基于高阶累积量的自适应IIR线谱增强器

将四阶累积量的递推算法推广到求正弦信号的四阶混合累积量，并提出了一种基于四阶混合累积量切片的自适应IIR结构的线谱增强器算法。该线谱增强器通过自适应前向线性预测法求得滤波器的系数，从而使带噪信号的线谱成份得到增强。仿真结果表明，在平稳或非平稳输入信号情况下，该算法从色噪声中提取正弦信号的能力优于基于二阶自相关函数的自适应IIR线谱增强器。     

基于时频特征的卷积神经网络跳频调制识别

针对人工设计特征表征能力不足,提取难度大的问题,提出基于卷积神经网络（CNN）的跳频信号调制方式识别系统. 该系统通过训练学习跳频信号时频图特征,将调制方式识别问题转化为图像识别问题. 采用组合时频变换方法对跳频信号进行时频变换得到二维时频图;经过自适应维纳滤波算法滤除背景噪声,提高系统抗噪性;采用连通域检测和双线性插值算法提取跳频信号每跳时频图,对时频图大小进行重置调整;将已处理的时频图输入到设计的11层卷积神经网络中进行训练学习,通过在输出层增加Softmax分类器,实现跳频调制方式分类识别. 仿真结果表明,该系统在信噪比为–4 dB条件下,对跳频信号BPSK、QPSK、8PSK、SDPSK、QASK、16QAM、32QAM和GMSK共8种调制方式的平均识别率达到92.54%.     

基于卡尔曼滤波的红外图像增强算法

针对红外图像中的非均匀性噪声的去除问题,提出基于卡尔曼滤波的红外图像去噪及增强算法.在Bayesian MAP框架下分析卡尔曼滤波器对去噪问题的适用性.由于成像电路内部温度上升和参数的细微变化,每个像元的固定模式噪声（FPN）在帧间缓慢变化.基于此点,建立暗帧的噪声模型.将卡尔曼滤波器作用于红外暗帧序列,估计出暗帧中每个像元的FPN水平.引入噪声影响因子（NIF）来评估FPN噪声对像元输出信号的影响.根据NIF自适应地选取每个像元的FPN噪声权重.实际带噪图像减去加权FPN噪声,即得到增强图像.将该算法应用于实拍红外图像,用平均灰度梯度（GMG）评估算法的性能.在目标区域,GMG下降了5.1%,说明算法在去噪的同时很好地保留了目标的边缘.而在平滑区域,GMG下降了85.5%.结果表明,该算法在去除非均匀性噪声,提高图像的对比度方面,取得较好的效果.     

基于扫频法的电声设备测试系统的设计与实现

介绍了无失真传输系统的频率响应特性,分析了基于扫频法测量系统频响的JH6170电声测试系统。该系统采用对数压缩电路和A/D转换电路相结合的方法,解决了SPL值在音频域内的动态范围很大的问题。该系统以可编程开关电容滤波器为中心,采用自适应滤波方法,自适应地跟踪输入信号的频率变化,对频率不固定的噪音和谐波干扰均有较强的抑制能力,一般情况下可以实现普通环境下扬声器频率响应的测量。     

Low Distortion Quick Response Noise Filter Realized with Average Peaks Method

The filter proposed in this paper is expected to reduce noise whose frequency is lower than higher order harmonics of real signals. It is based on the distributive characteristics of noise, and uses analog circuits to select the high peak and low peak of the input signal and applies their average in order to reduce random noise. So it has no cutoff frequency and higher order harmonics of real signals are remained. As a result, it gives an instant response to changes in input signals and retains the integrity of real signals. Furthermore, it has only a small phase delay. The simulation results of slew rate, phase delay and spectral analysis under MULTISIM indicate that the quick response noise filter achieves a high slew rate of 472 V/ms and the phase shift is nearly zero. By having it used in a color tester design, it is also demonstrated that the proposed filter effectively reduces noise and remains signal integrity. With the filter’s help, the relative standard deviation of the spectrograph decreases from 1% to 0.22%, indicating better stability.     

随机信号中值频率实时估计的研究

提出了一个在线实时估计中值频率的算法．这个算法是建立在通过控制采样频率实现截止频率可调的数字滤波器的基础上．为检验算法的有效性，文中给出了输入试验信号测试结果．     

基于实际无线局域网系统的信道估计算法

结合无线局域网(WLAN)系统进行适合实际系统的信道估计方法研究。针对实际系统在要求算法稳健性的同时,还要求算法简单易实现的特点,在最小二乘(Least Square,LS)算法中添加了离散傅里叶逆变换(Inverse Discrete Fourier Transform,IDFT)运算,利用信号在时域能量集中的特点,在时域对信号按门限值进行筛选,滤除大部分噪声,以此提高系统性能。仿真结果显示,改进算法可为实际WLAN系统所采用。     

基于中心频率检测的应答机载波捕获技术

针对基于理想型积分环路滤波器的二阶锁相环在无信号输入时,环路中心频率会随热噪声发生漂移的问题,研究了卫星星载测控应答机的载波捕获技术.为解决无信号输入下的环路中心频率漂移问题,在基于正交欠采样技术及全数字载波恢复环的接收机结构基础上,通过一级中心频率检测器控制环路.当检测到上行信号时闭合环路,避免了接收机中心频率在无信号输入时随热噪声发生漂移.给出了中心频率检测器的设计方法,分析了检测器漏检概率和误判概率之间的关系,并在此基础上给出了检测器的具体参数选择依据.     

基于新息的神经网络自适应卡尔曼滤波

卡尔曼滤波是一种基于最小方差的递推式滤波算法,系统模型和噪声统计特性的先验知识决定了滤波的性能和估计的准确性,不精确的先验知识将导致滤波性能的明显下降甚至发散。采用BP神经网络对系统进行辨识,获得精确的系统状态方程,利用新息自适应估计卡尔曼滤波算法中的过程噪声和测量噪声协方差矩阵,提出基于新息的神经网络自适应卡尔曼滤波算法。Matlab仿真结果表明,与传统卡尔曼滤波算法相比,改进的卡尔曼滤波算法获得了与原始信号几乎一致的输出信号,噪声得到明显抑制。同时,改进的算法不需要系统精确的数学模型,在实际应用中具有可行性和普适性。     

基于小波变换和复合混沌系统的数字图像水印算法

提出了一种基于小波变换和复合混沌系统的数字图像水印算法.在水印嵌入过程中,算法首先对原始图像进行离散小波变换,提取其低频部分作为嵌入区域;在对水印进行加密时,不是使用以往单混沌序列,而是采用复合混沌系统产生的混沌序列;再将加密后的水印进行小波变换并提取其低频部分;最后将加密水印的低频部分嵌入到原始图像的低频部分中.通过水印相关系数NC和峰值信噪比PSNR评价水印算法性能.实验结果表明,该算法可以抵抗JPEG压缩、噪声、滤波等攻击,图像水印效果很好.     

噪声野值下的学生t分布混合CPHD滤波

针对过程噪声和量测噪声野值导致高斯混合势概率假设密度滤波性能下降的问题,提出了一种基于学生t分布的势概率假设密度滤波。首先,引入学生t分布对重尾的过程噪声和量测噪声进行建模;其次,将多目标后验强度近似为学生t分布混合形式,推导了基于学生t分布的势概率假设密度滤波的闭合解,并采用矩匹配算法防止学生t分布的自由度无限增长。仿真结果表明,在含有过程噪声和量测噪声野值的环境下,所提算法的目标数估计精度和最优子模式分配距离优于高斯混合势概率假设密度滤波和学生t分布混合概率假设密度滤波,提高了多目标跟踪性能。     

Design of the satellite synchronized clock

This paper introduces a system for a new type of GPS/the Beidou locking second-class frequency standard of measuring time intervals based on the TDC-GP2 Chip. It also presents the overall design scheme for the system, develops the hardware and software frame, and implements the Kalman filter algorithm combined with the method of linear average for estimating and filtering noise. The universal TDC-GP2 produced by the ACAM company for measuring time interval of locked second-class frequency standard system is used by the satellite. By increasing another dividing frequency output signal 1PPS2, the measurement range is extended to -3.25～+3.25ms and the time resolution of 50ps is obtained. Experimental results show that the system's locked output frequency accuracy is as high as 10^-12(24-hour average). Frequency stability is better than 10^-11/s. Compared with the traditional frequency standard locked system, the system has the advantages of simple circuit, convenient adjustment, wide measurement range, small additional noise, and high precision.     

非平稳时变随机噪声的数字滤波器设计与仿真

非平稳噪声的统计参数是时变的,频率滤波器不能实现对它的抑制,传统的自适应抵消器方法是基于最小均方误差准则(LMS)实现滤波的。针对LMS自适应算法中的固定步长导致收敛速度慢、失调量大的缺点,提出了变步长方法。采用最小二乘准则(LS),根据输入信号信噪比的变化来调整步长,并对滤波器的收敛速度、滤波性能进行了数据仿真,验证了该算法的有效性,实现了对时变非平稳噪声的有效抑制。     

Algorithm for extraction of features of robot speech control in the factory environment

In the real working environment,the mobile robots have a poor recognition performance to speech control commands due to the noise effect. Aiming at this issue,this paper proposes a new algorithm based on the gammatone frequency cepstral coefficient and the mixed feature extraction of the Teager energy operator. This algorithm replaces the common Mel filter with the Gammatone filter. In the process of extracting gammatone frequency cepstral coefficients,the Teager energy operator reflecting the energy of speech signal is added to form a new feature, with the dynamic characteristics of the speech signal considered. It is combined with the first-order difference parameters to form a mixed feature. And the principal component analysis is made to reduce the dimension,and the final mixed features are used to the speech recognition system for control command of the mobile robot. Experimental results show that,in the environment of the workshop noise and signal-to-noise ratio of 10dB,the recognition rate of mixed features is improved by 12.20% compared with the mel frequency cepstrum coefficient. The recognition rate of the mixed feature is increased by 1.02% when the dimension is reduced by principal component analysis.     

基于Laguerre变换的线性调频信号检测

提出了一种基于Laguerre变换的线性调频信号检测新方法，通过恰当设定Laguerre参数，能够对消线性调频信号的频率变化，得到一个近似周期的信号。由于线性调频信号的能量集中到一条谱线(frequency bin)上，因此能在低信噪比下实现有效检测，仿真实验证明了这种方法的有效性。     

基于LabVIEW的IIR数字滤波器的设计

详细介绍了基于LabVIEW虚拟滤波器的设计原理和开发过程.并以巴特沃斯低通滤波器为实例,用LabVIEW软件模拟产生一个接近实际信号并带噪声的虚拟信号,可根据实验的需求调整参数,并通过仪器的前面板来显示滤波前后的时域波形.     

多芯片小数分频锁相环输出信号相位同步设计

为了在多通道射频（RF）通信系统中,实现多个收发器芯片或单个收发器芯片上的锁相环（PLL）相位同步,提出小数分频PLL输出信号相位同步算法. 设计相位累加采样点数选取算法,算法选取的采样点数用于累加参考时钟欠采样的PLL输出信号与数控振荡器（NCO）产生的参考信号经三角运算的结果,以消除高次谐波分量,并有效降低相位差计算结果的误差. 根据相位差的计算结果反馈调节PLL内 delta-sigma 调制器(DSM)输入的小数分频比,线性调整PLL输出信号的相位,实现多个PLL输出信号相位与参考信号相位同步. 通过仿真验证算法的正确性,且最终相位同步后的相位误差为0.35°,完成同步所需的时间为210 ms.     

Noise filtering and subdivision precision analysis of Moiréfringe

The subdivision precision of MoiréFringe is restricted by its quality. In this paper, the adaptive filtering algorithm based on the neural network is used to restrain noise of MoiréFringe.The nonlinear mapping fuction is achieved by using the neural network layer. The step size of the algorithm can be adjusted dynamicly according to the signal’s frequency to meet the filtering request of the signal with a diversified frequency and make the algorithm self-adaptive.On subdividing filtered circle grating MoiréFringe signals by means of the tangent method by 512 times, it is shown that the distinguishment is 0.618″, that the maximal cumulate error is 1.236″, and that the signal quality and the subdivision precision are greatly improved.Because of its wide bandwidth and restraint of linear and nonlinear noises, the algorithm is better than general filtering way and can satisfy the preparation for the subdivision of MoiréFringe.     

Digital Demodulation Algorithm for Multi-Tone FM Signal in New Type Track Circuit

High speedrailwaysystemsarerapidlydevel opedinmanycountriesaroundtheworldinthis decade.Whenrunningwiththespeedhigherthan200km/h,therailwaycommunicationandcontrol systemsbetweenthewaysideandthetrainsaremore importantthanbefore.Forsecurityandefficiency reason,newcommunicationandcontrolsystems shouldbedevelopedtosupportautomatictrainprotec tion[1](ATP)andautomatictraincontrol[2](ATC).Thetrackcircuitisoneofthemostimportant componentsinhigh speedrailwaycontrolandcom municationsystem[3].Recently,…     

四轮移动机器人轨迹跟踪的最优状态反馈控制

对具有量测噪声、模型噪声和输入信号干扰的四轮移动机器人轨迹跟踪的最优状态反馈控制进行研究.建立系统的运动学与动力学方程和轨迹生成方程,导出了相应的离散状态方程式,采用卡尔曼滤波器对伴有高斯白噪声的系统状态方程进行了状态估计,提出一种基于李亚普诺夫稳定性的最优状态反馈控制策略.给出了补偿输入信号干扰的自适应算法.仿真结果表明,所提出的控制算法,在四轮移动机器人轨迹跟踪中,能有效地抑制系统的模型、量测和输入信号中的随机噪声和扰动,提高系统的跟踪精度和动态响应速度,使系统具有优良的静、动态特性．