Dynamic Range Of System Research Articles

Real-time and calibration-free generalized terahertz time-domain spectroscopic ellipsometry

Spectroscopic ellipsometry is a high-precision and powerful optical characterization technique, which can be categorized into two fundamental types of standard and generalized ellipsometry. The latter can obtain the complete Jones matrix to investigate various anisotropic samples. However, terahertz generalized ellipsometry has traditionally relied on frequency-domain instrumentation, which is limited in bandwidth, complicated in polarization manipulation, and slow in operation. In this study, we propose a highly accurate and efficient terahertz time-domain generalized ellipsometer based on a polarization beam coupler-splitter configuration. It measures four independent complex spectra in real-time without mechanical movement, providing ultrahigh data throughput. Each polarizer-antenna unit constructively superimposes their filtering effect, resulting in a 45–65 dB extinction ratio that approaches the system dynamic range. The superb illumination and detection linearity provides an outstanding polarization accuracy and eliminates the need for complicated calibration. Reflection characterization of the magneto-optical properties of an InAs wafer demonstrates the generalized ability to simultaneously obtain multiple dielectric functions. Transmission ellipsometric imaging of liquid crystals subjected to an inhomogeneous electric field further highlights the excellent efficiency. The proposed technique significantly expands the capabilities of terahertz spectroscopy, paving ways to anisotropic materials, in situ monitoring, and polarization-sensitive devices.

Balancing ensemble averaging and signal stationarity when processing acoustic data recorded during a rocket launch

There are many important details to consider when collecting acoustical data during a rocket launch including system noise floor, dynamic range and transducer sensitivity. In this talk, the choice of signal processing parameters will also be shown to be important. Since the pressures are created by turbulence, ensemble averaging is key to reducing random variation. As such, the use of a Hanning window with 50% overlap would be customary for performing this type of processing. However, as the rocket lifts off, the source location moves, and the data can only be considered stationary for short blocks of time. Therefore, the ability to average is limited by non-stationarity. To balance these competing phenomena, an adjustable windowing function such as the Tukey window may be more appropriate than Hanning. Noise data collected at two different launches will be used to compare of the Hanning window with 50% overlap to that using of the Tukey window with a taper of α = 0.25, which filters 12.5% of the signal at each extremity, with 87.5% overlap. The use of both window types will be compared when estimating auto spectral densities and integrated overall levels. The effect of blocksize will also be determined.

Trajectory Predictor and Conflict Detection Figures of Merit for a Performance-Based Adaptive Air Traffic Monitoring System

This paper investigates the impact of trajectory predictor performance on the encounter probability generated by an adaptive conflict detection tool and examines the flexibility of the tool dependent on its adjustable thresholds, using historical radar track data. To achieve these objectives, two figures of merit were proposed: System Dynamic Range and System Tuning Envelope. To examine the conflict detection’s performance variability under different uncertainty levels and predictor types, simple multi-horizon trajectory predictors trained with two machine learning techniques of different characteristics are assessed at various look-ahead times: extreme gradient boosting with a discrete nature and a multi-layer perceptron regressor with a continuous nature. The results highlight the interdependence between the performances of the trajectory predictor and the conflict detector, and the quantification of this relationship can be represented through a sigmoid function. In addition, the two proposed figures of merit are effective for selecting suitable operating points in an adaptive conflict detector, based on dynamic thresholds and the performance requirements necessary for the trajectory predictors to achieve the expected detection performance at different look-ahead time.

Generalized Theory and Realization of Continuously Loss-Programmable Bandpass Filtering Attenuators

In this article, a generalized theory of bandpass filtering attenuators (filtenuators) is proposed. A filtenuator is a device that combines the frequency-selective characteristics of a filter and the loss-programmable characteristics of an attenuator into a single component. The loss-programmable aspect of the filtenuator is based on the tuning of a <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\pi$</tex-math> </inline-formula> -network of resistances, which are implemented using p-i-n diodes to control the individual resistance values electronically. A loss-programmable, third-order Chebyshev bandpass filtenuator is designed, fabricated, and measured to verify the generalized theory. The filtenuator is designed to operate at 1 GHz and has a tunable attenuation range of 2–10 dB. This proposed filtenuator demonstrates the feasibility of a tunable, low-cost, size, weight, and power (C-SWaP) solution to increase radio frequency (RF) system dynamic range and a design process that allows for future development of filtenuators.

Detection and characterization of local nonlinearity in a clamped‐clamped beam with state space realization

AbstractThe state space representation of linear and nonlinear systems is widely used in the literature for system characterization, system identification, and model‐based control synthesis. In the case of systems with local nonlinearity, the realization of a state space model where the states are physically interpretable as a requirement has been a challenging task. This requirement becomes more emphasized, especially in the scope of industrial high‐precision systems. Consequently, the class of black‐box system identification approaches becomes less attractive. In the scope of this paper, we are interested in modeling systems with dominant local nonlinearity where employing linear models can only cover a limited range of system dynamics. More specifically, geometric nonlinearities which are present in the joints (bolted) of structural interfaces are analyzed. The main goal is to provide systematical modeling of such systems without using a sparse nonlinear representation. Such a low‐order nonlinear model can improve the simplicity of analyzing the nonlinear system and can be used for structural vibration and noise control. In order not to neglect the sophisticated linear modeling technique, the linear model is proposed to be extended by means of smooth nonlinear terms. The systematic approach contains the modeling of the linear counterpart followed by the localization and characterization steps in the well‐known three‐step paradigm. For the characterization step, this work relies on the acceleration surface method (ASM). The experimental setup under study, as a benchmark, is a set of two beams of different lengths and thicknesses connected by a screw that is excited by a mechanical shaker. The axes are oriented in the transverse direction of the beams, while the boundaries are realized as imperfect clamped‐clamped boundary conditions at two ends in the model. Consequently, by selecting the excitation amplitude, we can control the dominant dynamics at lower excitation amplitudes and invoke the local nonlinearity at higher amplitudes. For higher excitation levels using sine sweep signals, the phase space information of the shaker and accelerometer sensors is used to detect the local nonlinearities along the clamped‐clamped beam. The detected and characterized nonlinearities are incorporated into the linear system as a systematic approach for modeling such a structurally nonlinear system.

Phase Unwrapping Method of Φ-OTDR System Based on Recursive-Branch-Cut Algorithm

Phase unwrapping is a crucial technique in phase-sensitive optical time domain reflectometry (Φ-OTDR) systems. Due to the effects of system under-sampling, I/Q imbalance and environmental noise, the traditional method of unwrapping the phase is prone to wrapping or even distortion. In this work, a two-dimensional phase unwrapping method based on the recursive-branch-cut (RBC) algorithm is proposed and studied to improve the accuracy of the demodulated phase waveform. The data near the vibration location is expanded into a two-dimensional wrapped phase map along the time direction. According to the abnormal phase distribution law, the two-dimensional wrapped phase map is divided into sliding windows of different lengths. Under the constraint of ensuring the global continuity of the phase, the local phase is optimized by selecting an appropriate integration path, and the error is minimized, thereby suppressing the propagation of abnormal noise in the global. The experimental results show that in the range of 1-80 Hz, the method can stably increase the upper limit of the system dynamic range by 3.21 dB. At the same time, the system has a good linear strain response capability, and the strain sensitivity is 22.46rad/με×m and R <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> =0.9997. In addition, the method greatly improves the demodulation characteristics without increasing the generality and practicability of the system, which is beneficial to the fully digital realization of the heterodyne detection technology.

High Dynamic Range 100G PON Enabled by SOA Preamplifier and Recurrent Neural Networks

In recent years the PON research community has focused on future systems targeting 100 Gb/s/ <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\lambda$</tex-math></inline-formula> and beyond, with digital signal processing seen as a key enabling technology. Spectrally efficient 4-level pulse amplitude modulation (PAM4) is seen as a cost-effective solution that exploits the ready availability of cheaper, low-bandwidth devices, and Semiconductor Optical Amplifiers (SOA) are being investigated as receiver preamplifiers to compensate PAM4's high signal-to-noise ratio requirements and meet the demanding 29 dB PON loss budget. However, SOA gain saturation-induced patterning distortion is a concern in the context of PON burst-mode signalling, and the 19.5 dB loud-soft packet dynamic range expected by the most recent ITU-T 50G standards. In this paper we propose a recurrent neural network equalisation technique based on gated recurrent units (GRU-RNN) to not only mitigate SOA patterning affecting loud packet bursts, but to also exploit their remarkable effectiveness at compensating non-linear impairments to unlock the SOA gain saturated regime. Using such an equaliser we demonstrate <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$ &gt; 28$</tex-math></inline-formula> dB system dynamic range in 100 Gb/s PAM4 system by using SOA gain compression in conjunction with GRU-RNN equalisation. We find that our proposed GRU-RNN has similar equalisation capabilities as non-linear Volterra, fully connected neural network, and long short-term memory based equalisers, but observe that feedback-based RNN equalisers are more suited to the varying levels of impairment inherent to PON burst-mode signalling due to their low input tap requirements. Recognising issues surrounding hardware implementation of RNNs, we investigate a multi-symbol equalisation scheme to lower the feedback latency requirements of our proposed GRU-RNN. Finally, we compare equaliser complexities and performances according to trainable parameters and real valued multiplication operations, finding that the proposed GRU-RNN equaliser is more efficient than those based on Volterra, fully connected neural networks or long short-term memory units proposed elsewhere.

Research on the Single-Double Interval Closed-Loop Method of Resonant Fiber Optic Gyro

Resonant fiber optic gyro (RFOG) is a type of inertial sensor with great application potential. Its closed-loop signal detection methods include single closed-loop, double closed-loop and other methods to ensure high system stability and high-precision signal output. In view of the respective advantages of single and double closed-loop systems, a single-double interval closed-loop scheme for RFOG is proposed in this letter. By introducing the threshold trigger mechanism, the advantages of low control signal noise of the single closed-loop system and large dynamic range of the double closed-loop system are fully combined. In addition, in order to improve the linearity of the demodulation curve, a linear fitting method is applied to the system. The experiment shows that the short-term and long-term stability of the system have been improved effectively.

Pulsed microwave photonic vector network analyzer based on direct sampling.

Pulsed VNAs enabling large dynamic measurement at a low pulse duty cycle are necessary for the characterization of active devices due to the overheating damage risk under continuous wave stimulation. In this paper, we proposed a pulsed microwave photonic vector network analyzer (p-MPVNA) based on direct sampling. With the broad system bandwidth of the p-MPVNA and undersampling technique, pulsed signals are received thru asynchronous wideband detection, and pulsed S-parameters are calculated thru vector superposition. In asynchronous wideband detection, the continuous spectrum of the pulsed signal is discretized into multiple frequency components. A low repetition rate optical pulse train undersamples the pulsed signal, and the discretized frequency components are aliased. The frequency components in the main lobe including most energy of the pulse signal are vector superimposed to calculate the pulsed S-parameter. The proposed p-MPVNA has a dynamic range decreases rate of 10log(duty cycle) when pulse duty cycle is below 10% , which is much slower than that of 20log(duty cycle) for classical narrowband detection. An experimental p-MPVNA is established for validation. A 6 to 18 GHz microwave amplifier is measured with continuous and pulsed power supply and the measured gain curves are consistent with the results from a commercial VNA. The system dynamic range decrease with pulse duty cycle is verified by the pulsed S-parameter measurement of a 10 GHz low pass filter under continuous and pulsed stimulation.

Comprehensive stray light (flare) testing: Lessons learned

Stray light (also called flare) is any light that reaches the detector (i.e., the image sensor) other than through the designed optical path. Depending on the mechanism causing stray light, it can introduce phantom objects (ghosts) within the scene, reduce contrast over portions of the image, and effectively reduce system dynamic range. These factors can adversely affect the application performance of the camera and, therefore, stray light measurement is to be included in the upcoming IEEE-P2020 standard for measuring automotive image quality. The stray light of a camera can be measured by capturing images of a bright light source positioned at different angles in (or outside of) the camera&#x2019;s field of view and then processing those captured images into metric images with associated summary statistics. However, the setup and light source can have a significant impact on the measurement. In this paper, we present lessons learned and various technical elements to consider for stray light (flare) testing of digital imaging systems. These elements include the radiometric (e.g., brightness) and geometric (e.g., size) qualities of the light source and setup. Results are to be presented at the conference.

True eddy accumulation – Part 2: Theory and experiment of the short-time eddy accumulation method

Abstract. A new variant of the eddy accumulation method for measuring atmospheric exchange is derived, and a prototype sampler is evaluated. The new method, termed short-time eddy accumulation (STEA), overcomes the requirement of fixed accumulation intervals in the true eddy accumulation method (TEA) and enables the sampling system to run in a continuous flow-through mode. STEA enables adaptive time-varying accumulation intervals, which improves the system's dynamic range and brings many advantages to flux measurement and calculation. The STEA method was successfully implemented and deployed to measure CO2 fluxes over an agricultural field in Braunschweig, Germany. The measured fluxes matched very well against a conventional eddy covariance system (slope of 1.04, R2 of 0.86). We provide a detailed description of the setup and operation of the STEA system in the continuous flow-through mode, devise an empirical correction for the effect of buffer volumes, and describe the important considerations for the successful operation of the STEA method. The STEA method reduces the bias and uncertainty in the measured fluxes compared to conventional TEA and creates new ways to design eddy accumulation systems with finer control over sampling and accumulation. The results encourage the application of STEA for measuring fluxes of more challenging atmospheric constituents such as reactive species. This paper is Part 2 of a two-part series on true eddy accumulation.

Investigating the effect of density variation on pitch angle scattering events of runaway electrons as observed through electron cyclotron emission diagnostic at Aditya-upgrade tokamak.

Nascent observations about the influence of kinetic instabilities on electron cyclotron emission (ECE) from runaway electrons (REs) have been detected and explored at the Aditya-Upgrade (Aditya-U) tokamak. The developed broadband ECE radiometer system offers wideband measurements by integrating several radio frequency units with a fixed intermediate frequency receiver with multiple channels, which is a novel approach to meet the needs of the localized measurements at various toroidal fields and extend the system dynamic range. The low density (ne ≤ 1 × 10-19m-3) plasma discharges at Aditya-U are consistently accompanied by a 20%-40% increase in the ECE radiometer signal amplitude within 100 µs and sporadic step-like modulations. The Pitch Angle Scattering (PAS) of REs induced by kinetic instabilities is a potential candidate for their occurrence. This steep jump in the radiometer signals was detected due to its high temporal resolution of 10 µs. A "PREDICT" code that employs the relativistic test particle model validates these experimental findings of the radiometer diagnostic for the first time for Aditya-U tokamak. Preliminary observations of the ECE radiometer signals also show that additional gas puffs can be used to vary the trigger timings of such PAS events or even lead to their complete avoidance.

Constitutional design for dynamic democracies: A framework for analysis

Abstract Over time, a constitution may become suboptimal for the political system that it is meant to support and yet remain in place, largely unchanged. Thus, we might ask how a constitution might be designed to remain ideal for a democracy as it evolves, and indeed whether this is even possible. This practical dilemma has not been rigorously analyzed in the literature on constitutional design, however, because this research agenda has tended to downplay the potential for democracies to transform over time. To remedy this gap, this article sketches an explicitly temporal approach to design, which takes account of a wide range of political system dynamics. The framework contributes insights into the various ways that constitutional structures can be designed to operate over time; the alignment between these setups and different political system dynamics; and the means by which a constitutional design process might be reconfigured to give more weight to the prospect of fundamental political change.

Stochastic models of stem cells and their descendants under different criticality assumptions

We study time continuous branching processes with exponentially distributed lifetimes, with two types of cells that proliferate according to binary fission. A range of possible system dynamics are considered, each of which is characterized by the mutation rate of the original cells and the survival probability of the altered cells’ progeny. For each system, we derive a closed-form expression for the joint probability generating function of cell counts, and perform asymptotic analysis on the behaviors of the cell population with particular focus on probability of extinction. Part of our results confirms known properties of branching processes using a different approach while other are original. While the model is best suited for modeling the fate of differentiating stem cells, we discuss other scenarios in which these system dynamics may be applicable in real life. We also discuss the history of the subject.

The Two-Stage PI2 Control Strategy

PI <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> is a stochastic optimal control method generally regarded as a reinforcement learning algorithm. Recent work, however, suggests that the reinforcement learning aspect of PI <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> actually appears when optimizing feedforward controls which will lead to optimal closed-loop performance once combined with feedback controls. These feedbacks are necessary to achieve the predicted performance, yet have been largely neglected in the literature and applications due to their complexity. In this letter, we show that the feedbacks actually take a simple-to-implement form for a wide range of system dynamics, paving way for future research and applications of PI <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> . The correctness of the results is demonstrated through numerical simulations.

A 32-Channel Time-Multiplexed Artifact-Aware Neural Recording System.

This paper presents a low-power, low-noise microsystem for the recording of neural local field potentials or intracranial electroencephalographic signals. It features 32 time-multiplexed channels at the electrode interface and offers the possibility to spatially delta encode data to take advantage of the large correlation of signals captured from nearby channels. The circuit also implements a mixed-signal voltage-triggered auto-ranging algorithm which allows to attenuate large interferers in digital domain while preserving neural information. This effectively increases the system dynamic range and avoids the onset of saturation. A prototype, fabricated in a standard 180 nm CMOS process, has been experimentally verified in-vitro with cellular cultures of primary cortical neurons from mice. The system shows an integrated input-referred noise in the 0.5-200 Hz band of 1.4 μVrms for a spot noise of about 85 nV /√{Hz}. The system draws 1.5 μW per channel from 1.2 V supply and obtains 71 dB + 26 dB dynamic range when the artifact-aware auto-ranging mechanism is enabled, without penalising other critical specifications such as crosstalk between channels or common-mode and power supply rejection ratios.

Utilization of slow light enhancement of four-wave mixing within a silicon photonic crystal for microwave frequency measurement purposes

We report the demonstration of an instantaneous frequency measurement system based on the four-wave mixing (FWM) effect in short dispersion engineered slow-light silicon photonic crystal waveguides for RF frequency measurement purposes within a range of 10 MHz to 80 GHz. Three nonlinear media were investigated including 3 mm ridge waveguide, 80 µm nanowire, and 80 µm photonic crystal (PhC). The system size could thus be decreased, and as a result system integration would become possible. We have shown that the optical power required to excite FWM is low enough to remove any need for optical amplification, and hence the system noise floor will be kept low. Issues due to the amplifier saturation will also be resolved this way. As a result, no noise reduction system, like lock-in amplification, would be required. A better system latency will also be achieved accordingly. The system dynamic range would also be improved in two ways. First, due to the low noise floor, and second, because of removing any optical amplifier that possibly could become saturated at higher power levels. All three media behaviors were simulated by the split step Fourier method, and the results showed that the best medium to be used is PhC.

Signal and Noise Analysis of an Open-Circuit Voltage Pixel for Uncooled Infrared Image Sensors

An imaging pixel unit-cell topology leveraging a photodetector in the forward-bias region is proposed. Connecting the anode of the photodiode to the gate of a NMOS device operating in the subthreshold region provides the basis for a new open-circuit voltage pixel (VocP) architecture. Theoretical analysis is presented to show the response and performance benefits of the VocP in comparison to a conventional pixel. Based on this analysis, the signal and noise relationships for both pixels are derived and leveraged to construct an end-to-end readout system model. The model results highlight potential performance benefits of the VocP over a conventional direct-injection pixel topology. To verify the analysis, the proposed VocP readout architecture is fabricated along with a conventional direct-injection pixel readout in a $0.18~\mathrm {\mu }\text{m}$ CMOS technology. The VocP performance is compared to a traditional reverse-bias current-mode photodetector configuration. Simulation, modeling, and measurements align with the proposed analytical model. Benefits in system sensitivity and dynamic range are demonstrated showing more than a $2\times $ improvement in noise-equivalent temperature difference and a 4 dB improvement in dynamic range.

Ultra-Wideband Systems with Energy Harvesting Units for Sensors, 5G, IoT and Medical Systems

The high tech industrial revolution in the last fifty years depleted and ruined the planet natural resources. Energy harvesting is the main challenge in the research in green technologies. Compact wideband efficient antennas are crucial for energy harvesting portable sensors and systems. Small antennas have low efficiency. The efficiency of 5G, IoT communication and energy harvesting systems may be improved by using wideband efficient passive and active antennas. The system dynamic range may be improved by connecting amplifiers to the small antenna feed line. Ultra-wideband portable harvesting systems are presented in this paper. This paper presents new Ultra-Wideband energy harvesting system and antennas in frequencies ranging from 0.15 GHz to 18 GHz. Three wideband antennas cover the frequency range from 0.15 GHz to 18 GHz. A wideband metamaterial antenna with metallic strips covers the frequency range from 0.15 GHz to 0.42 GHz. The antenna bandwidth is around 75% for VSWR better than 2.3:1. A wideband slot antenna covers the frequency range from 0.4 GHz to 6.4 GHz. A wideband fractal notch antenna covers the frequency range from 6 GHz to 18 GHz. Printed passive and active notch and slot antennas are compact, low cost and have low volume. The active antennas may be employed in energy harvesting portable systems. The antennas and the harvesting system components may be assembled on the same, printed board. The printed notch and slot antennas bandwidth are from 75% to 100% for VSWR better than 3:1. The slot and notch antenna gain is around 3 dBi with efficiency higher than 90%. The antennas electrical parameters were computed in free space and near the human body. There is a good agreement between computed and measured results.

Testing and evaluation method for HDR thermal imaging system dynamic range performance

Testing and evaluation method for HDR thermal imaging system dynamic range performance