An innovative detection method of high frequency BPSK signal with low signal-to-noise ratio

Based on chaotic oscillator system, this paper proposes a novel method on high frequency low signal- to-noise ratio BPSK（ Binary Phase Shift Keying） signal detection. Chaotic oscillator system is a typical non-lin- ear system which is sensitive to periodic signals and immune to noise at the same time. Those properties make it possible to detect low signal-to-noise ratio signals. The BPSK signal is a common signal type which is widely used in modern communication. Starting from the analysis of advantages of chaotic, os~.illator system and signal features of the BPSK signal, we put forward a unique method that can detect low signar-to-noise ratio BPSK sig- nals with high frequency. The simulation results show that the novel method can dclct.t low signal-to-noise ratio BPSK signals with frequency in an order of magnitude of l0s Hz, and the input Signal-to-Noise Ratio threshold can be -20 dB.

Calculation method of the signal-to-noise ratio attribute of seismic data based on structural orientation

At present,most signal-to-noise ratio(SNR)estimation methods can only calculate the global and not the local SNR of seismic data.This paper proposes a calculation method of a structure-oriented-based seismic SNR attribute.The purpose is to characterize the temporal and spatial variation of the seismic data SNR.First,the local slope parameters of the seismic events are calculated using a plane wave decomposition filter.Then,the singular value decomposition method is used to calculate the local seismic data SNR,thereby obtaining it in time and space.The proposed method overcomes the insufficiency of a conventional global SNR to characterize any local seismic data features and uses the SNR as an attribute of seismic data to more accurately describe the signal-noise energy distribution characteristics of seismic data in time and space.The results of a theoretical model test and real data processing show that the SNR attribute can be used not only for seismic data quality evaluation but also for analysis and evaluation of denoising methods.

Effect of signal-to-noise ratio on the automatic clustering of X-ray diffraction patterns from combinatorial libraries

Hierarchical clustering algorithm has been applied to identify the X-ray diffraction(XRD)patterns from a high-throughput characterization of the combinatorial materials chips.As data quality is usually correlated with acquisition time,it is important to study the hierarchical clustering performance as a function of data quality in order to optimize the efficiency of high-throughput experiments.This work investigated the effects of signal-to-noise ratio on the performance of hier-archical clustering using 29 distance metrics for the XRD patterns from Fe−Co−Ni ternary combinatorial materials chip.It is found that the clustering accuracies evaluated by the F1 score only fluctuate slightly with signal-to-noise ratio varying from 15.5 to 22.3(dB)under the experimental condition.This suggests that although it may take 40-50 s to collect a visually high-quality diffraction pattern,the measurement time could be significantly reduced to as low as 4 s without substantial loss in phase identification accuracy by hierarchical clustering.Among the 29 distance metrics,Pearsonχ^(2)shows the highest mean F1 score of 0.77 and lowest standard deviation of 0.008.It shows that the distance matrixes calculated by Pearsonχ^(2)are mainly controlled by the XRD peak shifting characteristics and visualized by the metric multidimensional data scaling.

融合多源数据挖掘信息的非轴对称端壁/叶身联合成型设计空间知识挖掘

为厘清联合成型设计空间各造型方法对涡轮叶栅性能提升的贡献,将基于总变差分析的全局敏感性分析方法与平行坐标系及直方图、散点图等可视化技术相结合,提出了将多源数据挖掘信息进行融合的设计空间知识挖掘框架,并利用该框架对某小展弦比叶栅端壁/叶身联合成型设计空间进行知识挖掘。结果表明:叶栅气动损失增减对基元型线微调十分敏感;非轴对称端壁所带来的损失减少量与型线微调接近,但设计空间内不同非轴对称端壁样本性能波动较小,导致其重要性被全局敏感性分析方法低估;虽然单独采用弯叶片难以整体降低小展弦比叶栅损失,但将弯、型线微调和非轴对称端壁造型相结合可获得“1+1+1>3”的性能增益;在端壁/叶身联合成型设计空间内,将基元型线朝着后加载方向微调,并采用喉部附近下凹较深的非轴对称端壁造型及反弯叶片设计,可获得气动损失较小的叶栅设计。研究结果明晰了端壁/叶身联合成型设计空间优化解特征,可为类似小展弦比叶栅设计优化提供借鉴。

川东高陡构造灰岩出露区地震资料品质主控因素分析

川东构造地震地质条件可概括为“恶地形、石灰岩、陡构造”,一直是地震攻关的重点和难点。随着物探技术装备、采集处理技术发展,高陡构造顶部灰岩出露区(简称灰岩区)地震资料品质有较大提高,但信噪比仍然远低于构造两翼砂泥岩出露区。如何看待灰岩区低信噪资料比这一客观的地震现象,是地震攻关力度不够,还是受限于地震多次覆盖的假设条件,亟需解答。基于最新川东高密度三维和束线三维地震资料分析,从地震勘探基本原理出发,结合模型正演技术和地震资料处理解释,认为灰岩区低信噪比地震资料是客观存在的,根本原因是灰岩区地震地质条件不满足多次覆盖的假设条件。影响灰岩区低信噪比资料的主控因素有3点,1)灰岩区0~500 m表层岩溶地貌引起地震波散射,产生各类复杂噪声,向下传播能量快速吸收衰减,有效反射能量弱;2)受不同构造几何形态影响,灰岩区低信噪比资料特征有所不同;3)受灰岩区内外炮检距的影响,纵向上灰岩区地震成像质量存在浅、中、深层分带现象,由浅至深资料品质变好。文章指出,面对高陡构造灰岩区特殊的地震地质条件,地震攻关重点应放在提高中深层地震资料信噪比上。

Combining Radon-ambiguity transform with second-order difference to improve detection probability of LFM signals in low SNR

The Radon-ambiguity transform （RAT）, although efficient for detecting the linear frequency modulated signals （LFMs）, is troubled by the energy accumulation of noise in low signal-to-noise ratio （SNR）. A secondorder difference （SOD） method is proposed to treat with this problem. In the SOD method, the optimal search step and difference step are derived from the LFM rate resolution formula. The sharpness of the peaks of RAT is measured by curvature, and the sharpness, but not the magnitude of the peaks, is used to detect the LFMs. The SOD method removes the noise energy accumulation and reserves the drastically changing components integrally; thus, it improves the detection probability of LFMs in low SNR. The expected performance of the new method is verified by 100 Monte Carlo simulations.

Long term integration of radar signals with unknown Doppler shift for ubiquitous radar

Ubiquitous radar is a new radar system that provides continuous and uninterrupted multifunction capability within a coverage volume. Continuous coverage from close-in ＂pop-up＂ targets in clutter to long-range targets impacts selection of waveform parameters. The coherent processing interval （CPI） must be long enough to achieve a certain signal-to-noise ratio （SNR） that ensures the efficiency of detection. The condition of detection in the case of low SNR is analyzed, and three different cases that would occur during integration are discussed and a method to determine the CPI is presented. The simulation results show that targets detection with SNR as low as -26 dB in the experimental system can possibly determine the CPI.

Local binary pattern-based reversible data hiding

A novel local binary pattern-based reversible data hiding(LBP-RDH)technique has been suggested to maintain a fair symmetry between the perceptual transparency and hiding capacity.During embedding,the image is divided into various 3×3 blocks.Then,using the LBP-based image descriptor,the LBP codes for each block are computed.Next,the obtained LBP codes are XORed with the embedding bits and are concealed in the respective blocks using the proposed pixel readjustment process.Further,each cover image(CI)pixel produces two different stego-image pixels.Likewise,during extraction,the CI pixels are restored without the loss of a single bit of information.The outcome of the proposed technique with respect to perceptual transparency measures,such as peak signal-to-noise ratio and structural similarity index,is found to be superior to that of some of the recent and state-of-the-art techniques.In addition,the proposed technique has shown excellent resilience to various stego-attacks,such as pixel difference histogram as well as regular and singular analysis.Besides,the out-off boundary pixel problem,which endures in most of the contemporary data hiding techniques,has been successfully addressed.

Blind parameter estimation of pseudo-random binary code-linear frequency modulation signal based on Duffing oscillator at low SNR

Conventional parameter estimation methods for pseudo-random binary code-linear frequency modulation(PRBC-LFM)signals require prior knowledge,are computationally complex,and exhibit poor performance at low signal-to-noise ratios(SNRs).To overcome these problems,a blind parameter estimation method based on a Duffing oscillator array is proposed.A new relationship formula among the state of the Duffing oscillator,the pseudo-random sequence of the PRBC-LFM signal,and the frequency difference between the PRBC-LFM signal and the periodic driving force signal of the Duffing oscillator is derived,providing the theoretical basis for blind parameter estimation.Methods based on amplitude method,short-time Fourier transform method,and power spectrum entropy method are used to binarize the output of the Duffing oscillator array,and their performance is compared.The pseudo-random sequence is estimated using Duffing oscillator array synchronization,and the carrier frequency parameters are obtained by the relational expressions and characteristics of the difference frequency.Simulation results show that this blind estimation method overcomes limitations in prior knowledge and maintains good parameter estimation performance up to an SNR of-35 dB.

Tracking algorithm of BPSK signal in low bit SNR and high dynamic scenarios

A new tracking algorithm is proposed aiming at the tracking problem in low bit signal-to- noise ratio （i. e. , Eb/N0 ） scenarios, in which the bit clock regenerated by bit synchronization loop decides loop update moment. The double frequency processing and non-coherent accumulation tech- nologies are applied to eliminate the impact of data polarity inversion, and then long time accumula- tion improves the input signal-to-noise ratio of discriminator. The frequency locked loop and phase locked loop constitute a carrier loop in parallel, which can meet the high dynamic demands. The ef- fectiveness of this algorithm has been corroborated by theoretical analysis, simulation and measure- ments, and the new tracking algorithm has been used in an aerospace engineering project successfully.

Novel Frame Shift and Integral Technique for Enhancing Low-Light-Level Moving Images

A novel frame shift and integral technique for the enhancement of low light level moving image sequence is introduced. According to the technique, motion parameters of target are measured by algorithm based on difference processing. To obtain spatial relativity, images are shifted according to the motion parameters. As a result, the processing of integral and average can be applied to images that have been shifted. The technique of frame shift and integral that includes the algorithm of motion parameter determination is discussed, experiments with low light level moving image sequences are also described. The experiment results show the effectiveness and the robustness of the parameter determination algorithm, and the improvement in the signal-to-noise ratio （SNR） of low light level moving images.

数据模式感知的低成本云日志存储系统

公共云的日志服务能够全面提升研发、运维、运营和安全保障的能力,而云日志具有数据规模庞大、留存时间长、写入速度快、有用信息密度低、访问延迟要求高等特点.为了节省存储成本,需要满足3个要求:1)以较高压缩密度保存此类数据(压得狠);2)以较高的压缩速度实现数据写入(压得快);3)以低延迟对压缩数据进行快速检索(查得快).同时实现这三者是充满挑战的,需结合具体应用场景进行定制化设计.通过总结云日志中的典型数据模式,给出一种低成本云日志存储范式——数据模式感知的低成本云日志存储系统,从压缩率、压缩速度和检索延迟等3个方面对若干低成本云日志存储方法进行对比测试.最后,结合相关领域研究提出3点经验和思考,供未来的研究工作参考.

CNN算法的损失函数优化及在低信噪比资料中的应用

深度学习CNN算法的核心之一是其利用损失函数完成反传机制达到各层网络之间的优化,因此,不同的损失函数及反传机制带来训练阶段人工神经网络模型不同的网络优化效果,其影响了机器学习算法的泛化能力及预测效果。基于此,文中提出了一种改进的带惩罚系数的损失函数,解决了在断层识别问题中因正负样本的数量高度不均衡导致的网络朝着错误方向收敛的问题。将其用于网络中指导训练,通过不同损失函数下的网络模型对理论数据和实际数据的识别结果,证明了这种方法的有效性和适用性。在低信噪比资料中的断层识别中,这种改进的优化网络,能够得到更稳定和更可靠的断层识别结果,为研究区潜山内幕小断层及断缝系统识别提供一种高效可靠的方法技术。

低负载率下数据中心模块化UPS的智能休眠技术研究

智能休眠技术是数据中心UPS的主流节能模式之一。本文介绍了该技术的节能原理,并考虑系统的可靠性和智能化,对智能休眠机制及保护功能进行了分析、梳理和总结。最后以某数据中心为例,计算分析了开启智能休眠机制后的节能效果,并给出进一步挖掘低负载率下UPS节能潜力的建议。

基于Dropout-多尺度空洞卷积神经网络的轴承故障诊断

为了提高故障诊断模型对故障轴承低信噪比信号的特征提取能力,使模型在强噪声环境下仍能发挥作用,提出了一种基于Dropout-多尺度空洞卷积神经网络(D-MDCNN)的滚动轴承故障诊断模型。首先,通过Dropout数据预处理,对训练数据进行“损坏”,强迫模型仅依靠少量特征便可进行故障诊断,以提高模型的抗噪声能力;然后,使用不同扩张率的空洞卷积扩充了多尺度信息,并利用CNN模块来完成对特征的提取与故障诊断;同时,在模型中加入批量归一化处理操作,用来加快模型训练的收敛速度,提高了模型的性能;最后,利用美国凯斯西储大学轴承数据集和东南大学齿轮箱数据集对基于D-MDCNN的模型进行了实验验证,并将实验结果与采用其他深度学习模型所得的实验结果进行了对比分析。实验结果表明:在无噪声至4dB的噪声环境下,D-MDCNN在西储大学和东南大学两个数据集上均可取得99%的诊断准确率;相比于其他同类模型,基于D-MDCNN的模型具有更高的诊断准确率和抗噪声能力。研究结果表明:基于D-MDCNN的模型是一种有效的轴承故障诊断模型。

低信噪比叠前数据定量分析软件研发与应用

在野外地震采集项目中,地震数据的信噪比分析对激发井深、激发药量等施工参数的确定至关重要,并可指导后续野外生产。以往将信噪比定性分析作为地震资料数据的评价依据存在一定误差,故信噪比分析逐步由定性分析向定量分析方向发展。目前常用的地震采集商业软件信噪比定量分析功能欠缺,部分商业采集软件的信噪比分析模块可满足地形平缓、信噪比较高工区的使用需求,但对于复杂地区、低信噪比地区适应性较差。因此,为解决复杂地区、低信噪比地区的信噪比定量分析问题,本文对常用的信噪比分析方法原理及其适应性进行深入研究,根据不同方法原理研发了相应的算法模块。通过模型试算以及实际资料应用表明,该软件模块完善了针对低信噪比地区叠前数据的信噪比定量计算方法,针对不同地形地貌可优选适用的算法,弥补了采集软件相应功能的空白。

塔里木盆地沙漠区低信噪比地震资料静校正和去噪方法

针对塔里木沙漠地区低信噪比地震资料的特点,提出了一套适应沙漠地区低信噪比地震资料处理方法,主要解决了该区静校正、叠前去噪等问题。实际处理中见到了良好的效果。

准噶尔盆地低信噪比地震资料处理方法

新疆准噶尔盆地表层地震地质条件复杂,干扰严重,原始地震资料品质差,信噪比低,因此,消除各种干扰, 提高资料的信噪比是处理中的重要内容。为此,开展了有针对性的提高信噪比处理方法研究。首先进行数据分析,以确定合适的处理方法和处理参数,制定恰当的处理流程;针对资料中严重的静校正问题,采用了基准面静校正和交互初至波迭代静校正相结合的方法;针对资料中干扰类型多且严重这一特点,采用了多步、多域联合去噪的方法;针对资料的分辨率问题,采用了反褶积和子波处理技术;针对地下地质构造成像质量问题,采用了精细速度分析和高精度成像技术。实际资料处理结果表明,上述方法对消除干扰,提高资料的信噪比实用有效,剖面质量有了较大的提高,波组关系清楚,断点、尖灭点清晰,构造假象被消除。

复杂山地低信噪比地震资料处理方法

宜阳复杂山地地震资料的特点是静校正量大,信噪比低。针对该区的特点,在资料处理中采用建立全区统一浮动基准面与折射静校正方法解决静校正问题;运用叠前去噪技术、目标速度分析、DMO技术、优化迭代叠加技术、F-X域信号增强去噪技术,同时,优化处理流程,精选处理参数,取得了明显效果。

宽频带低轴比双圆极化频率复用天馈系统设计

分析了影响卫星数据地面接收系统交叉极化鉴别率的主要因素,提出了天馈系统的体系结构和设计方案。该方案已用于频率复用高码速率遥感卫星数据接收系统工程中,并成功实现了国内首颗双圆极化频率复用遥感卫星("资源三号"卫星,数据速率450Mbit/s×2)的数据接收。