Modeling random telegraph signal noise in CMOS image sensor under low light based on binomial distribution

The random telegraph signal noise in the pixel source follower MOSFET is the principle component of the noise in the CMOS image sensor under low light. In this paper, the physical and statistical model of the random telegraph signal noise in the pixel source follower based on the binomial distribution is set up. The number of electrons captured or released by the oxide traps in the unit time is described as the random variables which obey the binomial distribution. As a result,the output states and the corresponding probabilities of the first and the second samples of the correlated double sampling circuit are acquired. The standard deviation of the output states after the correlated double sampling circuit can be obtained accordingly. In the simulation section, one hundred thousand samples of the source follower MOSFET have been simulated,and the simulation results show that the proposed model has the similar statistical characteristics with the existing models under the effect of the channel length and the density of the oxide trap. Moreover, the noise histogram of the proposed model has been evaluated at different environmental temperatures.

A Novel 2-D Signal Processing Scheme for Quasi-Random Step Frequency Signal

Due to the heavy congestion in HF bands, HF radars are restricted to operating within narrow frequency bands. To improve the system bandwidth and avoid heavy interference bands, a quasi-random step frequency signal with discontinuous bands is presented. A novel two-dimensional signal processing scheme for this signal is proposed on the basis of delicate signal analysis. Simulation results demonstrate that the scheme could successfully realize the resolutions by decoupling the range-Doppler ambiguity, and effectively suppress the maximal sidelobe. Moreover, the scheme is simple and has good numerical stability.

Analysis of random laser scattering pulse signals with lognormal distribution

The statistical distribution of natural phenomena is of great significance in studying the laws of nature. In order to study the statistical characteristics of a random pulse signal, a random process model is proposed theoretically for better studying of the random law of measured results. Moreover, a simple random pulse signal generation and testing system is designed for studying the counting distributions of three typical objects including particles suspended in the air, standard particles, and background noise. Both normal and lognormal distribution fittings are used for analyzing the experimental results and testified by chi-square distribution fit test and correlation coefficient for comparison. In addition, the statistical laws of three typical objects and the relations between them are discussed in detail. The relation is also the non-integral dimension fractal relation of statistical distributions of different random laser scattering pulse signal groups.

Measuring the Qatar-Kazeron Fault Dip Using Random Finite Fault Simulation of September 27, 2010 Kazeron Earthquake and Analytical Signal Map of Satellite Magnetic Data

In this research the fault parameters causing the September 27, 2010 Kazeron Earthquake with a magnitude of MW = 5.8 (BHRC) were determined using the random finite fault method. The parameters were recorded by 27 accelerometer stations. Simulation of strong ground motion is very useful for areas about which little information and data are available. Considering the distribution of earthquake records and the existing relationships, for the fault plane causing the September 27, 2010 Kazeron Earthquake the length of the fault along the strike direction and the width of the fault along the dip direction were determined to be 10 km and 7 km, respectively. Moreover, 10 elements were assumed along the length and 7 were assumed along the width of the plane. Research results indicated that the epicenter of the earthquake had a geographic coordination of 29.88N - 51.77E, which complied with the results reported by the Institute of Geophysics Tehran University (IGTU). In addition, the strike and dip measured for the fault causing the Kazeron Earthquake were 27 and 50 degrees, respectively. Therefore, the causing fault was almost parallel to and coincident with the fault. There are magnetic discontinuities on the analytical signal map with a north-south strike followed by a northwest-southeast strike. The discontinuities are consistent with the trend of Kazeron fault but are several kilometers away from it. Therefore, they show the fault depth at a distance of 12 km from the fault surface.

Filtering noisy chaotic signal via sparse representation based on random frame dictionary

The denoising problem of impure chaotic signals is addressed in this paper. A method based on sparse representation is proposed, in which the random frame dictionary is generated by a chaotic random search algorithm. The numerical simulation shows the proposed algorithm outperforms those recently reported alternative denoising methods.

高阶伪随机信号在对地通讯中的应用

对地通讯(Through-The-Earth Communication,TTEC)以大地为传播介质,使用低频电磁波来传输信息,在地下工程建设调度、预警、救援中有着重要作用.高阶伪随机信号可同时包含数十个频率,其具有易于实现、频率可控、抗干扰能力强的特点,有应用于对地通讯的潜力和价值.鉴于此,本文提出一种基于高阶伪随机信号的对地通讯新方法.通过在高阶伪随机信号中设置静态频组和动态频组,利用静态频组保证多个主频的平均幅值以维持发射稳定性,利用动态频组对通讯信息编码,传输有效信息.在实际工作时,发射端将通讯信息编码转换为高阶伪随机信号,利用长导线源向大地发射,接收端利用电极或者线圈接收电磁信号,经模式识别、时频变换、反向解码转换为有效通讯信息.通过仿真测试和在济南市某煤矿井下试验,完成有效通讯信息的发射、传输、解译等过程,实现了基于高阶伪随机信号的对地通讯方法,验证了方法在地下工程通讯的可行性和可靠性.

连续振动载荷在线复现控制技术研究

提出一种主从分布式振动试验方法,建立了连续振动载荷在线复现控制技术,研制了系统样机。其中,提出一种信号分帧处理与重构技术,解决了长时连续振动载荷的在线波形复现难题;提出一种基于多量级样本库构建与加权平均的传递函数动态估计方法,抑制了系统非线性对控制精度的影响;采用谱误差反馈修正方法,改善了系统的频域控制精度。开展了“1主2从”联台试验,结果表明:时域和频域控制精度良好,整体延迟时间在亚秒量级,全程总均方根值误差在1%以内,为主从分布式振动试验提供了关键技术支撑。

“随机信号分析”课程中相关特性的实验设计

探索了“新工科”背景下“随机信号分析”课程的实验设计。以雷达应用为背景,结合科研项目中的实际问题和解决方法设计了三个随机过程相关特性方面的实验,给出了应用背景、原理分析和实验设计。通过该实验教学,使学生深刻体会所学理论、方法在实际中是如何应用的,如何分析和解决实际的工程问题,激发了学生的学习兴趣,培养了学生的创新意识和创新能力。

“随机信号分析”课程思政教学案例设计

针对“随机信号分析”课程内容抽象难懂、理论推导繁琐,思政教育元素与课程内容的融合难度大等问题,探讨了课程思政教学案例的设计原则、基本要求,并通过一个完整的教学案例研究了“随机信号分析”课程的思政案例教学法的设计思路和具体应用。通过教学实践发现,热点问题的思政案例能够激发学生学习的热情和兴趣,提高教学质量。

基于特征值的动态数字信道化子带检测算法

动态数字信道化接收结构通过检测所有子带,判断信号是否存在,为综合滤波器组处理提供依据,因此子带检测在接收结构中起着关键作用。针对传统检测算法存在低信噪比(signal-to-noise ratio,SNR)下检测性能不高的问题,依据随机矩阵理论,提出了基于最大最小特征值之差与平均特征值之比的检测算法,利用平均特征值和最小特征值的极限分布规律来推导算法的检测门限。其次,根据所有子带数据获取的特征值信息对所提算法进行了优化。最后,在动态数字信道化接收结构中,分析不同因素下算法的性能,表明了所提算法能够克服低SNR的影响,子带检测的性能更好。

基于改进随机森林的高光谱激光雷达信号分选研究

高光谱激光雷达数据在频谱维度上具有很高的维度,包含大量的波段或频带,易出现忽视频谱带中有用信息的情况,进而导致高光谱激光雷达信号分选效果较差。为此,提出基于改进随机森林的高光谱激光雷达信号分选研究。首先,采用变分模态分解算法对高光谱激光雷达含噪信号展开去噪处理;然后,采用长短期记忆神经网络算法对去噪后的高光谱激光雷达信号展开特征提取,并利用自编码神经网络对提取的特征展开重构处理,以获取重构后的雷达信号特征;最后,采用随机森林算法根据高光谱激光雷达信号特征完成信号分选。实验结果表明,所提方法的SNR为30.648 dB,RMSE为0.1498,预测分选类别与实际分选类别几乎一致,分析时间始终未超过5 s,表明所提方法的分选性能较好,具有实用性。

基于深度残差网络的机床减速器故障诊断研究

为了进一步提高对机床不同故障的分类准确率,设计了一种深度残差网络。通过对机床振动试验台信号预处理优化网络结果,并进行故障诊断对比分析。研究结果表明:当行数比列数更少时,随着两者差异增加,模型分类准确率显著降低;当行数超过列数后,模型达到了更高的分类准确率并保持相对稳定的状态。CNN网络比浅层模型LeNet表现出了更强识别性能。ShortCut结构具备明显优越性,有助于网络具备更强识别能力。该研究有助于提高减速器的运行效率,可将其拓宽到其他机械传动领域,具有很好的应用价值。

金刚石滚轮轮廓圆度误差在线判别

金刚石滚轮形面的修形技术是制造金刚石滚轮的关键技术之一,常采用金刚石砂轮磨削法对其进行精密修形,修形后的轮廓圆度误差是考量滚轮修形合格与否的重要指标。目前的轮廓圆度检测方法是人工停机取下滚轮并放置于轮廓仪上进行,极大地增加了滚轮制作的时间和成本。为此,对在五轴加工机床上的金刚石滚轮,沿其轮廓面横向磨削修形时产生的振动信号,提出基于小波包系数和随机森林的在线检测方法并对其轮廓修形状态进行识别,在修形进行状态时的识别准确率为93.3%,具有实际应用价值。

外部随机激励干扰下掘进机振动信号多传感采集方法

掘进机运行过程中,在外部随机激励源的作用下,造成多传感器模式下的传感敏感性波动,结合振动信号不稳定,会导致采集的振动信号大幅度失真。为保证掘进机的稳定运行,提出多传感器模式下的随机激励振动信号采集方法。将掘进机看作多自由度系统,建立设备动力学模型;结合掘进机动力学特征,利用虚拟激励法构建符合外部源的随机激励函数;在建立的随机激励下,选择传感器类型和参数并安装多个传感器,设定采样频率;根据正弦稳态校准方法需求,设计校准传感器采集系统,提高传感器敏感性;在随机激励函数约束下预测传感器输出延时,计算每次测量的同步误差和误差补偿值,通过补偿确保多传感器实现振动信号的同步动态采集。实验结果表明:在多传感模式下,这种方法降低了外部的随机迟滞干扰,在随机激励作用下采集到的掘进机多传感振动信号波形与实际波形相符。

基于随机森林法的铣刀磨损状态监测

针对机床加工过程中铣削刀具状态监测困难,以及单传感器监测法存在信息不全的问题,提出了一种利用随机森林完成多传感器信息融合的刀具磨损状态监测研究方法。在不同的切削参数下,以声发射传感器和振动传感器为信号采集元件,多方位采集信号,并对信号进行时域、频域、小波包分析,提取其对刀具状态敏感的共计23个特征量,构建随机森林模型对铣刀状态进行监测。实验结果表明,该研究方法识别刀具准确率达90.0%,具有可行性。

超短基线在低频基阵指向性测量中的应用

随着水声换能器工作频率的降低,实验室空间很难达到自由场和远场测量的要求。而开阔水域的水下环境复杂,基阵很难实现更深层次的吊放,需要安装价格昂贵的吊装平台来获取标准声源与待测基阵之间的相对位姿,效率低且维护成本高。文章采用超短基线定位技术,信号选用线性调频脉冲信号与伪随机编码脉冲信号,并分别基于脉冲压缩法和复相关算法实现距离和相位测量。比对湖上定位精度试验和基阵指向性标定静态试验的结果显示:角度误差为2.5°以内;-6 dB波束宽度在2~10 kHz频率范围内测量误差在5.38%以内。证明超短基线定位在低频基阵指向性标定的可行性。

基于表面肌电信号的上肢康复机器人变阻抗控制技术研究

我国老龄人群肢体障碍者很多,运动康复技术是康复治疗的有效手段。但医患比例严重失调难以使得人人都能享受到康复医疗服务。康复机器人通过阻抗控制技术能够与人体进行一定的安全交互,但现有康复机器人多采用定阻抗控制,环境适应能力弱,难以应用于临床。针对上述问题,提出一种变阻抗控制方法,以采集使用者的表面肌电信号为输入条件,通过改进随机森林算法训练识别使用者上肢的运动角度。并配合末端力传感器,获得使用者的运动意图,再通过变阻抗控制器完成康复运动。搭建了实验平台,并对轨迹跟踪和康复训练能力进行验证与评估。结果表明所设计的控制器能够控制机器人完成康复运动。

北斗卫星船载导航信号并行捕获算法

信号捕获作为实现北斗卫星船载导航的第一阶段,也是最重要的一环,为此研究基于北斗卫星船载导航信号并行捕获算法,在短时间内捕获卫星信号,为船舶提供高精度的定位和导航服务。建立北斗卫星导航信号模型,依据模型生成的北斗卫星导航信号,采用傅里叶变换(Fast Fourier Transformation,FFT)算法以及快速傅里叶逆变换(Inverse Fast Fourier Transform,IFFT)算法,通过并行频率搜索和并行码相位搜索分别将伪随机码相位、载波频移的二维搜索变成一维进行并行搜索,获取北斗卫星信号的伪随机码和载波频移,实现北斗卫星船载导航信号并行捕获。实验结果表明,该算法可以成功地捕获船载导航信号,并且捕获耗时短;对船载导航信号的载波频率估计误差小。

低成本接收阵列方向图测试系统与方法

采用传统的相控阵测试方法对数字阵列及数字波束合成进行测试,存在系统复杂、设备齐套周期长、问题难解耦等弊端。因此,对于数字阵列及相关算法,需要一种不依赖天线和物理环境,且能够以低成本和高效率,在系统开发中期完成相关性能评估和迭代的方法。给出一种基于阵列信号模拟技术的低成本接收阵列方向图测试系统,并提出了随机虚拟相移技术用于解决测试精度不足的问题。基于简要的理论分析、给出了测试平台构成和测试流程,并通过仿真和实测验证了方法的有效性。

基于轻量化RF算法的高阶QAM信号OSNR估计方法

针对光信噪比(OSNR)估计复杂度高、计算量大的问题,提出了一种基于轻量化随机森林(RF)算法的高阶正交幅度调制(QAM)信号OSNR估计方法。该方法通过将不同OSNR的高阶QAM信号映射为不同的星座图数据集,并利用这些数据集来训练RF模型,从而实现OSNR的快速估计。仿真结果表明:采用基于轻量化RF算法估计64QAM和128QAM信号的OSNR,在系统OSNR真实值为5~30 d B时,2种调制格式的OSNR估计准确率均接近100%;64QAM信号OSNR估计值的平均绝对误差(MAE)为0.08 d B,128QAM的MAE为0.12 d B,比基于长短期记忆(LSTM)算法的信号OSNR估计结果更准确。