Digital signal acquisition system for complex nuclear reaction experiments

A digital data-acquisition system based on XIA LLC products was used in a complex nuclear reaction experiment using radioactive ion beams.A flexible trigger system based on a field-programmable gate array(FPGA)parametrization was developed to adapt to different experimental sizes.A user-friendly interface was implemented,which allows converting script language expressions into FPGA internal control parameters.The proposed digital system can be combined with a conventional analog data acquisition system to provide more flexibility.The performance of the combined system was veri-fied using experimental data.

Adversarial attacks and defenses for digital communication signals identification

As modern communication technology advances apace,the digital communication signals identification plays an important role in cognitive radio networks,the communication monitoring and management systems.AI has become a promising solution to this problem due to its powerful modeling capability,which has become a consensus in academia and industry.However,because of the data-dependence and inexplicability of AI models and the openness of electromagnetic space,the physical layer digital communication signals identification model is threatened by adversarial attacks.Adversarial examples pose a common threat to AI models,where well-designed and slight perturbations added to input data can cause wrong results.Therefore,the security of AI models for the digital communication signals identification is the premise of its efficient and credible applications.In this paper,we first launch adversarial attacks on the end-to-end AI model for automatic modulation classifi-cation,and then we explain and present three defense mechanisms based on the adversarial principle.Next we present more detailed adversarial indicators to evaluate attack and defense behavior.Finally,a demonstration verification system is developed to show that the adversarial attack is a real threat to the digital communication signals identification model,which should be paid more attention in future research.

Investigation on Analog and Digital Modulations Recognition Using Machine Learning Algorithms

In the field of radiocommunication, modulation type identification is one of the most important characteristics in signal processing. This study aims to implement a modulation recognition system on two approaches to machine learning techniques, the K-Nearest Neighbors (KNN) and Artificial Neural Networks (ANN). From a statistical and spectral analysis of signals, nine key differentiation features are extracted and used as input vectors for each trained model. The feature extraction is performed by using the Hilbert transform, the forward and inverse Fourier transforms. The experiments with the AMC Master dataset classify ten (10) types of analog and digital modulations. AM_DSB_FC, AM_DSB_SC, AM_USB, AM_LSB, FM, MPSK, 2PSK, MASK, 2ASK, MQAM are put forward in this article. For the simulation of the chosen model, signals are polluted by the Additive White Gaussian Noise (AWGN). The simulation results show that the best identification rate is the MLP neuronal method with 90.5% of accuracy after 10 dB signal-to-noise ratio value, with a shift of more than 15% from the k-nearest neighbors’ algorithm.

100 Gb/s coherent chaotic optical communication over 800 km fiber transmission via advanced digital signal processing

Chaotic optical communication has shown large potential as a hardware encryption method in the physical layer.As an important figure of merit,the bit rate–distance product of chaotic optical communication has been continually improved to 30 Gb/s×340 km,but it is still far from the requirement for a deployed optical fiber communication system,which is beyond 100 Gb/s×1000 km.A chaotic carrier can be considered as an analog signal and suffers from fiber channel impairments,limiting the transmission distance of high-speed chaotic optical communications.To break the limit,we propose and experimentally demonstrate a pilot-based digital signal processing scheme for coherent chaotic optical communication combined with deep-learning-based chaotic synchronization.Both transmission impairment recovery and chaotic synchronization are realized in the digital domain.The frequency offset of the lasers is accurately estimated and compensated by determining the location of the pilot tone in the frequency domain,and the equalization and phase noise compensation are jointly performed by the least mean square algorithm through the time domain pilot symbols.Using the proposed method,100 Gb∕s chaotically encrypted quadrature phase-shift keying(QPSK)signal over 800 km single-mode fiber(SMF)transmission is experimentally demonstrated.In order to enhance security,40 Gb∕s real-time chaotically encrypted QPSK signal over 800 km SMF transmission is realized by inserting pilot symbols and tone in a field-programmable gate array.This method provides a feasible approach to promote the practical application of chaotic optical communications and guarantees the high security of chaotic encryption.

Design of a 14-Bit 1 MS/s Successive Approximation Analog-to-Digital Converter

A 14-bit successive approximation analog-to-digital converter (SAR ADC) with capacitive calibration has been designed based on the SMIC. 18 μm CMOS process. The overall architecture is in fully differential form to eliminate the effect caused by common mode noise. Meanwhile, the digital-to-analog converter (DAC) is a two-stage structure, which can greatly reduce the area of the capacitor array compared with the traditional DAC structure. The capacitance calibration module is mainly divided into the mismatch voltage acquisition phase and the calibration code backfill phase, which effectively reduces the impact of the DAC mismatch on the accuracy of the SAR ADC. The design of this paper is based on cadence platform simulation verification, simulation results show that when the sampling rate is 1 MS/s, the power supply voltage is 5 V and the reference voltage is 4.096 V, the effective number of bits (ENOB) of the ADC is 13.49 bit, and the signal-to-noise ratio (SNR) is 83.3 dB.

Wireless location algorithm using digital broadcasting signals based on neural network

In order to enhance the accuracy and reliability of wireless location under non-line-of-sight （NLOS） environments,a novel neural network （NN） location approach using the digital broadcasting signals is presented. By the learning ability of the NN and the closely approximate unknown function to any degree of desired accuracy,the input-output mapping relationship between coordinates and the measurement data of time of arrival （TOA） and time difference of arrival （TDOA） is established. A real-time learning algorithm based on the extended Kalman filter （EKF） is used to train the multilayer perceptron （MLP） network by treating the linkweights of a network as the states of the nonlinear dynamic system. Since the EKF-based learning algorithm approximately gives the minimum variance estimate of the linkweights,the convergence is improved in comparison with the backwards error propagation （BP） algorithm. Numerical results illustrate thatthe proposedalgorithmcanachieve enhanced accuracy,and the performance ofthe algorithmis betterthanthat of the BP-based NN algorithm and the least squares （LS） algorithm in the NLOS environments. Moreover,this location method does not depend on a particular distribution of the NLOS error and does not need line-of-sight （ LOS ） or NLOS identification.

基于双DSP(Digital Signal Processor)结构的有源滤波器检测及控制系统

简要介绍了DigitalSignalProcessor(DSP)的发展及其性能特点 ,详细讨论了一种利用双DSP构成的有源滤波器检测及控制系统的实现和基本结构及算法 .

Digitalization of inverting filter shaping circuit for nuclear pulse signals

In the design of filter shaping circuits for nuclear pulse signals,inverting filter shaping circuits perform better than non-inverting filter shaping circuits.Because these circuits facilitate changing the phase of a pulse signal,they are widely used in processing nuclear pulse signals.In this study,the transfer functions of four types of inverting filter shaping circuits,namely the common inverting filter shaping,improved inverting filter shaping,multiple feedback low-pass filter shaping,and third-order multiple feedback low-pass filter shaping,in the Laplacian domain,are derived.We establish the numerical recursive function models and digitalize the four circuits,obtain the transfer functions in the Z domain,and analyze the filter performance and amplitude-frequency response characteristics in the frequency domain.Based on the actual nuclear pulse signal of the Si-PIN detector,we realize four types of inverting digital shaping.The results show that under the same shaping parameters,the common inverting digital shaping has better amplitude extraction characteristics,the third-order multiple feedback low-pass digital shaping has better noise suppression performance,and the multiple feedback digital shaping takes into account both pulse amplitude extraction and noise suppression performance.

Digital Signal Processing Based Real Time Vehicular Detection System

Traffic monitoring is of major importance for enforcing traffic management policies.To accomplish this task,the detection of vehicle can be achieved by exploiting image analysis techniques.In this paper,a solution is presented to obtain various traffic parameters through vehicular video detection system(VVDS).VVDS exploits the algorithm based on virtual loops to detect moving vehicle in real time.This algorithm uses the background differencing method,and vehicles can be detected through luminance difference of pixels between background image and current image.Furthermore a novel technology named as spatio-temporal image sequences analysis is applied to background differencing to improve detection accuracy.Then a hardware implementation of a digital signal processing (DSP) based board is described in detail and the board can simultaneously process four-channel video from different cameras. The benefit of usage of DSP is that images of a roadway can be processed at frame rate due to DSP′s high performance.In the end,VVDS is tested on real-world scenes and experiment results show that the system is both fast and robust to the surveillance of transportation.

Measuring Absolute Delay of RNSS Signal Channel Using Digital Envelope Detection

The absolute delay caused by equipment of radio navigation satellite service (RNSS) signal channel must be calibrated in the application of positioning. The measurement accuracy of absolute delay will affect the positioning precision of RNSS user. An absolute delay measurement technique using digital envelope detection was developed for RNSS signal transmission channel. The RNSS transmission signal of navigation satellite and the one pulse per second (1PPS)generated by satellite time keeping system were sampled synchronously. With sampling data of 1PPS,the reference point of the absolute delay can be decided at first,and then sampling data of RNSS transmission signal were truncated. The truncated data were processed using digital envelop detection algorithm to search the phase converting points of RNSS signal. Finally,the absolute delay of RNSS signal transmitting channel was calculated. Uncertainty of measurement with proposed technique is lower than 0. 2 ns as the sampling frequency is 10 GHz.

Kravchenko atomic transforms in digital signal processing

The modified atomic transformations are constructed and proved. On their basis the new complex analytic wavelets are obtained. The proof of the Fourier transforms existence in L~ and L2 on the basis of the theory of atomic functions （AF） are presented. The numerical experiments of digital time series processing and physical analysis of the results confirm the efficiency of the proposed transforms.

A new method of demodulating the digital frequency modulation signals

A new method of estimating the frequency-known signals from the strong background noise was presented first. Then the new method was used in the demodulation of the digital frequency modulation (FSK) signals. The new demodulation method can complete the demodulation of the FSK signals only with the carrier frequency and without any carrier phase information. The simulation results show that the performance of anti-noise of the new method is better than that of the incoherent demodulation method and the fluctuation of the carrier phase has little effect on the new method. So the new demodulation method has a fine prospect in the practical applications.

Simulation and Design Optimization of Novel Microelectromechanical Digital-to-Analog Converter

A microelectromechanical Digital to Analog Converter (DAC) based on Weighted Gap (WG) principle is described,which is analogous to the weighed resistor DAC in electronic circuits.To convert the input of binary voltage to the output of analog displacement,the gaps are proposed to be employed as a scale factor.A finite element method is used to simulate the performance of the DAC.To reduce the error,the structure design is optimized and the maximum error of 0 002μm is obtained.

DATA BYPASSING ARCHITECTURE AND CIRCUIT DESIGN FOR 32-BIT DIGITAL SIGNAL PROCESSOR

This paper presents a design method of ByPassing Unit(BPU) in 32-bit Digital Signal Processor(DSP)-MD32. MD32 is realized in 0,18μm technology, 1.8V and 200 MHz working clock. It focuses on the Reduced Instruction Set Computer(RISC) architecture and DSP computation capability thoroughly, extends DSP with various addressing modes in a customized DSP pipeline stage architecture. The paper also discusses the architecture and circuit design of bypassing logic to fit MD32 architecture. The parallel execution of BPU with instruction decode in architecture level is applied to reduce time delay. The optimization of circuit that serial select with priority is analyzed in detail, and the result shows that about half of time delay is reduced after this optimization. Examples show that BPU is useful for improving the DSP's performance.The forwarding logic in MD32 realizes 8 data channels feedback and meets the working clock limit.

Energy-Efficient Large-Scale Antenna Systems with Hybrid Digital-Analog Beamforming Structure

A largescale antenna system （LSAS） with digital beamforming is expected to significantly increase energy efficiency （EE） and spectral efficiency （SE） in a wireless communication system. However, there are many challenging issues related to calibration, energy consumption, and cost in implementing a digital beamforming structure in an LSAS. In a practical LSAS deployment, hybrid digitalanalog beamforming structures with active antennas can be used. In this paper, we investigate the optimal antenna configuration in an N ＆#215; M beamforming structure, where N is the number of transceivers, M is the number of active antennas per transceiver, where analog beamforming is introduced for individual transceivers and digital beamforming is introduced across all N transceivers. We analyze the green point, which is the point of maximum EE on the EESE curve, and show that the logscale EE scales linearly with SE along a slope of lg2/N. We investigate the effect of M on EE for a given SE value in the case of fixed NM and independent N and M. In both cases, there is a unique optimal M that results in optimal EE. In the case of independent N and M, there is no optimal （N, M） combination for optimizing EE. The results of numerical simulations are provided, and these results support our analysis.

A Design of High-precision High-Voltage Fiber-Optic Analog Signal Isolation Converter

This paper introduces a design of high-precision high-voltage fiber-optic analog sig-nal isolation converter based on the technology of Voltage-to-Frequency (V/F) and Frequency-to-Voltage (F/V) conversion. It describes the principle, system configuration and hardware design.

An acquisition system of digital nuclear signal processing for the algorithm development

A principle and method of constructing the digital acquisition system is presented in this work,which is convenient for the study on the theories and algorithms of digital nuclear signal processing.The hardware system of the digital acquisition system consists of front-end controller,waveform digitizer and PC workstation,on which the software system has been developed based on Visual C++under Windows environment.The alterable-frequency sampling(AFS)algorithm and the alterable-frequency trapezoidal filter(AFTF)algorithm have also been studied in the real-time environment,along with a digital nuclear spectrum acquisition system being set up based on the new algorithms and theγ-ray spectra of 241Am being shown.A useful experimental platform could be provided by this work for the successive work such as the development of global digitized nuclear measurement system and the study of digital nuclear signal processing.

New WA-system of kravchenko functions in digital signal processing

On the basis of modified atomic transformations the new WA-systems of Kravchenko functions are constructed.As an example the digital processing of time series of the various physical nature processing is considered.The numerical experiments and physical analysis of the results confirm the efficiency of the proposed WA-systems of Kravchenko functions.

Multi-narrowband signals receiving method based on analog-to-information convertor and block sparsity

The analog-to-information convertor (AIC) is a successful practice of compressive sensing (CS) theory in the analog signal acquisition. This paper presents a multi-narrowband signals sampling and reconstruction model based on AIC and block sparsity. To overcome the practical problems, the block sparsity is divided into uniform block and non-uniform block situations, and the block restricted isometry property and sub-sampling limit in different situations are analyzed respectively in detail. Theoretical analysis proves that using the block sparsity in AIC can reduce the restricted isometric constant, increase the reconstruction probability and reduce the sub -sampling rate. Simulation results show that the proposed model can complete sub -sampling and reconstruction for multi-narrowband signals. This paper extends the application range of AIC from the finite information rate signal to the multi-narrowband signals by using the potential relevance of support sets. The proposed receiving model has low complexity and is easy to implement, which can promote the application of CS theory in the radar receiver to reduce the burden of analog-to digital convertor (ADC) and solve bandwidth limitations of ADC.

Overview of Energy-Efficient Successive-Approximation Analog-to-Digital Converters: State-of-the-Art and a Design Example

This paper makes a review of state-of-the- arts designs of successive-approximation register analog-to-digital converters （SAR ADCs）. Methods and technique specifications are collected in view of innovative ideas. At the end of this paper, a design example is given to illustrate the procedure to design an SAR ADC. A new method, which extends the width of the internal clock, is also proposed to facilitate different sampling frequencies, which provides more time for the digital-to-analog convert （DAC） and comparator to settle. The 10 bit ADC is simulated in 0.13 μm CMOS process technology. The signal-to-noise and distortion ratio （SNDR） is 54.41 dB at a 10 MHz input with a 50 MS/s sampling rate, and the power is 330 μW.