Quadrature Components Research Articles

Low Limit of Detection Gas Density Sensing With a Digitally PI-Controlled Microcantilever

This work describes a new platform for sensing mass or rheological properties of gases with unprecedented responsivity and limits of detection. The system consists of a microcantilever working in a phase-locked loop (PLL) with an imposed phase between its excitation and deflection signals. The optically detected cantilever deflection is demodulated against digitally synthetized reference signals, and the quadrature component ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${Q}$ </tex-math></inline-formula> -signal) is used as the error parameter in a PI controller, which continuously tracks the oscillation frequency. The direct digital synthesis of the reference and actuation signals allows low-noise and fast-transient responses of the sensor for real-time detection of minute changes of any environmental parameter. A general analytical model is derived, used to understand the dynamical response of the platform, and validated against experiments using different gases and pressures. In particular, the responsivity of the sensor to density variations of the fluids and the stability of its frequency response are studied and measured. It is shown that the responsivity and the achieved limits of detection depend on the chosen phase imposed in the loop. A limit of detection for density variations of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$3.5\times 10^{-{4}}$ </tex-math></inline-formula> kg/ <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\text{m}^{{3}}$ </tex-math></inline-formula> in air is measured, in agreement with the theoretical predictions, and one to two orders of magnitude lower than any reported value achieved with the same type of physical uncoated resonant sensors.

Experimental Demonstration of Linear Inter-Channel Interference Estimation Based on Neural Networks

In this paper, an algorithm for the estimation of the linear inter-channel crosstalk in a dense-WDM polarization-multiplexed 16-QAM transmission scenario is proposed and demonstrated. The algorithm is based on the use of a feed-forward neural network (FFNN) inside the coherent digital receiver. Two types of FFNNs were considered, the first based on a regression algorithm and the second based on a classification algorithm. Both FFNN algorithms are applied to features extracted from the histograms of the in-phase and quadrature components of the equalized digital samples. After a simulative investigation, the performance of the channel spacing estimation algorithms was experimentally validated in a 3 × 52 Gbaud 16-QAM WDM system scenario.

Multi-Dimensional Joint Constellation and Precoding Design for MIMO Systems

Digital modulation and precoding are two key modules for increasing the data rate and reducing the symbol error rate in multiple-input multiple-output (MIMO) systems. Traditionally, these two modules are designed separately, and regular constellations like <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${M}$ </tex-math></inline-formula> -ary phase-shift keying ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${M}$ </tex-math></inline-formula> -PSK) and quadrature amplitude modulation (QAM) are used for modulation. However, significant gains can be achieved if modulation and precoding are designed jointly for all antennas. Motivated by this, a multi-dimensional joint constellation and precoding design is proposed to optimize the in-phase and quadrature components for all sub-channels of a MIMO channel at once. The objective is to maximize the minimum distance among the symbols. Extensive simulation results indicate that this approach can significantly improve the performance of the state-of-the-art solutions by reducing the symbol error rate and bit error rate.

Sliding mode approach for control and observation of a three phase AC-DC pulse-width modulation rectifier

Introduction. For AC-DC conversion systems, the electrical systems typically use thyristor or diode bridge rectifiers, which have relatively poor performance. Nowadays, three-phase pulse-width modulation rectifiers are widely applied in various applications for their well-known intrinsic benefits, such as adjustable DC link voltage, unity power factor, bidirectional power flow and very low total harmonic distortion. Purpose. The objective of this work is to achieve better stability and dynamic performance using sliding mode strategy for control and observation. Methods. For that purpose, first a sliding mode controller is introduced on the DC-link side to ensure a fast and accurate response of the output load voltage. Then, the sliding mode approach is employed to control the quadrature and direct components of power to maintain the input power factor at unity. Finally, this approach is used to design two observers for grid voltage estimation and online variation of load resistance. To overcome the problem associated with the use of the classical low-pass filter, an adaptive compensation algorithm is used to compensate the attenuation of the amplitude and phase delay of the observed grid voltages. This algorithm is based on the use of the two low-pass filters in cascade and ensures the minimization of chattering. Results. Comparative studies have been carried out between sliding mode control method for controlling the three-phase AC-DC pulse-width modulation rectifier and other conventional techniques. The validation by simulation and the tests carried out gave very satisfactory results and proved the effectiveness and feasibility of the sliding mode for both control and observation of three phase pulse-width modulation rectifier.

Effect of three-beam interference on phase-generated carrier demodulation of a fiber-optic interferometric sensor.

Homodyne demodulation using a phase-generated carrier (PGC) has been applied in fiber-optic interferometric sensors to overcome the signal fading and distortion due to the drift of the operating point. An assumption needed for the PGC method to be valid is that the sensor output is a sinusoidal function of the phase delay between the arms of the interferometer, which is readily achieved by a two-beam interferometer. In this work, we theoretically and experimentally study the effect of three-beam interference, whose output deviates from a sinusoidal function of the phase delay, on the performance of the PGC scheme. The results show that the deviation could lead to additional undesirable terms in the in-phase and quadrature components in PGC implementation, which may result in significant signal fading with the drift of the operating point. The theoretical analysis leads to two strategies for eliminating these undesirable terms so that the PGC scheme is valid for three-beam interference. The analysis and the strategies were validated experimentally using a fiber-coil Fabry-Perot sensor with two fiber Bragg grating mirrors, each having a reflectivity of 26%.

Complex Convolutional Neural Network for Signal Representation and Its Application to Radar Emitter Recognition

Signal representation and identification in wireless communication has recently aroused substantial concern due to the remarkable evolution of data-driven techniques. Consider there are vital complementary information between inphase (I) and quadrature (Q) components, and I and Q have respective emphasis on the signal. Therefore compact signal representation requires their joint interaction. However, it is a pity that most methods ignore their implicit relevance. This letter considers the codify of tacit knowledge between I/Q pairs. First, a complex-valued convolutional unit is proposed to mine individual information and to explore their complementation. Second, a complex convolutional neural network (CCNN) is built to achieve radar emitter recognition end-to-end. Experimental results demonstrate CCNN’s superiority on measured radar signals in comparison to other methods from literature.

A Unification of LoS, Non-LoS, and Quasi-LoS Signal Propagation in Wireless Channels

The modeling of wireless communication channels is often broken down into two distinct states, defined according to the optical viewpoints of the transmitter (TX) and receiver (RX) antennas, namely, line-of-sight (LoS) and non-LoS (NLoS). Movement of the TX, RX, both and/or objects in the surrounding environment means that channel conditions may transition between LoS and NLoS leading to a third state of signal propagation, namely, quasi-LoS (QLoS). Unfortunately, this state is largely ignored in the analysis of signal propagation in wireless channels. We, therefore, propose a new statistical framework that unifies signal propagation for LoS, NLoS, and QLoS channel conditions, leading to the creation of the three-state model (TSM). The TSM has a strong physical motivation, whereby the signal propagation mechanisms underlying each state are considered to be similar to those responsible for Rician fading. However, in the TSM, the dominant signal component, if present, can be subject to shadowing. To support the use of the TSM, we develop novel formulations for the probability density functions of the in-phase and quadrature components of the complex received signal, the received signal envelope, and the received signal phase. In addition, we derive an expression for the complex autocorrelation function of the TSM, which will be of particular importance in understanding and simulating its time correlation properties. Finally, we show that the TSM provides a good fit to field measurements obtained for two different body-centric wireless channels operating at 2.45 GHz, which are known to be subject to the phenomena underlying the TSM.

Compatibility Assessment of Multistatic/Polarimetric Clutter Data With the SIRP Model

This article deals with the statistical inference of simultaneously recorded co- and cross-polarized bistatic coherent sea-clutter returns at <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$S$</tex-math></inline-formula> -band. This study is conducted employing appropriate statistical learning tools, involving the complex envelope of data, to assess the compliance of the available measurements with the spherically invariant random process (SIRP) representation, as well as to analyze possible texture correlations among the diverse polarimetric channels. Moreover, the spatial heterogeneity of the sea-clutter data is studied. The results highlight that the SIRP model is a good candidate for the representation of bistatic coherent clutter and usually the coherence time of the SIRP texture at the bistatic nodes is longer than that in the monostatic sensing. Notably, at bistatic angles in order of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$60^\circ$</tex-math></inline-formula> , the quadrature components of the cross-polarized bistatic measurements substantially exhibit a Gaussian behavior. These achievements further shed light on the bistatic sea-clutter diversity from the geometric and polarimetric point of view.

Finding Explanations in AI Fusion of Electro-Optical/Passive Radio-Frequency Data.

In the Information Age, the widespread usage of blackbox algorithms makes it difficult to understand how data is used. The practice of sensor fusion to achieve results is widespread, as there are many tools to further improve the robustness and performance of a model. In this study, we demonstrate the utilization of a Long Short-Term Memory (LSTM-CCA) model for the fusion of Passive RF (P-RF) and Electro-Optical (EO) data in order to gain insights into how P-RF data are utilized. The P-RF data are constructed from the in-phase and quadrature component (I/Q) data processed via histograms, and are combined with enhanced EO data via dense optical flow (DOF). The preprocessed data are then used as training data with an LSTM-CCA model in order to achieve object detection and tracking. In order to determine the impact of the different data inputs, a greedy algorithm (explainX.ai) is implemented to determine the weight and impact of the canonical variates provided to the fusion model on a scenario-by-scenario basis. This research introduces an explainable LSTM-CCA framework for P-RF and EO sensor fusion, providing novel insights into the sensor fusion process that can assist in the detection and differentiation of targets and help decision-makers to determine the weights for each input.

Coordinate Interleaved Faster-Than-Nyquist Signaling

Faster-than-Nyquist (FTN) signaling is an attractive transmission technique which accelerates data symbols beyond the Nyquist rate to improve the spectral efficiency; however, at the expense of higher computational complexity to remove the introduced intersymbol interference (ISI). In this work, we introduce a novel FTN signaling transmission technique, named coordinate interleaved FTN (CI-FTN) signaling that exploits the ISI at the transmitter to generate constructive interference for every pair of the counter-clockwise rotated binary phase shift keying (BPSK) data symbols. In particular, the proposed CI-FTN signaling interleaves the in-phase (I) and the quadrature (Q) components of the counter-clockwise rotated BPSK symbols to guarantee that every pair of consecutive symbols has the same sign, and hence, has constructive ISI. At the receiver, we propose a low-complexity detector that makes use of the constructive ISI introduced at the transmitter. Simulation results show the merits of the CI-FTN signaling and the proposed low-complexity detector compared to conventional Nyquist and FTN signaling.

Self-reliant solar PV based microgrid with seamless transition capabilities at weak grid conditions

• The extended proportional complex filter (EPCF) control allows a fast estimation of the quadrature and in-phase fundamental load current components with reduced harmonics within the prescribed limit. • The EPCF-based control has extracted the fundamental component of load current with high rate of convergence and better system response. The variations on load, utility, and solar array radiation are well established in simulation and test results. The PQ is enhanced at unbalancing of load, change in solar insolation and grid adverse conditions of voltages unbalances. The performance of the system is found satisfactory and its response is enhanced at adverse grid conditions. Experimental results have demonstrated that the THD are as recommended by the IEEE-519 standard even during weak grid conditions. • A comparative analysis is included, which validates the superior filtering capability and improved power quality during weak grid conditions. In addition a tabular comparative analysis is included to support its effectiveness while addressing abnormalities of the grid. • The EPCF-PLL grid synchronization and phase angle estimator scheme has provides fast mode transition, frequency tracking and uninterrupted supply to the load during non availability of the grid. This has given precise phase angle estimation. Conventional PLL controllers are non-adaptive towards large frequency. EPCF-PLL has provided effective frequency adaptability. This makes the synchronization process immune from frequency variation and voltage unbalance. • The proportional resonant controller with harmonic compensation (PRHC) controller provides satisfactory performance under all the intermittent conditions overcoming the tradeoff between improved steady-state and transient performance. This paper presents a solar photovoltaic (PV) based energy conversion system with seamless transfer to the grid. To provide satisfactory performance in grid connected mode, a control based on extended proportional complex filter (EPCF) is used. The EPCF is used to estimate the fundamental current component (LCFC) of local loads At the linkage point (LP), the power quality (maintaining IEEE-519 standard) is improved using this control. The EPCF maintains balanced grid currents whether PV array generation is available or not. It provides effective mitigation of harmonics and monitors the flow of active power, which improves the grid current quality.This control provides versatile actions such as extraction of LCFC, harmonics elimination, DC offset removal, robust performance during voltages unbalance etc. The same control technique (EPCF) along with phase locked loop is used for smooth synchronization; it reduces the use of another algorithm, which improves the dynamic response of the system. This control estimates exact phase and frequency variation for the seamless mode switching. It provides frequency adaptation during mode shifting. The comparative results validate that the control based on EPCF has a faster detection of grid in comparison with existing controls. During the grid-outage, the proportional resonant (PR) controller with harmonics compensation (HC) based control algorithm enhances performance of the microgrid. This provides successful solution for harmonics compensation and minimizing steady state errors. Simulated and experimental results, in various scenarios, have verified the effectiveness of the controllers and demonstrate the favourable solution in controlling the unfavorable grid conditions.

Experimental demonstration on quantum coherence evolution of two-mode squeezed state

As one of the most remarkable features of quantum mechanics, quantum coherence is regarded as an important quantum resource in the quantum information processing. The one-mode squeezed state and the two-mode squeezed state (Einstein-Podolsky-Rosen (EPR) entangled states) as the most representative examples of nonclassical states both have quantum coherence. The squeezing property of the squeezed state is described by the variance of quadrature components, and the positive partial transposition (PPT) criterion is used to describe the entanglement of the EPR entangled states. The research of the quantum coherence of Gaussian states is also a bridge between the properties of squeezing and entanglement. It has been shown that the quantum coherence with infinite-dimensional systems can be quantified by relative entropy. One of the widely used effective methods to obtain the value of quantum coherence experimentally is the quantum tomography. The covariance matrices of the quantum states are reconstructed via balanced homodyne detection and then taken into quantum coherence expression to calculate the corresponding value. The main factors affecting quantum coherence are the classical and uncorrelated noise in the actual experimental generation processing and the decoherence effect caused by the coupling between quantum resources and the surrounding environment. And the quantum coherence evolution in the generation and transmission process of the quantum resources is essential for the practical applications. Therefore, we analyze in detail the influences of the impurity of quantum resource on squeezing, entanglement and quantum coherence. The evolutions of quantum coherence of these Gaussian states in the lossy channels are demonstrated experimentally. The quantum coherence is shown to be robust against the loss in the lossy channels, which is similar to the case of squeezing and entanglement. The quantum coherences of the squeezed states and the EPR entangled states are robust against the thermal photons in the actual experimental generation processing, although the squeezing and entanglement of Gaussian states disappear at a certain number of thermal photons. Our research results provide a reference for the practical applications of quantum coherence of the squeezed state and entangled states in the lossy environment.

Explicit Joint Resolution Limit for Range and Direction of Arrival Estimation in MIMO Radar

Resolution capability is an important metric for radar parameter estimation. However, the resolution limit for multi-parameters estimation has not been adequately studied. In this paper, we exploit results from Shannon's information theory to derive a joint resolution limit (JRL) for range and direction of arrival (DOA) estimation in MIMO radar. Based on the general model, the closed-form expression of scattering information is obtained for two targets with complex Gaussian scattering properties. A critical state is considered where the quadrature component of the scattering information is 1 b and corresponding intervals of range and DOA are defined as the JRL. Under the assumption of closely-spaced targets, the approximated explicit JRL is derived by a second-order Taylor series, which indicates that the JRL is inversely proportional to the number of array elements, the square root of the signal to the noise ratio, and the signal bandwidth to the carrier frequency ratio. Also, closed-form approximations for range resolution limit and DOA resolution limit are obtained as special cases. It is indicated that these resolution limits are general and not based on any specific resolution method. The accuracy and the validity of the proposed resolution limits are verified by numerical simulations.

Geophysical mapping of freshwater lens in Big Pine Key, Florida: Electromagnetic Induction Calibration and Application

AbstractGeoelectric and electromagnetic (EM) methods are rapid and non‐invasive geophysical techniques for estimating groundwater properties and characterizing the spatial and temporal variability of subsurface formations. However, to quantitatively interpret the EM data, the systematic error due to calibration problems and random error must be considered. We conducted coincident EM and electrical resistivity tomography (ERT) surveys in January and December 2018 on Big Pine Key, FL. In this study, we used vertical electrical sounding (VES) data extracted from a 220 m long ERT profile to calibrate the EM data. The inverted VES data were used as input in the EM forward model to estimate the quadrature component response. Then, the observed offset between the calculated and observed quadrature data was corrected using a multiple linear regression model. Finally, the calibrated quadrature data were converted to apparent electrical conductivity and inverted as a 2‐layer model using both the full solution and the low induction approximation. These models were used to assess the temporal and spatial variations of conductivity on a 2.2 km long E–W trending profile across the island. The calibrated apparent electrical conductivity on the profile decreased between January and December 2018, with the largest decreases in the lower elevation regions of the profile. In addition, the 2‐layer models inverted using the full solution and low induction approximation showed the depth of the freshwater interface increased by December 2018. These observations suggest the recovery of the freshwater lens due to precipitation. Based on this study, we concluded the VES at pilot locations can be used for calibration purposes and verification of the accuracy of EM measurements.

Pre-calibration and compensation of quadrature components in continuous-variable quantum key distribution

Pre-calibration and compensation of quadrature components in continuous-variable quantum key distribution

UNIFIED POWER FLOW CONTROLLER CONTROL STRATEGIES for POWER FLOW

In order to address power flow control issues, this study introduces the use of Unified Power Flow Controller (UPFC) models. These models are based on regulating the variables influencing the transmission line’s power flow, and they are capable of controlling the bus voltage, the line’s actual and reactive power, all at once and independently. The idea behind the UPFC technique proposed in this paper is to provide the unique functional capability of independently controlling both the real and reactive power flow in the line. The in-phase component of the series injected voltage dominates the reactive power while the quadrature component affects the real power. A conventional controlling steady-state analysis and dynamic stability analysis of the power system is developed based on the UPFC model. UPFC provides real-time controlling of all or any combination of the power system parameters which determine the transmittable power. UPFC can force and maintain strategically chosen values of the active power and the reactive power at a given point of the line by PI control.

A Low-Power Single-Path Bio-Impedance Measurement System Using an Analog-to-Digital Converter for I/Q Demodulation.

In this paper, a low power single-path bio-impedance (Bio-Z) measurement system for early detection of acute myocardial ischemia is presented. The fully integrated system consists of a current source, an amplifier, and an analog-to-digital converter (ADC). The system utilizes the in-phase and quadrature (I/Q) components to obtain the real and imaginary parts of the tissue impedance. To achieve this goal, the ADC has been used to separate the I/Q components in addition to digitizing the samples. This can lead to power and silicon area reduction. The proposed circuit exploits the benefits of capacitively-coupled instrumentation amplifier, including inherent DC cancellation, low power, low noise, and high linearity and is implemented in 0.18 µm CMOS technology with a 1 V power supply. This system is designed and tested using a pseudo-sine 2 µAP-P current with a frequency of 1 kHz. The system can measure an input impedance that varies over a range from 0.03-7.5 kΩ with a resolution of 0.766 Ωrms while consuming 2 µW power from the supply. The operation of the system is also shown in the recording of impedance variation with respiration and heartbeat.

Low-complexity soft-output signal detector based on AI-SSOR preconditioned conjugate gradient method over massive MIMO correlated channel

Massive multiple-input multiple-output (MIMO) techniques with a large number of antenna elements at base station (BS) have been proved as an alternative to provide potential opportunity to increase the spectrum and energy efficiency. However, in the system, there generally exists a spatial correlation effect due to insufficient antenna elements spacing and/or the lack of rich scattering at BS. The minimum mean square error (MMSE) method performs signal detection at the expense of large-scale matrix inversion operation. Thus, the conjugate gradient (CG) method has received a lot of attentions to realize the MMSE detection efficiently. Unfortunately, this efficiency can be compromised due to the ill-conditioned equalization matrix of MMSE method over the correlated channel environments. Moreover, the hard output signal detection exhibits a sharply degradation in performance for higher-order quadrature amplitude modulation (QAM). Therefore, the modern communication systems use the soft-output information, i.e., log-likelihood ratio (LLR) along with the forward error-correcting code (FEC) to achieve satisfactory performance. The LLR computation along with a higher-order QAM remains challenging due to the exhaustive search of symbol in the modulation constellation. In this paper, a low-complexity soft-output signal detector based on approximate inverse symmetric successive over-relaxation preconditioned conjugate gradient (AI-SSOR-CG-SOD) method is proposed to realize MMSE method detection for uplink multiuser massive MIMO correlated channel. In the proposed method, a new preconditioner, an AI-SSOR, which is based on the Neumann series approximation of the inverse of the conventional SSOR preconditioner is firstly developed to handle ill-conditioned matrix, and then incorporated with CG method to improve the convergence rate and performance. According to the characteristic of the Gray-coding that adjacent symbols in the constellation set have only one different bit, the constellation set is divided multiple times based on the bits of the inphase and the quadrature components of the symbol, which reduces the complexity of the LLR computation of the transmitted bits by avoiding the exhaustive search process. Simulation results show that the AI-SSOR preconditioner is robust against spatial correlation effect, and the proposed detector converges at 3 iterations. Simulation results also show that the proposed detector achieves a better trade-off between the complexity and the performance compared to other existing detectors.

Broadband coherent multidimensional variational measurement

Standard Quantum Limit (SQL) of a classical mechanical force detection results from quantum back action perturbing evolution of a mechanical system. In this paper we show that usage of a multidimensional optical transducer may enable a broadband quantum back action evading measurement. We study a corresponding technique for measurement of a resonant signal force acting on a linear mechanical oscillator coupled to an optical system with three optical modes with separation nearly equal to the mechanical frequency. The measurement is performed by optical pumping of the central optical mode and measuring the light escaping the two other modes. By detecting optimal quadrature components of the optical modes and post-processing the measurement results we are able to exclude the back action in a broad frequency band and characterize the force with sensitivity better than SQL. We discuss how proposed scheme relates to multidimensional system containing quantum-mechanics-free subsystems (QMFS) which can evade the SQL using idea of so called "negative mass".

Methods and Algorithms of Subsurface Holographic Sounding

In our experiments, we develop and test portable multi-element receiver antenna arrays, electrically scanned in order to immediately obtain a recognizable image of subsurface objects. Two quadrature components of the radar return signal are processed with a Kirchhoff backward migration algorithm. Physical theory is used to assess the quality of the holographic image, and the synthetic aperture approach is developed and tested. The parabolic wave equation and Gaussian beam technique are used in order to take into account refraction effects and to suppress specular reflection from the air-ground interface. Laboratory and field tests confirmed the predicted device parameters.