In-phase Components Research Articles

Research on digital silicon gyroscope interface circuit based on bandpass sigma-delta modulator

This paper presents a novel digital silicon gyroscope interface circuit, designed by 0.35 [Formula: see text]m BCD process, and the chip area is 4.8 mm ∗ 5.0 mm. The traditional noise model of charge amplifier decomposes the noise into voltage noise and current noise. But the test results show that current noise accounts for a large proportion, which is not consistent with the theoretical model. Through the analysis of experimental data and the study of operational amplifier’s working principle in charge amplifier, a new noise model is established, which makes the experimental data closer to the theoretical model. The design makes use of the bandpass characteristics of the bandpass sigma–delta modulator consistent with the sensitive structure of the silicon gyroscope, and optimizes the digital principle of the silicon gyroscope. The digital demodulation of bandpass sigma–delta modulator (BP SDM) can directly separate the in-phase component from the orthogonal component, which eliminates the tedious design of carrier signal digitization and multi-digital filtering, simplifies the frame structure of the whole digital silicon gyroscope system and reduces the design difficulty and physical cost. The ASIC of silicon gyroscope digital interface circuit is tested in combination with the sensitive structure. The noise density of 0.0014[Formula: see text]/s/Hz[Formula: see text], zero stability of 1[Formula: see text]/[Formula: see text]h (1[Formula: see text]) and 0.2[Formula: see text]/[Formula: see text]h (Allen variation). The test of ASIC and the whole machine proves the correctness of the theoretical model, which reflects the correctness of the performance of the digital interface circuit of silicon gyroscope.

A Discrete-Time Frequency-Locked Loop for Single-Phase Grid Synchronization Under Harmonic Distortion

This article presents a discrete-time frequency-locked-loop (FLL) scheme that estimates the in-phase fundamental component of a distorted single-phase reference signal and its fundamental angular frequency. The proposed scheme also estimates the square-phase fundamental component as a set of orthogonal signals. The proposed design is based on an exact discrete model of a single-phase signal generator. It is shown that the proposed method provides an accurate response even under low sampling frequency. The proposed scheme includes, as a plug-in block, an explicit harmonic compensation mechanism to reduce the effect of harmonic distortion. The article includes a local stability analysis for the proposed scheme as well as guidelines for control parameter tuning. Experimental results are provided to assess the performance of the proposed scheme under angular frequency variations and harmonic distortion on the reference signal.

A Robust Adaptive Identification of Sinusoidal Signal With Unknown Frequency

A robust algorithm in the form of a 3-D dynamic system is introduced to identify the frequency, the in-phase component, the orthogonal component, and the amplitude of a sinusoidal signal with unknown frequency. The condition for asymptotically convergent property of the dynamic system is analyzed sequentially by time scale change, variable transformation, slow integral manifold, averaging method, Lyapunov stability theorem, and stability theory of Mathieu equation. The robustness is embodied in two aspects: 1) the actual values of both frequency and amplitude slightly influence the convergent property and 2) two design parameters have independent effects on performance of both frequency identification and amplitude identification, respectively. Simulation results verify the validity.

Grid-Tied Inverter With AC Voltage Sensorless Synchronization and Soft Start

This paper presents a novel grid synchronization method with bumpless start that requires minimal computational load and can selectively track the positive sequence of the grid voltage in an unbalanced and distorted three-phase weak grid. Only 12 floating-point operations are required to obtain the in-phase and quadrature components that define a synchronous frame which tracks the positive sequence of the grid voltage. Contrary to a phase-locked loop (PLL), the presented scheme does not require to measure any ac voltages. Therefore, this sensorless method is particularly suited for weak-grid conditions, in which the voltage at the point of common coupling may contain significant noise and can experience larger deviations from the grid voltage (compared to a strong grid) due to the voltage drop in the weak grid impedance. The error in the estimated phase depends on the accuracy of the plant model. If the LCL filter parameters are known, then both the proposal and a PLL-based scheme result in the same steady-state error. Experimental results show the advantages of the proposal compared to a moving average filter PLL.

Ultra-Low Complex Blind I/Q-Imbalance Compensation

Direct-conversion transceivers are the predominating architecture in current mobile communication systems. Despite many advantages, this topology suffers from unavoidable mismatches in the analog part, which causes imbalance between the in-phase and quadrature (I/Q) component. In this paper, we present a novel fully digital, blind I/Q imbalance compensation algorithm that features extremely low computational complexity and high compensation performance for a wide range of input signal types. Different to many state-of-the-art compensation schemes, the approach is not based on a gradient descent optimization and does not require any global feedback. This simplifies the implementation at high data rates and reduces the configuration effort to a minimum. For comparison, we examine an existing method of moment-based estimator with similar properties, for which we also provide the detailed insights beyond available literature. For both algorithms, we provide a rigorous mathematical analysis, which is supported by simulations with a focus on various long-term evolution (LTE) signal types. In addition, hardware architectures, including field-programmable gate array (FPGA) verification, are presented for both algorithms.

Metal Discrimination in Metal Detector

In the article show the basic principles of metal detection, proposed methods for measuring the quantities by which the type of metal can be determined, and methods for improving the accuracy of metal detection and classification. A hardware implementation of a data processing and analysis unit for determining the type of metal has been developed. Digital data processing tools were used for the implementation, which allows to simplify the block design, minimize possible errors and noises during measurement, distorting the final result of the detection and classification of metals.In the modern world people has to deal with a large number of different metals. There is a problem of distinguishing one type of metal from all others. Such a function of metal detectors is called discrimination. Metal Detector Discrimination is a function that allows you to recognize marked objects by metal type and classify them. Modern high-precision metal detectors contain a large number of functional blocks, complex in setting up and use, sensitive to noise and errors during measurement and detecting metal. The task is to design a unit for discrimination of metals that would consist of a minimum number of functional units, required minimum number of settings and could give correct information about the presence of metal and type of metal and will be insensitive to disturbances caused by the noise and errors during measurement.Metal detectors operate on the principle of magnetic field generation and analysis of the feedback signal from a metal object and the environment. The transmitted magnetic field varies in time. The transmitter is made as coil with an electric current of a certain shape, passing through it and obtained from the generator block. The receiver is made as receiving coil connected to the amplification, filtering and processing unit of the received signal. Any metal has the properties of the resistivity and the properties of the inductance. Using information about the phase difference and amplitude between transmitted and received signals, we can determine type of the metal. To find the phase and amplitude of the received signal, the signal from the metal can be divided into two components: quadrature component has the same form of signal as the transmission signal, but is shifted in time relative to the transmitted signal (phase difference); in-phase component has the same form of signal as the signal transmitted, but, the amplitude of the received signal changes. Then using this two components find the phase and amplitude of the signal. To increase accuracy of the measurement using “ground balancing” principals, and ferrite calibration. As a result get the block for metal discrimination with simple design, minimum number of setting and good capabilities to minimize noise and errors during measurement.Ref. 12, fig. 8.

8-port homodyne detection of optical fields using IQ demodulation

A phase-sensitive detection scheme for optical fields is described, which allows for the simultaneous measurement of orthogonal field quadratures. The recent achievement of -radian cross-phase shifts between a single photon and a second light field has opened the door to quantum computing protocols which utilize photonic quantum bits. Optical phase measurements play an integral role in these schemes. The detection scheme presented here was designed to measure such transient phase shifts of a laser field as it interacts with another light field through a cloud of laser-cooled Rb atoms. In place of conventional spatial interferometry, which is very sensitive to mechanical instabilities, the scheme utilizes beat-note interferometry to improve on the robustness of the measurement. Beat-note interferometry serves to map a signal from a THz-frequency carrier onto a radio-frequency carrier. A variant of 8-port optical homodyne detection, the scheme then uses IQ demodulation, a well-established technique in communications engineering, to extract amplitude information for both the in-phase (I) and quadrature-phase (Q) components of the radio-frequency signal. This IQ data can then be used to extract any amplitude variation and/or phase shifts of the original THz-frequency optical field. The technique is illustrated here by simultaneously measuring the absorption and dispersion experienced by an optical beam as it passes through a cloud of laser-cooled atoms, which have been prepared in a state of electromagnetically-induced transparency. A thorough characterization of the measurement is presented, which identifies the dominant noise sources and illustrates the utility of IQ demodulation in eliminating noise. This scheme has been used to measure rad phase shifts on nanosecond time scales.

Improved phase‐locked loop‐based control for grid‐integrated PV system

This work presents an improved phase-locked loop (IPLL)-based control for grid-integrated photovoltaic (PV) system (GIPVS). It is used to extract amplitude, frequency, and phase angle of distorted load currents to control PV-grid-interfaced voltage source converter (VSC). The VSC controls active and reactive powers at unbalances and distortions in the grid voltages. The control algorithm of VSC includes power feed-forward term, DC-link voltage, and grid voltages. The feed-forward term improves the dynamic performance of a GIPVS and enhances the utilisation of VSC. Three-phase IPLLs extract the in-phase components of three-phase load currents at utility frequency. Further, these in-phase components of load currents are used for estimation of reference-grid currents. The proposed IPLL-based control algorithm offers good dynamic response even under unbalanced load condition. The efficient working of IPLL-based control algorithm is realised by extracting maximum power from PV-grid system and through its power-quality improvement. The perturb and observe (P & O) control algorithm is used for optimum utilisation of a PV array. A developed prototype of PV-grid system is used to implement an IPLL-based control algorithm under different operating conditions.

Comprehensive Performance Evaluation of Computationally Efficient Discrete Fourier Transforms for Frequency Estimation

In this paper, the design of frequency-locked loop (FLL) is proposed based on computationally efficient discrete Fourier transform (DFT) structures. In recent years, the DFT structures are evolved as sliding DFT (SDFT), modulated SDFT, hopping DFT (HDFT), modulated HDFT, and sliding-windowed infinite Fourier transform. Considering their tuned filter characteristics, an attempt has been made to obtain a solution for the instantaneous frequency estimation problem of the input signal under varying center frequency condition. In each DFT structure, the $k$ th bin in-phase and quadrature components are separated for instantaneous signal extraction. The feedback loop is designed around these DFT structures, and it was observed that the frequency responses exhibit flat magnitude and phase interestingly when compared with the open-loop structures. Hence, an adaptive sampling frequency adjustment scheme is proposed for these structures as FLL to estimate the instantaneous frequency of the input signal for the wide variation in center frequency. These FLLs with different DFT structures are tested for dynamic performance and wide operating range. The proposed FLLs are implemented in field-programmable gate array (FPGA), and the experimental investigations have been carried out for frequency estimation. Further experimental investigations on these FLLs as a system on chip were carried out with area and power analysis.

Merged Cloud and Precipitation Dataset from the HIAPER GV for the Cloud System Evolution in the Trades (CSET) Campaign

AbstractThe Cloud System Evolution in the Trades (CSET) aircraft campaign was conducted in the summer of 2015 in the northeast Pacific to observe the transition from stratocumulus to cumulus cloud regime. Fourteen transects were made between Sacramento, California, and Kona, Hawaii, using the NCAR’s High-Performance Instrumented Airborne Platform for Environmental Research (HIAPER) Gulfstream V (GV) aircraft. The HIAPER W-band Doppler cloud radar (HCR) and the high-spectral-resolution lidar (HSRL), in their first deployment together on board the GV, provided crucial cloud and precipitation observations. The HCR recorded the raw in-phase (I) and quadrature (Q) components of the digitized signal, from which the Doppler spectra and its first three moments were calculated. HCR/HSRL data were merged to develop a hydrometeor mask on a uniform georeferenced grid of 2-Hz temporal and 20-m vertical resolutions. The hydrometeors are classified as cloud or precipitation using a simple fuzzy logic technique based on the HCR mean Doppler velocity, HSRL backscatter, and the ratio of HCR reflectivity to HSRL backscatter. This is primarily applied during zenith-pointing conditions under which the lidar can detect the cloud base and the radar is more sensitive to clouds. The microphysical properties of below-cloud drizzle and optically thin clouds were retrieved using the HCR reflectivity, HSRL backscatter, and the HCR Doppler spectrum width after it is corrected for the aircraft speed. These indicate that as the boundary layers deepen and cloud-top heights increase toward the equator, both the cloud and rain fractions decrease.

Extraction of Carrier Phase Delay for Nonlinear Errors Compensation of PGC Demodulation in an SPM Interferometer

Traditional phase generated carrier (PGC) schemes require that the carrier phase delay be kept zero and the phase modulation depth be maintained at a certain value; otherwise, serious nonlinear errors will be introduced into the phase demodulation of a sinusoidal phase modulation interferometer. Proposed herein is a robust carrier phase delay extraction method for nonlinear errors compensation of PGC demodulation that mitigates the effect of the interference phase shift. The carrier phase delay is directly extracted by adopting the first-, second-, and fourth-order in-phase and quadrature harmonic components generated by quadrature multi-harmonics frequency down conversion. Further, with the extracted phase delay, real-time compensations for the phase delay and phase demodulation depth are realized simultaneously in PGC demodulation. Theoretical analysis and derivation of the proposed method are given in detail. Simulation and displacement measurement experiments with different phase delays and phase modulation depths are performed to verify the effectiveness of the proposed method. The experimental results demonstrate that the proposed method is able to precisely extract the phase delay and efficiently eliminate the effects of the phase delay and modulation depth instability.

Enhanced Multiuser Superposition Transmission Through Structured Modulation

The fifth-generation (5G) air interface, namely, dynamic multiple access (MA) based on multiuser superposition transmission (MUST) and orthogonal MA (OMA), may require a complicated scheduling and heavy signaling overhead. To address these challenges, we propose a unified MA scheme for future cellular networks, which we refer to as structured MUST (S-MUST). In S-MUST, we apply complex power allocation coefficients (CPACs) over multiuser legacy constellations to generate a composite constellation. In particular, the in-phase ( $I$ ) and quadrature ( $Q$ ) components of the legacy constellation of each user are separately multiplied by those of the CPACs. As such, the CPACs offer an extra degree of freedom for multiplexing users and guarantee fairness in symmetric broadcast channels. This new paradigm of superposition coding allows us to design $IQ$ separation at the user side, which significantly reduces the decoding complexity without degrading performance. Hence, it supports low-complexity frequency-selective scheduling that does not entail dynamical switching between MUST and OMA. We further propose to quantize the CPACs into complex numbers where $I$ and $Q$ components of each quantized coefficient are primes, facilitating parallel interference cancellation at each user via modulo operations; last but not least, we generalize the design of S-MUST to exploit the capabilities of multiantenna base stations. The proposed S-MUST exhibits an improved user fairness with respect to conventional MUST (134% spectral efficiency enhancement) and a lower system complexity compared with dynamically alternating MUST and OMA.

Probability Distribution of Intercore Crosstalk in Weakly Coupled MCFs With Multiple Interferers

The statistical behavior of the intercore crosstalk (ICXT) power in weakly coupled multicore fibers (MCFs) with multiple interfering cores is experimentally assessed. The histograms with multiple interfering cores are compared with the probability density function (pdf) of the quadratic form corresponding to the ICXT power considering different correlation coefficients between the in-phase and quadrature Gaussian ICXT field components of the orthogonal polarizations. A very good fitting between experimental histograms and the numerical pdf of the quadratic form occurs when the ICXT field components are modeled as uncorrelated random processes. These results demonstrate that the ICXT power can, with a very low error, be described by a chi-square distribution with 4 degrees of freedom not only with a single interfering core but also with multiple interfering cores. This means that the ICXT contributions induced by different cores of the MCF are uncorrelated.

Hand-Gesture Recognition Using Two-Antenna Doppler Radar With Deep Convolutional Neural Networks

Low-cost consumer radar integrated circuits combined with recent advances in machine learning have opened up a range of new possibilities in smart sensing. In this paper, we use a miniature radar sensor to capture Doppler signatures of 14 different hand gestures and train a deep convolutional neural network (DCNN) to classify these captured gestures. We utilize two receiving antennas of a continuous-wave Doppler radar capable of producing the in-phase and quadrature components of the beat signals. We map these two beat signals into three input channels of a DCNN as two spectrograms and an angle of arrival matrix. The classification results of the proposed architecture show a gesture classification accuracy exceeding 95% and a very low confusion between different gestures. This is almost 10% improvement over the single-channel Doppler methods reported in the literature.

Data-Driven Deep Learning for Automatic Modulation Recognition in Cognitive Radios

Automatic modulation recognition (AMR) is an essential and challenging topic in the development of the cognitive radio (CR), and it is a cornerstone of CR adaptive modulation and demodulation capabilities to sense and learn environments and make corresponding adjustments. AMR is essentially a classification problem, and deep learning achieves outstanding performances in various classification tasks. So, this paper proposes a deep learning-based method, combined with two convolutional neural networks (CNNs) trained on different datasets, to achieve higher accuracy AMR. A CNN is trained on samples composed of in-phase and quadrature component signals, otherwise known as in-phase and quadrature samples, to distinguish modulation modes, that are relatively easy to identify. We adopt dropout instead of pooling operation to achieve higher recognition accuracy. A CNN based on constellation diagrams is also designed to recognize modulation modes that are difficult to distinguish in the former CNN, such as 16 quadratic-amplitude modulation (QAM) and 64 QAM, demonstrating the ability to classify QAM signals even in scenarios with a low signal-to-noise ratio.

A Low-Complexity I/Q Imbalance Calibration Method for Quadrature Modulator

This brief presents a low-complexity I/Q (in-phase and quadrature components) imbalance calibration method for the transmitter using quadrature modulation. Impairments in analog quadrature modulator have a deleterious effect on the signal fidelity. Among the critical impairments, I/Q imbalance (gain and phase mismatches) deteriorates the residual sideband performance of the analog quadrature modulator degrading the error vector magnitude. Based on the theoretical mismatch analysis of the quadrature modulator, we propose a low-complexity I/Q imbalance extraction algorithm. After the parameter extraction, the transmitter is calibrated by imposing the counter imbalanced mismatch of the transmitter through the digital baseband. In comparison with existing I/Q imbalance calibration methods, the novelty of the proposed method lies in that: 1) only three spectrum measurements of the device-under-test are needed for extraction and calibration of gain and phase mismatches; 2) due to the blind nature of the calibration algorithm, the proposed approach can be readily applicable to an existing I/Q transmitter; 3) no extra hardware that degrades the calibration accuracy is required; and 4) due to the noniterative nature, the proposed method is faster and computationally more efficient than previously published methods.

Multipath Cluster Fading Statistics and Modeling in Millimeter-Wave Radio Channels

The second-order statistics of indoor directional channels are investigated using millimeter-wave (mmWave) band (30.4–37.1 GHz) ultrawideband (UWB) channel measurements. Considering two main mmWave system assumptions (high bandwidth and high beamforming gain), this paper aims to investigate the validity of the Rayleigh–Rice fading models for the cluster fading envelope. The results from the mmWave band study are compared to an already well-studied lower frequency FCC band (3.4–10.1 GHz). During the measurements, only selective objects (emulated multipath clusters in the propagation channel) are illuminated in a small lecture room. The experiments show that for both UWB channels, the complex received (Rx) signal is a circularly symmetric non-Gaussian random variable with highly correlated inphase (I) and quadrature (Q) components. These properties demonstrate that the intracluster multipath components (MPCs) structure is sparse. Consequently, modeling the cluster fading envelope with Rayleigh–Rice distribution is not realistic. Therefore, the sum-of-cisoids principle is used for intracluster multipath modeling which inherently considers a correlation between I and Q components. It has been established that a reasonably good approximation of the cluster fading envelope can be obtained with $N=3-6$ equal amplitude cisoids. However, we remark that Rayleigh–Rice models may become realistic cluster fading envelopes for narrowband mmWave systems.

QAM classification methods by SVM machine learning for improved optical interconnection

High-order quadrature amplitude modulation (QAM) formats are very effective for increasing the transmission capacity due to the highly increased spectral efficiency. However, the signal-to-noise-ratio (SNR) hungry and dense constellation of QAM make it very sensitive to nonlinear distortion. The nonlinear decision boundary adaptively generated by machine learning method of support vector machine (SVM) can be effectively used for the classification of the symbols. The different classification methods have different performance in terms of classification complexity. We experimentally investigated five SVM multi-classification methods for machine learning assisted adaptive nonlinear mitigation, including the one versus rest (OvR), the symbol encoding (SE), the binary encoding (BE), the constellation rows and columns (RC), and the in-phase and quadrature components (IQC). The comprehensive results with comparisons are demonstrated, indicating significant nonlinear mitigation with BER reductions. The SVM multi-classifier based on the in-phase and quadrature components is relatively optimal, considering the calculation and storage.

Relative Vibration of Suspended Particles With Respect to Microchannel Resonators and Its Effect on the Mass Measurement

In this work, the three-dimensional fluid–solid interaction vibration of particle in the oscillating resonator and its effect on the dynamic characteristics are analyzed and discussed. It demonstrates that the displacement of a particle is composed of two components, one is in phase with the acceleration of resonator and the other is out of phase. The former is responsible for the added mass effect and the latter results in a small damping. A modified measurement principle for detecting the buoyant mass is then presented by considering the in-phase component. The three-dimensional (3D) fluid–solid interaction problem involving the particle, fluid, and resonator is numerically solved, and the effects of density ratio, inverse Stokes number, and the ratio of channel height to particle diameter are studied. Based on the numerical results, a function characterizing the in-phase component is identified through a fitting procedure. According to the modified measurement principle and the analytical expression for the in-phase component, a calibration method is developed for measuring buoyant mass. Using this calibration method, the systematic measurement error induced by the vibration of particles can be effectively reduced.

Near-surface resistivity structure near avcilar landslide in İstanbul, Turkey by 2D inversion of VLF data

In this study, VLF data collection and 2D modeling is carried out in order to gather information about the Avcılar landslide and to detect possible faults, may be residing in the study area, located at the southwestern slopes of the Küçükçekmece Lake in Avcılar, İstanbul, Turkey.Data collection is realized on 12 traverses in TE mode between 2015 and 2017 and mostly consists of in-phase and quadrature components of the tipper data. On a single profile, apparent resistivity and phase data is also collected. The study area is placed near an urban area and relatively higher noise levels are observed at several profiles. However, data in adjacent and overlapping profiles shows consistency and repeatability. Thus, instead of omitting these profiles, the data with higher noise is treated with Empirical Mode Decomposition (EMD) filtering.Karous-Hjelt filtered in-phase component data is calculated for basic interpretation, and 2D inversions are performed in order to obtain more information about the shallow geo-electrical structure. The approximate resistivities of the near-surface geological formations are differentiated from the recovered models. Accordingly, 2D inversion results suggest resistivity values significantly different from the values previously obtained using 1D methods. Inversion results also revealed the structure and the base of the Avcılar landslide successfully. In the northern part of the study area, the top of the Gürpınar formation, forming the base of the Avcılar landslide, is detected with varying depths up to 25 m. In the resistivity images any structure that may represent a fault is not detected.