higher 1/f noise PSD is found. The LF noise characteristics indicate that the AlGaN/GaN HEMTs on silicon substrates can be a promising candidate for analog and Radio Frequency applications (RF). São Paulo State University (UNESP) Institute of Science and Technology, Av. 3 de Março, n. 511 National Inst. of Technol. Kumamoto College Depart. of Information Commun. and Electron. Eng., 2659-2 Suya, Koshi IMEC, Kapeldreef 75 Vrije Universiteit Brussels, Pleinlaan 2 São Paulo State University (UNESP) Institute of Science and Technology, Av. 3 de Março, n. 511

In this paper, DC and low-frequency noise characteristics of AlGaN/GaN high electron mobility transistors (HEMTs) with different gate-to-source lengths (L GS ) are presented. Due to the different (L GS ), the device with shortest shows highest transconductance (g m ) and drain current. But the threshold voltages (V TH ) are the same for all devices. In low-frequency noise measurement, not only flicker noise (1/f noise) exists also accompany by generation-recombination noise (G-R) noise). Noise power spectral densities (PSD) are similar in devices with different L GS , and 1/f noise shows carrier number fluctuation (CNF) is the dominant cause. In addition, this paper discussed the G-R noise and extracted the traps in GaN buffer layer with activation energy of $\sim 0.35 \text{eV}$.

In Wireless Communication, equalizer is used to inverse the bending caused by a signal transmitted through a channel. Need of equalization is to decrease the effects of Inter Symbol Interference (ISI) without suppression of signal, but the noise power enhancement should be prevented with this reduction of ISI. Hence there is a requirement of less complex, more efficient Adaptive equalizer which suppresses the error and increases the efficiency in communication channel. In this paper the algorithm for the adaptive equalizer is proposed and performance is compared with Least Mean Square (LMS), Normalized Least Mean Square (NLMS) and Recursive Least Square (RLS) algorithm using 3 parameters; speed, power and area. The proposed Hybrid filter is efficient compared to LMS, NLMS and RLS in speed of execution and area utilization. The power consumption of this hybrid filter is higher than the LMS, NLMS and lesser than RLS.

The satellite navigation integrity monitoring technology is closely related to the reliability of train positioning. It is of great significance to study satellite navigation Receiver autonomous integrity monitoring (RAIM) algorithm suitable for train positioning. Some existing conventional RAIM algorithms do not consider the influence of satellite navigation signal on algorithms performance. Aiming at the influence of satellite navigation signal on the propagation processes, such as shadow and multipath effects, the fault detection algorithm based on BeiDou navigation satellite system (BDS) baseband signal is proposed. The innovation parameters contained in the satellite navigation baseband signal are combined into the covariance matrix to set up a new test statistics of RAIM. A new fault detection algorithm based on optimized BDS baseband signal is discussed. And combined with weighted least square method, the noise power balance factor is established to realize satellite fault detection. Experimental results show that the proposed algorithm can improve the monitoring performance of train satellite positioning integrity, and lay the foundation for meeting the railway industry's security requirements for positioning services.

Conduction characteristics and low frequency noises in ITO-stabilized ZnO thin film transistors (TFTs) with constant channel width (W=50 μm) and different channel lengths (L=5, 10, 25, 50 and 100 μm) are measured and analysis. Firstly, dependences of threshold voltage and field effect mobility on channel length are examined. With decreasing channel length, the threshold voltage shifts to the negative direction which may attribute to carrier diffusion from source/drain to the intrinsic device channel. In addition, significant degradation of field effect mobility is observed in short channel device which are induced by the presence of series contact resistance. The value of contact resistance has also been extracted. Secondly, the drain current noise power spectral densities (SID) are measured at varied effective gate voltages. The measured noises follow a 1/fγ and y is about -1.1. Moreover, the normalized noises (SID/Ids) are dependent linearly on the inverse of channel length and the slope is about -0.75. Finally, the dominant mechanism of low frequency noise in ITO-stabilized ZnO thin film transistor are examined. The slope of normalized noise against effective gate voltage are extracted, which are varied from -1.03 to -1.84 with decreasing channel length and thus it indicates that ITO-stabilized ZnO TFTs varied from bulk dominated devices to interface dominated devices. By using of ΔN-Δμ model, the normalized noises are simulated by considering of contact resistance. Several noise parameters (flat-band voltage noise spectral density, etc) are extracted and analysis.

Resumen: OFDM (Orthogonal Frequency Division Multiplexing) es una tecnología de comunicación inalámbrica que tiene ventajas como alta eficiencia espectral, alta tasa de transmisión y es robusta a la propagación por mulitrayecto. Sin embargo, su principal desventaja es que tiene alta PAPR (Peak-to-Average Power Ratio). Este artículo presenta la evaluación de la técnica OPS (Orthogonal Pilot Sequence) para la reducción de la PAPR en un sistema OFDM con canal multitrayecto. Para la evaluación se consideran dos tipos de canales multitrayecto selectivos en frecuencia, con y sin línea de vista. Se evalúa OPS obteniendo la gráfica del BER (Bit Error Rate) vs Eb/No (energy per bit to noise power spectral density ratio) y la gráfica de la CCDF (Cumulative Complementary Distribution Function) para distintos parámetros. Los resultados muestran una reducción de la PAPR cuando se utiliza la técnica OPS y una mejora en el BER. Palabras clave: OPS, PAPR, OFDM, Canal multitrayecto.

Because it is relatively difficult in practice to classify the Raman spectrum under baseline noise and additive white Gaussian noise environments, this paper proposes a new framework based on a wavelet transform and deep neural network for identification of noisy Raman spectra. The framework consists of two main engines. Wavelet transform is proposed as the framework front end for transforming the 1-D noise Raman spectrum to two-dimensional data. The two-dimensional data are fed to the framework back end, which is a classifier. The optimum classifier is chosen by implementing several traditional machine learning (ML) and deep learning (DL) algorithms, and we investigate their classification accuracy and robustness performances. The four chosen MLs are naive Bayes (NB), a support vector machine (SVM), a random forest (RF) and a k-nearest neighbor (KNN), and a deep convolution neural network (DCNN) was chosen as a DL classifier. Noise-free, Gaussian noise, baseline noise, and mixed-noise Raman spectra were applied to train and validate the ML and DCNN models. The optimum back-end classifier was obtained by testing the ML and DCNN models with several noisy Raman spectra (10-30 dB noise power). Based on the simulation, the accuracy of the DCNN classifier is 9% higher than that of the NB classifier, 3.5% higher than the RF classifier, 1% higher than the KNN classifier, and 0.5% higher than the SVM classifier. In terms of robustness to mixed noise scenarios, the framework with the DCNN back end showed superior performance compared with the other ML back ends. The DCNN back end achieved 90% accuracy at 3 dB SNR, while the NB, SVM, RF, and K-NN back ends required 27 dB, 22 dB, 27 dB, and 23 dB SNR, respectively. In addition, in the low-noise test dataset, the F-measure score of the DCNN back end exceeded 99.1%, and the F-measure scores of the other ML engines were below 98.7%.

Los altos requerimientos inalámbricos en acceso, capacidad y seguridad que demanda la sociedad actual junto con la gran congestión del espectro radioeléctrico ha llevado a buscar nuevas soluciones tecnologías como es la Fidelidad de la Luz (Li-Fi). Este artículo presenta el diseño e implementación de un sistema de comunicaciones Li-Fi dentro de un ambiente indoor utilizado la técnica de modulación OFDM óptica con recorte asimétrico (ACO-OFDM) a través del software MATLAB. El desempeño del sistema se analiza en términos de la tasa de error de bit (BER) y la relación energía de bit a potencia de ruido (Eb/No) teniendo en cuenta la posición del receptor, orden de modulación QAM y velocidad de transmisión. Los resultados muestran que el desempeño del sistema depende directamente de la posición del receptor, además para altas tasas de transmisión el efecto multitrayectoria degrada el desempeño del sistema.

We perform phase noise characterization of a tunable laser source that is capable of tuning to 103 channels between 1527.6-1568.36 nm with 50 GHz grid spacing between the channels. The measured frequency modulation (FM) noise power spectral density (PSD) is reproduced by simulations in order to investigate the impact of equalization-enhanced phase noise (EEPN) in a coherent transmission system. The simulations are performed on a 30 Gbaud channel with 16 quadrature amplitude modulation (16QAM) and using pilot-based carrier phase estimation with 3% overhead. By performing extensive system simulations, we show the impact of different accumulated dispersion. Furthermore, we show the possibility to overcome EEPN related penalties by using a local oscillator (LO) with reduced low frequency phase noise or flat FM-noise PSD profiles with lower linewidths.

Purpose To evaluate the quantitative accuracy and dose efficiency of simultaneous imaging of two contrast agents using dual-energy computed tomography (DECT), two imaging tasks each representing one potential clinical application were investigated in a phantom study: biphasic liver imaging with iodine and gadolinium, and small bowel imaging with iodine and bismuth. Methods To separate and quantify mixtures of two contrast agents using a single DECT scan, mixed iodine and gadolinium samples were prepared with the contrast enhancement values corresponding to the late arterial (iodine) and the portal-venous (gadolinium) phase for biphasic liver imaging. Mixed iodine and bismuth samples were prepared mimicking the arterial (iodine) and the enteric (bismuth) enhancement for small bowel imaging. For comparison to the reference condition of performing two single-energy CT (SECT) scans, contrast samples were prepared separately to mimic separate scans in the arterial/venous phase and arterial/enteric enhancement. Samples were placed in a 35 cm wide water tank and scanned using a third-generation dual-source DECT scanner with three tube potential pairs: 80/Sn150, 90/Sn150, and 100/Sn150 kV, all with default dose partitioning between two x-ray beams to acquire DECT data. The same scanner operated in a single-energy mode acquired SECT data (120 kV). Total radiation dose (CTDIvol) was matched for the single-scan DECT and the two-scan SECT protocols. The DECT protocol was followed by a generic image-based three-material decomposition method to determine the material-specific images, based on which concentrations of each basis material were quantified and noise levels were measured. To compare with the SECT images directly acquired with the SECT protocol, the concentration values in each contrast-specific image were converted to CT numbers at 120 kV (i.e., virtual SECT (vSECT) images). The noise level and noise power spectra differences between the SECT and vSECT images were compared to evaluate the dose efficiency of the single-scan DECT protocol. The impact of dose partitioning in the DECT protocol on quantitative dual-contrast imaging performance was also studied. Results For each imaging task, contrast materials were accurately quantified against the nominal concentrations using the DECT data with strong correlation (R2 ≥ 0.98 for both imaging tasks). Compared to the SECT protocol, the DECT protocol was not dose efficient. With the optimal x-ray tube potential pair 80/Sn150 kV, the noise level in vSECT images increased by 401%/488% (arterial/portal-venous) for the biphasic liver imaging task and by 10%/41% (arterial/enteric) for the small bowel imaging task compared to that in SECT images. The corresponding radiation dose increase is 2410%/3357% for the biphasic liver imaging task and 21%/99% for the small bowel imaging task, respectively, to achieve the same noise as that in SECT images. This could be improved by adjusting the dose partitioning in DECT. Conclusions DECT can be used to simultaneously separate and quantify two contrast materials. However, compared to a two-scan SECT protocol, much higher radiation dose is needed in a single-scan DECT protocol to achieve the same image noise, especially for tasks involving the dual contrast of iodine and gadolinium.

The study considers the possibility of changing the isotopic composition of a substance to improve the physical properties of the material and the optoelectronic characteristics of a photodetector as the most common device in optoelectronics. It is shown that the reduction of heavy isotopes in the semiconductor material of photodetectors increases the mobility of charge carriers, the light absorption coefficient, and quantum efficiency, while reducing the number of band gap sublevels that affect the dark current. This increases the photodetector sensitivity, decreases the magnitude of the dark current, and improves the signal power to noise power ratio at the output of the photodetector. Technologies for improving the properties of a material by improving the characteristics of bulk semiconductor crystals, multiple quantum wells, and superlattices are compared.

Noise power spectral density (NPSD) in time domain terahertz (THz) wave detection systems utilizing GaAs-based photoconductive antennas (PCAs) was investigated quantitatively. The contributions of the PCA noise and the amplifier noises at the amplifier output depend strongly on the resistance of the PCA, the circuit parameters, and the frequency. The PCA has two types of noise: one can be modeled by the Johnson-Nyquist (thermal) noise for the PCA resistance, while the other has an NPSD inversely proportional to the frequency with its intensity dependent on the properties of the GaAs and the metallization. At a high frequency range ~ 100 kHz, voltage-type amplifier noise could appear if the cable capacitance between the PCA and the amplifier is large. As a result, a low-noise range tends to appear in the intermediate frequency range. In comparison with the PCAs with Ti/Au metallization, the PCAs with Pd/Ge/Ti/Au having lower contact resistance lead to lager influence of the Johnson-Nyquist noise at the output.

Spectrum sensing is a fundamental component in multi-user free space optical communication systems. In order to avoid interference among the users, it is required to periodically sense the optical frequency spectrum to detect if the channel is occupied by active transceiver pairs. Spectrum sensing allows the user to continuously sense the optical spectrum within their operating range to detect the channels. In this paper, we propose a generic novel blind spectrum sensing scheme for an unknown optical signal over strong atmospheric turbulence channel. By generic, we mean that the proposed scheme is applicable to all optical wavelengths, i.e. ultraviolet (UV), visible light, and infrared. The proposed blind spectrum sensing scheme is based on the estimated signal-to-noise ratio (SNR) and the noise power, for which we have derived expressions from a statistical ratio of the received signal. The atmospheric turbulence is the main reason behind the signal fading in free space optical links as it causes fluctuations in the received signal intensity. To mitigate this adverse effect, the proposed scheme is equipped with a spatial diversity scheme in the form of switch-and-stay combining. We use Gamma–Gamma distribution to model both small-scale and large-scale turbulence fadings. From the estimated SNR and noise power expressions, we formulate the novel closed-form expressions for the probabilities of detection and false alarm mathematically. Numerical and simulation results based on randomly generated optical signals are presented to verify the effectiveness of the proposed scheme.

Constrained by the transimpedance limit, the conventional 1-stage shunt-feedback transimpedance amplifier (1S-SF-TIA) suffers poor noise and gain at higher data rates. In this paper, we propose to use a multi-stage stagger-tuned amplifier (MSTA) to constitute TIA (MSTA-TIA), which not only transcends the transimpedance limit of 1S-SF-TIA, but also realizes noise reduction in multiple fronts. First, the high-gain MSTA enables 17X TIA gain over 1S-SF-TIA, which effectively suppresses the white noise. Second, the MSTA realizes at least 2.8X~1.6 lower noise than the conventional multi-stage amplifier, which is essential to form low-noise TIA since the amplifier noise usually dominates. Third, the TIA built upon the 3-stage STA also shows steeper out-of-band roll-off to enable high-frequency noise reduction. Overall, the MSTA-TIA achieves 6.9X and 1.9X noise power reduction over conventional single-stage and multi-stage SF-TIAs. As a demonstration, a 10 Gb/s optical receiver front-end prototype employing proposed MSTA-TIA topology is implemented in a standard $0.18~\mu \text{m}$ CMOS technology. It achieves transimpedance gain of 68.3dB $\Omega $ , electrical bandwidth of 8.5GHz, and excellent input-referred noise current of $0.97~\mu $ Arms. The chip occupies 0.78 mm2 while consuming 43 mA from 1.8 V power supply. The low-noise design methodology in this paper empowers mature CMOS to compete with SiGe to make low-noise high-gain optical IC.

Purpose Convolutional neural network (CNN)-based image denoising techniques have shown promising results in low-dose CT denoising. However, CNN often introduces blurring in denoised images when trained with a widely used pixel-level loss function. Perceptual loss and adversarial loss have been proposed recently to further improve the image denoising performance. In this paper, we investigate the effect of different loss functions on image denoising performance using task-based image quality assessment methods for various signals and dose levels. Methods We used a modified version of U-net that was effective at reducing the correlated noise in CT images. The loss functions used for comparison were two pixel-level losses (i.e., the mean-squared error and the mean absolute error), Visual Geometry Group network-based perceptual loss (VGG loss), adversarial loss used to train the Wasserstein generative adversarial network with gradient penalty (WGAN-GP), and their weighted summation. Each image denoising method was applied to reconstructed images and sinogram images independently and validated using the extended cardiac-torso (XCAT) simulation and Mayo Clinic datasets. In the XCAT simulation, we generated fan-beam CT datasets with four different dose levels (25%, 50%, 75%, and 100% of a normal-dose level) using 10 XCAT phantoms and inserted signals in a test set. The signals had two different shapes (spherical and spiculated), sizes (4 and 12 mm), and contrast levels (60 and 160 HU). To evaluate signal detectability, we used a detection task SNR (tSNR) calculated from a non-prewhitening model observer with an eye filter. We also measured the noise power spectrum (NPS) and modulation transfer function (MTF) to compare the noise and signal transfer properties. Results Compared to CNNs without VGG loss, VGG-loss-based CNNs achieved a more similar tSNR to that of the normal-dose CT for all signals at different dose levels except for a small signal at the 25% dose level. For a low-contrast signal at 25% or 50% dose, adding other losses to the VGG loss showed more improved performance than only using VGG loss. The NPS shapes from VGG-loss-based CNN closely matched that of normal-dose CT images while CNN without VGG loss overly reduced the mid-high-frequency noise power at all dose levels. MTF also showed VGG-loss-based CNN with better-preserved high resolution for all dose and contrast levels. It is also observed that additional WGAN-GP loss helps improve the noise and signal transfer properties of VGG-loss-based CNN. Conclusions The evaluation results using tSNR, NPS, and MTF indicate that VGG-loss-based CNNs are more effective than those without VGG loss for natural denoising of low-dose images and WGAN-GP loss improves the denoising performance of VGG-loss-based CNNs, which corresponds with the qualitative evaluation.

The standard approach to signal difference-to-noise ratio (SDNR) analysis requires a region of interest (ROI) positioned within the object to measure signal-difference, restricting this metric to flat-topped objects with large, sharply delineated areas. This work develops a generalized expression for SDNR (SDNR g ) calculated from a ROI encompassing the object. Signal power, defined as the deviation of pixel values from the mean background due to the object, is used instead of signal-difference. Comparison was first made by simulating ideal flat-topped discs with sharp edges and diameters between 1 and 80 pixels, into a uniformly noisy background using a known signal-difference. For discs covering more than 20 pixels, SDNR g and standard SDNR (SDNR st ) were within 3%, while for discs of less than 20 pixels, SDNR g was within 26% of the truth compared to 58% for SDNR st . Generalized and standard SDNR were compared for radiography images of three different phantoms with microcalcification-like objects (MTM-100 phantom), hemispheric objects of different thicknesses with a Gaussian intensity distribution and mammography quality control (QC) images. Applied to Gaussian details, SDNR g was between 20% and 45% higher than SDNR st , depending on object thickness, while for the QC images, SDNR g was with 1.7% of the standard SDNR. Compared to the standard SDNR, SDNR g is applicable to non-uniform signals, where an explicit contrast measurement is not suitable, and has improved accuracy when assessing SDNR of small objects.

Background Digital breast tomosynthesis (DBT) is a three-dimensional breast imaging method. DBT vendors employ various approaches in both image acquisition and data processing, which may affect image quality and radiation exposure to patients. Objective This study aimed to evaluate the performance of five DBT systems: Fujifilm Amulet Innovality (using both a standard mode and high-resolution mode), GE Senographe Essential, Hologic Selenia Dimensions, Planmed Clarity 3D, and Siemens Mammomat Inspiration. Materials and methods The performance of each device and imaging technique was evaluated and compared by phantom measurements performed with four quality assurance phantoms. Technical image quality assessments consisted of measuring artefact extent, in-plane resolution, relative noise power spectrum, and geometric accuracy. Results Artefact spreading varied remarkably between the devices, and the full width at half maximum values of artefact spread functions varied from 3.5 mm to 10.7 mm. Noticeable in-plane resolution anisotropy, determined using modulation transfer function (MTF) analysis, was typically observed between tube travel direction and chest wall-nipple direction. The MTF50 varied from 1.1 mm−1 to 1.6 mm−1 and from 1.5 mm−1 to 4.1 mm−1 in the tube travel and chest wall-nipple directions, respectively. Moreover, distinctly different noise power spectra were observed between the systems. The geometric accuracy in every system was within 0.5%. Conclusion Technical image quality assessments with image quality phantoms revealed remarkable differences in artefact spread, in-plane resolution, and noise properties between the DBT systems and imaging methods.

The paper is devoted to questions on increasing of noise immunity of GPS/INS navigation systems containing GPS and inertial navigation systems. Analysis of effectual methods for digital processing of noisy signals of GPS/INS navigation systems is actual task. At the same time there is another direction of development of GPS navigation systems, based on modification of aerial tract and filtration devices. Different adaptive methods of multi-aerial receipt can be stressed out as an example. As regards the filtration method, there are some additional possibilities for filtration of noisy GPS signals upon presence of a priory or a posteriori data on energy-frequency characteristics of noise signal. The comparative analysis of methods for increasing of noise immunity of integrated GPS/INS navigation systems is carried out. The possibility for optimization of averaged integrated value of modified indicator, named as effective ratio of power of carrier signal on noise power regarding the case of utilization of noise signals pertaining to broad class of noise signals characterized by presence of integrated limitation condition imposed on amplitude-frequency spectrum. The optimization task on increase of averaged integrated parameter indicating the effective value of ratio of power of carrier signal on power of noise signal is formulated. Solution of formulated optimization task make it possible to formulate recommendations for increasing the noise immunity of GPS/INS based navigation systems for some limited class of utilized jamming noise. The methodic to increase noise immunity of GPS targeting systems in condition of jamming noise is suggested., Статья посвящена вопросам повышения помехоустойчивости GPS/INS навигационных систем. Изложен предлагаемый новый способ повышения помехоустойчивости GPS навигационных систем. Приведён сравнительный анализ методов повышения помехоустойчивости интегрированных GPS/Ins систем навигации. В качестве одного из основных показателей отношения сигнал-шум выделен модифицированный показатель, известный под названием эффективное отношение мощности несущего сигнала к мощности шумов. Сформулирована оптимизационная задача повышения среднеинтегрированного показателя «эффективная величина» отношения мощности и несущего сигнала к мощности шумового сигнала. Рассмотрена возможность оптимизации среднеинтегрированной величины рассматриваемого модифицированного показателя в случае применения в качестве шумового сигнала представителя достаточно широкого класса помеховых сигналов, характеризующихся наличием интегрального ограничения на амплитудно-частотный спектр. С учетом исходного целевого функционала и интегрального ограничительного условия, наложенного на шумовые сигналы, составлен целевой функционал безусловной вариационной оптимизации. Решение сформулированной оптимизационной задачи с применением условий уравнения Эйлера-Лагранжа позволило выработать рекомендацию по повышению помехоустойчивости GPS основанных навигационных систем для некоторого ограниченного класса используемых заглушающих помех. На основании полученных результатов составлена методика повышения помехоустойчивости GPS систем наведения в условиях применения заглушающей помехи рассмотренного класса., Статтю присвячено питанням підвищення завадостійкості GPS/INS навігаційних систем, що включають в себе GPS та інерціальні навігаційні пристрої. Пошук ефективних шляхів цифрової обробки зашумлених сигналів навігаційних систем є актуальним завданням, разом з тим, існує також інший напрямок розвитку GPS навігаційних систем, що заснований на удосконаленні антенного тракту і кутів фільтрації. Сюди можна віднести різні адаптивні методи рознесеного прийому. Що стосується методу фільтрації, то тут існують деякі додаткові можливості фільтрації зашумленного GPS сигналу за наявності апріорних або апастеріорних даних про енергочастотні характеристики шумового сигналу. Наведено порівняльний аналіз методів підвищення завадостійкості інтегрованих GPS/Ins систем навігації. Розглянуто можливість оптимізації середньоінтегрірованної величини модифікованого показника, названого ефективним відношенням потужності сигналу до потужності шумів відносно до випадку застосування в якості шумового сигналу представників досить широкого класу сигналів завад та характеризуються наявністю інтегрального обмеження на амплітудно-частотний спектр. Сформульована оптимізаційна задача підвищення средньоінтегрірованого показника «ефективна величина» відношення потужності сигналу до потужності шумового сигналу. Рішення сформульованої оптимізаційної задачі дозволило виробити рекомендації щодо підвищення завадостійкості GPS / INS заснованих навігаційних систем для деякого обмеженого класу використаних перешкод. Запропоновано методику підвищення завадостійкості GPS систем наведення в умовах застосування перешкод.

This study applied a vapor cooling condensation system for depositing p-ZnO:LiNO3, i-Ga2O3, and n-Ga2O3:Si layers on sapphire substrates to fabricate solar-blind p-i-n deep-ultraviolet photodetectors (DUV-PDs). The deposited i-Ga2O3 absorption layer was measured to exhibit high performance levels. Therefore, when the resulting solar-blind p-i-n DUV-PDs were operated at a reverse bias voltage of − 5 V, the dark current and the DUV (250 nm)/visible (500 nm) rejection ratio were 1.45 pA and 2.5 × 104, respectively. Moreover, when the solar-blind p-i-n DUV-PDs were operated at a reverse bias voltage of − 5 V, the photoresponsivity, noise power density, noise equivalent power, and specific detectivity were 0.73 A/W, 2.45 × 10−26 A2/Hz, 4.80 × 10−13 W, and 1.97 × 1012 cmHz0.5W−1, respectively. Furthermore, flicker noise was the dominant low-frequency noise source in the photodetectors. These results demonstrated the effectiveness of the proposed solar-blind p-i-n DUV-PDs.

This paper presents a noise circulating cross-coupled voltage-controlled oscillator (VCO) topology with a transformer-based tank. The introduced noise circulating active core greatly suppresses the effective noise power from the active devices while offering the same amount of negative resistance compared to conventional cross-coupled VCO topologies. The mechanism of noise circulation is investigated with theoretical analysis and further verified by simulation. Due to the broadband nature of the noise circulating technique, the resulting VCO phase noise in both 1/ $f^{2}$ and 1/ $f^{3}$ regions is greatly improved over a wide frequency tuning range. A prototype VCO at 2.35 GHz is implemented in a standard 130-nm bulk CMOS process with 0.36-mm2 core area. It draws 2.15 mA from a 1.2-V supply. The measured figure-of-merit (FoM) is 193.1/195.0/195.6 dBc/Hz at 100k/1M/10MHz offsets with a 1/ $f^{3}$ phase noise corner of only 50 kHz. The VCO design consistently achieves >192.8 dBc/Hz FoM at 100k/1M/10MHz offsets and $f^{3}$ phase noise corner over its entire 18.6% frequency tuning range (2.05 − 2.47 GHz). It also exhibits low supply frequency pushing of −25 and −13 MHz/V at the highest and lowest frequencies, respectively.

—The study considers the possibility of changing the isotopic composition of a substance to improve the physical properties of the material and the optoelectronic characteristics of a photodetector as the most common device in optoelectronics. It is shown that the reduction of heavy isotopes in the semiconductor material of photodetectors increases the mobility of charge carriers, the light absorption coefficient, and quantum efficiency, while reducing the number of band gap sublevels that affect the dark current. This increases the photodetector sensitivity, decreases the magnitude of the dark current, and improves the signal power to noise power ratio at the output of the photodetector. Technologies for improving the properties of a material by improving the characteristics of bulk semiconductor crystals, multiple quantum wells, and superlattices are compared.

This paper describes an energy-efficient bridge readout IC (ROIC), which consists of a capacitively coupled instrumentation amplifier (CCIA) that drives a continuous-time delta–sigma modulator (CT $\Delta \Sigma \text{M}$ ). By exploiting the CCIA’s ability to block dc common-mode voltages, the bridge’s bias voltage may exceed the ROIC’s supply voltage, allowing these voltages to be independently optimized. Since bridge output is typically much smaller than bridge offset, a digital to analog converter (DAC) is used to compensate this offset before amplification and thus increase the CCIA’s useful dynamic range. Bridge loading is reduced by using a dual-path positive feedback scheme to boost the CCIA’s input impedance. Furthermore, the CCIA’s output is gated to avoid digitizing its output spikes, which would otherwise limit the ROIC’s linearity and stability. The ROIC achieves an input-referred noise density of 3.7 nV/ $\surd $ Hz, a noise efficiency factor (NEF) of 5, and a power efficiency factor (PEF) of 44, which both represent the state of the art. A pressure sensing system, built with the ROIC and a differential pressure sensor (AC4010), achieves 10.1-mPa ( $1\sigma$ ) resolution in a 0.5-ms conversion time. The ROIC dissipates about 30% of the system’s power dissipation and contributes about 6% of its noise power. To reduce the sensor’s offset drift, a temperature compensation scheme based on an external reference resistor is used. After a two-point calibration, this scheme reduces bridge offset drift by $80\times $ over a 50 °C range.

The delayed self-heterodyne interferometer (DSHI) is a simple and effective method of measuring the laser linewidth. However, conventional DSHIs generally cannot measure a full laser frequency noise power spectral density (PSD). In this article, we theoretically analyzed the PSD of the DSHI beat signal, and propose a new method to extract the PSD of the laser frequency noise directly from the PSD of the DSHI beat signal. Compared with the methods already established, our method does not need an additional frequency demodulation technique, and a full laser frequency noise PSD can be measured by using a short delay fiber. The experimental scheme is simple and can reach a high spectral resolution. The applicable conditions, resolution and influences of the experimental parameters of the method are also analyzed. An experiment is conducted to verify the proposed method. By using a 1.1 km delay fiber, the frequency noise PSD of an optical cavity-locked diode laser is evaluated for frequency range between 100 Hz and 1 MHz.

This short paper presents a new approach to the calculation of Savitzky–Golay differentiators based on symmetric differentiation. Some comparisons with the regular polynomial derivative are made in order to find differences and similarities between the two methods. The evaluation shows that the new symmetric differentiation approach presents lower noise power gain, which is an interesting characteristic for digital signal processing purposes.

The detection in the THz band is significant due to practical importance in various fields requiring high sensitivity, detection accuracy, and cost reduction. The structures based on graphene / superconductor cause a significant increase in the supercurrent thanks to the inherent and unique properties of graphene, such as high mobility and density of the carriers in the tunneling process. In the meantime, due to its flexibility in controlling performance and compatibility with large-scale integration, the field effect transistor has been transformed to one of the best options for the implementation of tunabe THz detectors. Therefore, in this study, a graphene Bolometer detector based on a field effect transistor is proposed. The influence of various parameters such as temperature and gate voltage on the V-I characteristic was investigated. Thermal conductivity, equivalent noise power and coupling radiated power were evaluated. The calculations indicate high precision of low noise and optimal response to temperature variations.