Waveform Sampling Research Articles

Development of a sealed MRPC with high time resolution

Multi-gap Resistive Plate Chambers (MRPC) are used in the Solenoidal Large Intensity Device (SoLID) at Jefferson Lab (JLab) to identify kaons. SoLID requires 20 ps for the total time resolution. In this paper, a sealed MRPC (sMRPC) prototype with 4 stacks and 7 uniform gas gaps is designed to reach a good time resolution. At the same time, sMRPC can lower the airflow through the chamber to reduce the greenhouse pollution. Both analog signal discrimination & TDC electronic system and waveform sampling electronic system are used for the readout of the signal. In cosmic tests, we compared the time resolution of these electronic readout methods and measured the efficiency of the sealed MRPC. The preliminary result shows that the MRPC prototype has an efficiency higher than 95%. The sealed MRPC prototype using waveform sampling system, has a time resolution of 40 ps, while a 54 ps time resolution is obtained using analog signal discrimination & TDC electronic system.

Applications of nonlinear four-wave mixing in optical communication

In this paper I will briefly review some applications of nonlinear four-wave-mixing in optical fibers and silicon-nitride waveguides. This includes ultrafast all-optical waveform sampling and ‘noiseless’ phase-sensitive optical amplification which have been demonstrated to enable signal recovery at very low optical powers.

Low-power high-dynamic-range analog front-end for picosecond waveform sampling ASICs

This short communication presents an analog front-end (AFE) circuit used in the switched-capacitor array (SCA) for the waveform sampling ASIC. The idea to use in SCA-AFE native transistors which are common in today’s CMOS technologies offers a feasible solution to the issue of achieving picosecond time resolution with a low supply voltage. The circuit features a MOS capacitor and a source follower both of which are implemented with the native transistors, and a simple rail-to-rail comparator. A prototype PISTWAVE1 ASIC is designed in a 55 nm CMOS with a single 1.2 V supply voltage, the experimental results show the ASIC achieves a dynamic range of 0.1∼1.1 V, a 65.3 dB signal-to-noise ratio (SNR) with voltage calibration and a less than 10 ps time resolution. The overall power consumption is less than 10 mW/channel at a sampling rate of nearly 6 GS/s.

A 64-channel waveform sampling ASIC for SiPM in space-born applications

The architecture of a 64-channel ASIC for the readout of Silicon Photomultipliers in space experiments is described. Each channel embeds a front-end amplifier with a common gate topology followed by a 256 cells analogue memory with a sampling frequency of 200 MHz. A single memory cell includes a storage capacitor, a single-slope Analog-to-Digital Converter (ADC) with programmable resolution between 8 and 12 bits and the digital control logic. To save power, the A/D conversion is carried-out only when a trigger signal is received. The trigger can either be generated inside the ASIC or provided by an external source. The analogue samples are digitized in parallel, thus reducing the conversion dead time. The memory cells can be arranged in a single array or they can be grouped in shorter slots of 32 or 64 cells that work in a multi-buffer configuration. The channels can work independently or they can be synchronised to acquire the same time-frame in the full chip. The target power consumption is 5 mW/channel. The ASIC is being designed in a 65-nm CMOS technology. A digital-on-top flow is applied for the integration and final validation of the chip. The tape-out is scheduled in the first quarter of 2023.

Status and recent extensions of the Caribou DAQ system for picosecond timing with an FPGA TDC

Caribou is a flexible open-source DAQ system developed and used within several collaborative frameworks (CERN EP R&D, RD50, AIDAinnova) for laboratory and high-rate beam tests and easy integration of new silicon-pixel detector prototypes. It uses common hardware, firmware and software components that are shared across different projects, thereby reducing the development effort and cost for such readout systems significantly. This contribution introduces the FASTPIX, APTS and DPTS detectors recently integrated in Caribou and their requirements in terms of waveform sampling and timing of digital pulses. A Time-to-Digital-Converter implemented in the Caribou FPGA was developed to overcome the limitations of the previously used oscilloscope-based readout. It allows for precision timing over large time spans required for the Time-of-Arrival, Time-over-Threshold, and position encoding used in the FASTPIX and DPTS test chips with asynchronous digital readout. A time resolution after calibration of better than 10 ps is achieved.

Time-Resolved Optical Spectrum Measurement of Multi-Mode Fabry-Perot Laser Diodes

Fabry-Perot (FP) laser diodes usually have multiple longitudinal modes. An optical spectrum analyzer (OSA) is able to measure the average power distribution of the mode structure but cannot detect the dynamics of mode competition which is the origin of the mode partition noise. We demonstrate a time-resolved optical spectrum measurement technique based on frequency-to-time conversion through time gating, chromatic dispersion, and real-time waveform sampling. This allows to investigate the dynamics of mode competition and correlation of relative intensity noises among different FP modes of the diode laser.

Recognition of Hybrid PQ Disturbances Based on Multi-Resolution S-Transform and Decision Tree

Aiming at the problems of multiple types of power quality composite disturbances, strong feature correlation and high recognition error rate, a method of power quality composite disturbances identification based on multi-resolution S-transform and decision tree was proposed. Firstly, according to IEEE standard, the signal models of seven single power quality disturbances and 17 combined power quality disturbances are given, and the disturbance waveform samples are generated in batches. Then, in order to improve the recognition accuracy, the adjustment factor is introduced to obtain the controllable time-frequency resolution through multi-resolution S-transform time-frequency domain analysis. On this basis, five disturbance time-frequency domain features are extracted, which quantitatively reflect the characteristics of the analyzed power quality disturbance signal, which is less than the traditional method based on S-transform. Finally, three classifiers such as K-nearest neighbor, support vector machine and decision tree algorithm are used to effectively complete the identification of power quality composite disturbances. Simulation results show that the classification accuracy of decision tree algorithm is higher than that of K-nearest neighbor and support vector machine. Finally, the proposed method is compared with other commonly used recognition algorithms. Experimental results show that the proposed method is effective in terms of detection accuracy, especially for combined PQ interference.

Classification of Terrestrial Lidar Data Directly From Digitized Echo Waveforms

Information derived from full-waveform (FW) data collected by FW laser scanning systems has already been shown to be relevant for point cloud analysis tasks. Relevant waveform attributes to populate the corresponding point’s feature vector are typically provided through a post-processing FW analysis (FWA) technique based on fitting the echo waveform with a parametric function describing the shape and location of the echo pulse in the waveform. Samples of the digitized echo are the primary source for any waveform analysis using parametric functions. On the other hand, for some FW laser scanning systems, describing the complex system response model using a simple parametric function seems challenging or impractical. Earlier studies have shown the potential of waveform’s digital samples as relevant waveform attributes, for point cloud classification. The main goal of this study is to extend earlier experiments on direct exploitation of returned waveform signals collected by a FW terrestrial laser scanning (TLS) system in a built environment for point cloud classification, to multi-return waveform signals. Furthermore, the classification performance on feature vectors containing calibrated waveform attributes, derived from a waveform processing approach performed in real-time by the FW TLS system, is evaluated on multiple-echo waveforms and compared with the classification performance derived from the proposed FW data classification technique. Classification performance derived through the proposed technique demonstrates high information content of raw digitized waveform samples. Results show that feature vectors containing samples of digitized echoes carry more information about physical properties of the target than those containing calibrated waveform attributes.

Ultra-broadband all-optical sampling of optical waveforms.

Optical-field sampling techniques provide direct access to the electric field of visible and near-infrared light. The existing methods achieve the necessary bandwidth using highly nonlinear light-matter interaction that involves ionization of atoms or generation of charge carriers in solids. We demonstrate an alternative, all-optical approach for measuring electric fields of broadband laser pulses, which offers an advantage in terms of sensitivity and signal-to-noise ratio and extends the detection bandwidth of optical methods to the petahertzdomain.

1268: EVALUATING LOAD-DEPENDENT CONTRACTILITY TO PREDICT FLUID RESPONSIVENESS IN CRITICALLY ILL CHILDREN

Introduction: Fluid boluses are commonly administered to critically ill children with hypotension, but response is inconsistent. Inability to predict response to bolus may delay vasoactive infusion, increasing time in shock and leading to fluid overload. Stroke volume (SV) response to bolus varies with both contractility and volume of fluid via the Starling curve relationship. The maximum rate of systolic upstroke of the arterial line waveform (dp/dtmax) is a load-dependent estimate of cardiac contractility associated with SV response to bolus. We hypothesized that as dp/dtmax has previously been associated with SV response, dp/dtmax would also be associated with mean arterial pressure (MAP) response to bolus. Methods: This was a retrospective study of IV fluid boluses >10ml/kg given to children who had arterial waveform data captured in Bedmaster® during pediatric intensive care unit admissions from 3/2013-8/2020. At least 2hrs were required between boluses and every bolus had at least 30sec of adequate pre-bolus arterial waveform data. Dp/dtmax was calculated in 10sec intervals from the first difference of adjacent waveform samples and averaged over the 20min pre-bolus. MAP responsiveness was defined as increase by >10% in MAP from pre-bolus to average 20min post-bolus. Logistic regression was used to assess the relationship between dp/dtmax and MAP response. Results: A total of 890 boluses administered to 539 children had available arterial line waveform data. Of these, 624 boluses in 421 patients met inclusion criteria, and 170 (27%) were responders. Univariate analysis did not show a significant relationship between dp/dtmax and MAP response (OR 1.00, 95% CI 0.99, 1.00). This lack of association persisted despite adding to the model fluid volume, age, or exposure to mechanical ventilation (ORs unchanged for all analyses). Conclusions: Pre-bolus dp/dtmax may not be a predictor of MAP fluid response when used in isolation. Given previous association found between dp/dtmax and SV fluid response, this discrepancy might be due to the effect of systemic vascular resistance (SVR) on MAP in children. Future studies of dp/dtmax in particular—and fluid responsiveness in general—may want to consider the effects of SVR in addition to SV when assessing clinical response to IV fluid bolus.

A Frequency Measurement Method for Protection of Smart Circuit-breaker

The application scale of new energy such as wind energy and solar energy in China is increasingly large. One of the characteristics of these energy sources is instability. Circuit-breakers play an important role protection in distributing these energy sources. Aiming at a new type of smart circuit-breaker architecture, this paper proposes a frequency measurement method for protection function, that is, the waveform sample value of high precision and high sample rate output by the DMA of the metering chip. The FIR filter is used to eliminate harmonic interference, impulse interference, etc of sample value. The frequency value is calculated by the interval duration between the two cross-zero points of sample value, and the simulation process, as well as the results, are given.

Research on a step delay method in sequential equivalent time sampling (ETS)

Sequential equivalent time sampling (ETS) has been extensively used in data acquisition instruments (e.g., sampling oscilloscopes and time domain reflectometers). A novel step delay method is proposed based on the frequency difference to obtain a higher sampling rate in sequential ETS. It is different from the classic step delay methods and is capable of increasing the sampling rate. The sampling clock and the repetitive signal are taken as examples in this study. The time-frequency conversion relationship indicates that a fine step delay will be generated in the time domain if there is a frequency difference between the two in the frequency domain. The core of the proposed method is the selection of the appropriate frequency difference (step delay) according to the desired equivalent sampling rate. Two experiments were performed to verify the proposed method. The feasibility of the proposed method is verified using a digital storage oscilloscope. Four cases are examined in the experiment, and the final equivalent sampling rate is obtained as 5 PS/s for the equivalent sampling of a 4.999 995GHz (or higher) signal. A data acquisition system with a 10 MS/s real-time sampling rate is designed to verify the feasibility of the proposed method, obtaining a theoretical equivalent sampling rate of 585 GS/s. The theoretical equivalent sampling rate and the examined equivalent sampling rate are consistent. The equivalent sampling waveform and real-time sampling waveform of a 1GHz signal are compared, and the comparison result suggests that the proposed method can acquire more waveform information. The proposed method obtains a high equivalent sampling rate for repetitive signals, and techniques (e.g., oversampling) are given to obtain higher vertical resolution. The proposed method, combined with a sample-and-hold amplifier, can also achieve a higher analog bandwidth.

LYSO scintillation light test with an ultra-fast MCP-PMT

The scintillator can be seen as a wavelength shifter which converts the incident particle into a number of photons at certain wavelength. The scintillation light decay time of scintillator is measured by coupling the scintillator with the photosensitive device. With the photoelectric conversion process and waveform sampling technology, the waveform of the signal responding to the scintillation light is obtained. Through exponential fitting, we can obtain the decay time of the scintillator. Traditionally the photosensitive device used to measure the scintillation light have a rise time on the order of nanoseconds. In our experiment, an ultra-fast MCP-PMT with a rise time of 100 ps and a transit time spread of 46 ps at single-photon mode was used to be coupled with the Lu1.8Y2SiO5:Ce (LYSO) scintillator and obtain the scintillation light waveforms. The waveform obtained is not a complete scintillation pulse and the photons in one scintillation event are distinguished and becomes discrete pulses. A new method is introduced to measure the decay time of the scintillator and the result for LYSO with the new method is compared to the results measured with the dynode PMT XP2020.

A Waveform Sampling Prototype ASIC for Picosecond-Level Time Measurement

This article presents the design and test results of a waveform sampling application-specific integrated circuit (ASIC) based on the switched capacitor array (SCA). It integrates eight differential-input channels, and each channel consists of a 256-cell capacitor array, 256 12-bit Wilkinson analog-to-digital converters (ADCs), and a serial data readout. A sampling rate of up to 5 Gsps is achieved with a low-jitter delay-locked loop (DLL). Two shared coarse counters running at the rising and falling edges of the reference clock are used to extend the time measurement range. Several crosstalk reduction strategies were adopted in the circuit design, especially in the clock generation circuit and the digitization circuit. The ASIC has been fabricated in 180-nm CMOS process. The test results show that the random noise is approximately 0.7-mV rms after the fixed-pattern noise correction and that the precision of waveform timing is better than 7-ps rms with the sampling interval correction.

An SCA ASIC-based multi-channel readout system for a prototype multi-purpose TPC at CSNS Back-n white neutron source

The back-streaming white neutron source (Back-n) at China Spallation Neutron Source (CSNS), which has excellent energy spectrum and good time resolution, provides superior conditions for neutron induced light charged particle tracking experiment. To track light charged particles, CSNS has proposed a project named Multi-purpose Time Projection Chambers (MTPC) and completed a 1519-channel prototype. A multi-channel readout system based on Switched Capacitor Arrays (SCA) waveform sampling ASIC was designed to meet the requirements of the prototype MTPC. This paper presents the structure of this readout system and the results of the beam test with MTPC at CSNS. Time of Flight spectrum of neutron beam and 3D-track of neutron induced light charged particles were successfully reconstructed. These test results prove the feasibility of large-scale MTPC.

Adaptive intra‐pulse interference waveform generation technique based on Convolutional Neural Network—Deep Neural Network with global priority information of radar signal

To adapt to the complex and changeable electromagnetic environment of radar detection, improve the jamming effect on frequency-agile radar and low probability of intercept radar, and solve the problem of poor jamming effect caused by intra-pulse jamming lagging behind target radar signal, a Convolutional Neural Network—Deep Neural Network jamming waveform generation method, based on prior global information of radar signal, is presented in this study. This proposed method uses two networks to generate the overall interference waveforms. One Convolutional Neural Network—Deep Neural Network derives prior global radar information from local prior radar information, which is used by the other Convolutional Neural Network—Deep Neural Network to generate interference. In the whole scheme, an algorithm to design the intra-pulse interference waveform based on the prior global information of the radar signal is proposed. The algorithm can generate the interference waveform samples from the number and area of multiple false targets and the relative peak between multiple false targets and the real target area by the relevant parameters. Then, an evaluation system (Matched filter, Constant False Alarm Rate Detector, and Distance resolution etc.) is established to evaluate the global effect of the designed interference waveforms. Finally, the time-domain Root Mean Squared Errors is used as the loss function to optimise the training of the network and ultimately achieve the requirement of generating intra-pulse adaptive interference waveforms based on radar signal fragments. The principle of generating interference waveforms is based on various aspects of the evaluation of the interference effect, which enhances the time domain correlation between multiple false target areas, thereby boosting the interference effect on the radar. The experimental results show that the proposed method based on the Convolutional Neural Network—Deep Neural Network can effectively solve the problem of intra-pulse interference lag and small effective interference area after the pulse pressure of the interference waveform matching filter. This study offers certain reference significance for the adaptive interference waveform design based on radar prior global information.

A 64-channel high-time resolution digital waveform sampling electronic system based on DRS4 for positron burst annihilation lifetime measurement

Measurements of the positron burst annihilation lifetime place high demand on the time discrimination of electronics. DRS4 chips based on switched capacitor array technology (SCA) are used to develop an electronic system with a total (2048 + 256)-channel sampling rate up to 5.12 GSPS, which can provide better time resolution and flexible data processing. The electronic system is modular in design and includes a front-end waveform sampling module (WSM) with 32 waveform sampling boards, each with 64 input channels plus 8 additional channels(one per DRS4 chip) for time calibaion, in addition to a back-end data processing module (DPM). The fan-out circuit integrated with the DPM will fan out the T0 signal in multiple stages at the time of positron burst generation and provide a common starting time and trigger signal for every DRS4 chip in the WSM. In this electronic system, the jitter of T0 after three-stage fan-out is 18 ps. After DC offset correction and time interval nonuniformity calibration, the coincidence time resolution with other channels is about 21 ps (σ). In addition, we correct the time difference of different channels of different chips, which is caused by different trace lengths of the multi-level fan-out T0 signal and the different fabrication processes. The electronic system is used to evaluate a 64-pixel detector module, and the time resolution of the detection module is measured to be 44 ps (σ).

Non-intrusive power waveform modeling and identification of air conditioning load

As a typical flexible load, air conditioner (AC) can play a crucial role in improving energy efficiency and optimizing power grid operation. However, due to its continuously variable load characteristics, AC faces difficulties in feature extraction and unsupervised modeling for non-intrusive load monitoring. In coping with these problems, a novel fully unsupervised non-intrusive AC monitoring scheme is designed. Firstly, an autonomous AC waveform modeling method is introduced. According to the general electrical characteristics, the candidate AC (start and stop, etc.) transient waveform templates are captured from the aggregated data. On this basis, the transient waveform samples similar to candidate template are extracted and verified based on the common usage habit characteristics. Then AC model consisting of waveform template and feature vector is subsequently established by multi-dimensional clustering of the waveform samples. Secondly, an online AC state identification and power disaggregation method is proposed. Based on the dynamic time warping algorithm and guided filtering algorithm, an AC transient waveform extraction method via template matching is presented, which can extract complete and pure transient AC waveforms from the multi-appliance mixed operation scenarios. According to the extracted AC waveforms, the state identification and energy consumption estimation can be realized. In addition, the incremental clustering is carried on the online identification results to further update the established AC model. Finally, the comparison experiments on the REDD dataset and the real-world data measured from multiple users in China show that, the proposed method can construct AC templates in unseen scenarios and update the established AC models automatically, thus outperform the benchmarks in both operating state identification and power disaggregation.

Study of analog-to-digital mixed integrated circuit configuration using number theory

Electronic circuits form the basis of much of the technology we use today. Professor Haruo Kobayashi and Assistant Professor Anna Kuwana, Division of Electronics and Informatics, Gunma University, Japan, are utilising classical mathematics, including theorems such as number theory and control theory in their design of circuits that contain elements of analogue signalling. Analogue circuit planning is regarded as an art as these circuits are typically designed based on mature designers' intuition and experiences in a process that is less systematic for coming up with new architectures and more designing than digital circuit design and Kobayashi and Kuwana firmly believe that 'beautiful' mathematics can facilitate truly great circuit design. Additional mathematics techniques employed by Kobayashi and the team are statistics, coding theory, modulation and signal processing algorithms and pairing pure mathematics theorems with electrical engineering is a key feature of the researchers' work. The team utilises theoretical analysis and simulations such as the circuit simulator (SPICE) and system simulator (MATLAB) to test its work and collaborates with semiconductor companies and electronic measurement instrument companies in Japan for smart circuit design and effective circuit testing. So far, results include that using SAR ADC configurations with Fibonacci sequence weights can improve the speeds and reliability of the SAR ADC. Also several new DAC architecutures and waveform sampling methods are derived based on mathematics.

Imperceptible black-box waveform-level adversarial attack towards automatic speaker recognition

Automatic speaker recognition is an important biometric authentication approach with emerging applications. However, recent research has shown its vulnerability on adversarial attacks. In this paper, we propose a new type of adversarial examples by generating imperceptible adversarial samples for targeted attacks on black-box systems of automatic speaker recognition. Waveform samples are created directly by solving an optimization problem with waveform inputs and outputs, which is more realistic in real-life scenario. Inspired by auditory masking, a regularization term adapting to the energy of speech waveform is proposed for generating imperceptible adversarial perturbations. The optimization problems are subsequently solved by differential evolution algorithm in a black-box manner which does not require any knowledge on the inner configuration of the recognition systems. Experiments conducted on commonly used data sets, LibriSpeech and VoxCeleb, show that the proposed methods have successfully performed targeted attacks on state-of-the-art speaker recognition systems while being imperceptible to human listeners. Given the high SNR and PESQ scores of the yielded adversarial samples, the proposed methods deteriorate less on the quality of the original signals than several recently proposed methods, which justifies the imperceptibility of adversarial samples.