基于数字鉴相的自由轴法RLC测量

针对自由轴法RLC测量中因使用模拟鉴相器导致测量精度低的问题,提出采用一种基于数字鉴相的测量方法.基准相位发生器与信号源使用同一频率,通过编程控制使基准相位发生器产生两个正交的相位参考基准信号,应用乘法型D/A对被测信号与相位参考基准信号进行数字鉴相,获得了被测阻抗电压及标准阻抗电压在正交坐标轴上的投影分量.分析与计算表明了该方法的准确性.这种方法比基于模拟鉴相的自由轴法RLC测量的精度高,测量的速度快.     

一种使用双棱镜的动态小角度测量方法

提出一种基于正切关系和相位调制技术的动态小角度测量方法.使用双棱镜组成干涉测量臂引导两束平行光至分束棱镜处干涉,通过提取携带被测信息的干涉信号的相位实现动态的小角度测量.由于采用位置探测器(PSD)对测量臂中两平行光束的间距进行测量,简化了测量方程,消除了装置中双棱镜必须对称放置的要求.通过正弦地改变半导体激光器的注入电流在时域内实现对干涉信号的相位调制,形成准外差干涉测量模式,提高了光程差的测量精度.实验验证了该方法的可行性,并讨论了影响小角度测量精度的误差因素.研究结果表明,基于该方法的动态小角度的重复测量精度可达到10-8rad数量级.     

基于全相位频谱分析的相位差频谱校正法

为精确估计噪声背景下正弦信号频率、幅值、初始相位的真实值,结合全相位FFT与传统FFT谱分析形成了一种新的相位差频谱校正法.该法计算复杂度低,方便快捷.由两种主谱线上的谱分析结果经过简单运算即可校正出频率和幅值,而直接取主谱线上的全相位FFT相位谱值无需校正即可得到初始相位.由于全相位FFT具有抑制频谱泄漏的优良特性,因此该法适合于密集频率分布场合.该法相位估计误差非常低,无噪时处于10-7分辨率级.     

一种利用Duffing-Vanderpol振子估计弱信号相位的方法

根据Duffing-Vanderpol振子大周期态时的最大Lyapunov指数与系统策动力的关系,提出了一种基于该振子检测微弱信号相位参量的方法.该方法利用系统策动力与待测信号初始相位有关的特性,得到待测信号的初始相位,并将相位检测过程中噪声对系统的影响作为影响因子加以考虑.理论分析及数值仿真结果表明,该方法工程实现简单,抗噪性能好.当待测信号信噪比为-30 dB时,均方误差仅为0.1,具有较高的估计精度.     

消除光强调制影响的双波长正弦相位调制干涉仪

在双波长半导体激光(LD)正弦相位调制(SPM)干涉仪中,通过注入电流调制LD波长的同时,光源的输出光强也被调制,影响了测量精度。提出了一种新的双波长LD SPM干涉仪,通过对干涉信号进行处理,得到与干涉信号相位相关的线性方程组,利用该方程组精确计算相位,消除了光源光强调制的影响,使测量误差由6μm减小至1μm,并利用该干涉仪与波长扫描技术相结合实现了绝对距离的测量,当待测距离为60~280 mm时,测量结果的重复性为1μm。     

基于CAD光相位模型的数字全息检测方法研究

针对数字全息的精密机械结构三维检测中相位的跃变,在分析相位包裹产生的机理基础上,提出一种建立被测物体计算机三维辅助设计(3D-CAD)的光相位模型并进行解包裹的方法。将3D-CAD模型点云化处理,构建相位分布测量模型,获取被测物的相位图;通过搭建的双波长数字全息实验系统,拍摄被测物体的全息相位图并与模型的相位图进行初始对准和位置精确对准,计算全息图的包裹相位所对应的真实差值,获得全息测量的解包裹相位。仿真和实验分别采用不同表面形貌的被测物体,结果表明该方法对于精密结构的检测非常有效。     

基于Michelson干涉解调技术的光纤光栅传感系统

介绍了一种基于Michelson干涉解调技术的光纤光栅传感系统,将包含被测应变信息的FBG波长信号转变成相位信号,通过单片机系统检测相位的变化,得到被测应变的大小.系统可检测静态应变和动态应变,具有高分辨力、大测量范围等特点.     

基于Lab VIEW的FBG传感解调技术的研究

结合虚拟仪器技术和光纤光栅传感技术,自行设计了一套光纤光栅传感解调系统.系统采用了基于迈克尔逊干涉技术的解调方法,将包含被测应变信息的光纤布喇格光栅(FBG)波长信号转变成相位信号,通过以Lab VIEW为核心的虚拟仪器系统检测相位的变化,从而得到被测应变的大小.该干涉解调系统避开了传统解调系统受电磁干扰和环境等方面的影响,因此使测量精度提高.虚拟仪器系统可用于静态应变和动态应变的检测,具有高分辨力、大测量范围的特点.     

双频雷达测高技术研究

该文针对双频雷达的测高问题,研究了基于相位干涉原理的双频雷达测高方法.文中给出了相位干涉测角的基本原理,并针对该方法在双频雷达测高应用中存在的相位模糊问题进行了分析,在此基础上,给出了基于中国余数定理的双波段相位差解模糊处理方法,解决了双频雷达相位干涉测高法的相位模糊问题.最后对双频雷达相位干涉测高法的测高精度进行了分析.仿真分析,验证了算法的可行性.     

基于希尔伯特-黄变换的多项式相位信号检测

本文运用适合非线性非平稳信号分析的希尔伯特-黄变换,通过对含噪多项式相位信号进行经验模式分解和Hilbert谱分析,采用曲线拟合和最小二乘迭代方法,准确地估计出单一幅度恒定的多项式相位信号,从而提出了一个适合非线性非平稳信号的检测方法.仿真结果表明该方法在信噪比>10dB情况下能够准确有效地检测出非平稳信号,与基于Wigner-Ville分布的信号检测方法相比,具有更好的准确性和有效性.     

基于全相位的零相位数字滤波器的设计方法

针对通常情况下滤波器引起的相移问题,概述零相位数字滤波的重要意义.并在介绍传统两利零相位数字滤波器设计(FRR和RRF)原理和方法的基础上,提出了一种新的零相位数字滤波器的设计原理和方法——全相位方法.通过仿真实验将传统的两种设计方法与此新设计方法给予了验证,使数字信号处理中滤波器引起的相位失真问题得到很好的解决.说明全相位方法是一种很好的零相位数字滤波器的设计方法,同时还克服了传统设计方法物理上无法实现的弊端.最后,将此全相位方法与传统方法作了分析,并介绍了全相位作为一种全新数字滤波器设计方法的应用领域.     

Improved phase estimation based on complete bispectrum and modified group delay

In this paper, a new method for extracting the system phase from the bispectrum of the system output has been proposed. This is based on the complete bispectral data computed in the frequency domain and modified group delay. The frequency domain bispectrum computation improves the frequency resolution and the modified group delay reduces the variance preserving the frequency resolution. The use of full bispectral data also reduces the variance as it is used for averaging. For the proposed method at a signal to noise ratio of 5dB, the reduction in root mean square error is in the range of 1.5–7 times over the other methods considered.     

基于分数低阶统计量的双谱及其估计方法

稳定分布可更好地描述实际中所遇到的具有显著脉冲特性的随机噪声.为了更好地抑制信号背景中的非高斯噪声,本文提出了基于分数低阶的双谱定义,并给出在分数低阶有色噪声背景下双谱非参数和参数模型的估计方法.仿真结果表明,同传统的双谱估计相比较,非参数法分数低阶双谱估计能有效的识别信号,保留了信号的幅度和相位信息,但存在较大的估计方差.基于AR模型的分数低阶双谱估计具有最大的谱平坦度,能够有效地抑制噪声,具有良好的韧性.     

基于双谱理论的雷达辐射源指纹特征提取

针对雷达辐射源指纹特征提取困难的问题,提出了基于双谱切片法和双谱围线积分法,提取辐射源指纹特征的方法。介绍了二相编码信号的无意调制,仿真了理想情况和含有相位噪声的二相编码信号的时域波形。阐述了含相位噪声雷达信号的双谱估计,仿真了含相位噪声的二相编码信号的双谱图及等高图。最后利用双谱切片法和双谱围线积分法,提取了辐射源的指纹特征,通过计算机仿真实验验证了该方法的可实施性。     

Detection of quadratic phase coupling from human EEG signals using higher order statistics and spectra

Interactions among neural signals in different frequency components have become a focus of strong interest in biomedical signal processing. The bispectrum is a method to detect the presence of quadratic phase coupling (QPC) between different frequency bands in a signal. The traditional way to quantify phase coupling is by means of the bicoherence index (BCI), which is essentially a normalized bispectrum. The main disadvantage of the BCI is that the determination of significant QPC becomes compromised with noise. To mitigate this problem, a statistical approach that combines the bispectrum with an improved surrogate data method to determine the statistical significance of the phase coupling is introduced. The method was first tested on two simulation examples. It was then applied to the human EEG signal that has been recorded from the scalp using international 10–20 electrodes system. The frequency domain method, based on normalized spectrum and bispectrum, describes frequency interactions associated with nonlinearities occurring in the observed EEG.     

一种新的雷达辐射源信号识别方法研究

随着雷达技术的发展,雷达体制的多样性和雷达信号的复杂性对雷达辐射源信号识别技术提出了严峻的挑战.循环双谱抗噪性能强,且包含了丰富的信息,能用于识别雷达辐射源信号.但是其数据量庞大,而循环双谱对角切片法丢失了大部分信息.证明了循环双谱的对称性和周期性,提出了局部轴向积分循环双谱.该方法首先计算信号的循环双谱,然后在两个谱频率构成的平面上沿平行于谱频率轴的直线积分,最后用Fisher判决率(FDR)选择鉴别能力较强的轴向积分循环双谱.这样不但能有效地减小数据量,而且保留了大部分有用的循环双谱信息.仿真条件下,对比分析了局部轴向积分循环双谱与循环双谱对角切片的识别效果,结果表明新方法的识别率远远优于循环双谱对角切片法.     

Improved bispectrum estimation based on modified group delay

This article proposes an improved estimation method for the bispectrum of a system or signal, by applying the modified group delay (MMGD) in the bispectrum domain. To achieve a higher frequency resolution, the bispectrum is computed in frequency domain and further to reduce the variance preserving the frequency resolution, MMGD is applied in the bispectrum domain. The proposed method due to its better frequency resolution not only properly detects the phase coupled frequencies but also reduces the bispectrum magnitude estimate’s variance significantly compared to that of biperiodogram. Compared to the proposed method, though the windowed bispectrum (WB) provides a better reduction in variance, it is unable to detect the coupled frequencies due to its poor frequency resolution. For an AR process in the presence of noise (SNR = 4 dB), the system magnitude estimate by the proposed method has a 27.63% lower normalized sum sample mean square error (NSSMSE) than that by the WB. Also for a non-minimum phase system in presence of noise (SNR = 7 dB), the phase estimation by the new approach has 8.6% lower NSSMSE than that by WB and also it is marginally better than that obtained by applying MMGD in system group delay domain.     

Time delay estimation using the cross bispectrum

The cross bispectrum phase can be effectively used to estimate the time required for a nonGaussian signal to propagate between a pair of spatially separated sensors in the presence of highly correlated Gaussian noise. The authors present a consistent estimator of the phase of the cross bispectrum, derive the exact distribution of the phase of a complex Gaussian sample bispectrum, and show that in most cases the exact distribution can be approximated by a Gaussian distribution. Using this Gaussian approximation, the authors derive the variance of the time delay estimate computed from the sample cross bispectrum of a signal in additive correlated noise. These results allow the performance of time delay estimators based on the cross bispectrum phase to be quantified as a function of the sample size, the skewness of the signal, the signal-to-noise ratio (SNR), and the noise correlation     

Signal reconstruction from the phase of the bispectrum

The authors present a simple procedure, the bispectrum signal reconstruction (BSR) algorithm, to recover the Fourier phase of a signal from the phase of its bispectrum. By simple analogy, a procedure that recovers the Fourier magnitude of a signal from the magnitude of its bispectrum is also presented. In addition, the authors propose an iterative scheme, the bicepstrum iterative reconstruction algorithm (BIRA), for the reconstruction of a finite impulse response (FIR) sequence from only the phase of its bispectrum, and they demonstrate how some a priori information on the energy of the cepstra coefficients can improve significantly the convergence rate of the algorithm. Both schemes are based on the key observation that the differences of the bispectrum coefficients contain all the information concerning the Fourier phase of the signal, whereas their sums contain the Fourier-magnitude information     

Statistical approach to quantify the presence of phase coupling using the bispectrum

The bispectrum is a method to detect the presence of phase coupling between different components in a signal. The traditional way to quantify phase coupling is by means of the bicoherence index, which is essentially a normalized bispectrum. The major drawback of the bicoherence index (BCI) is that determination of significant phase coupling becomes compromised with noise and low coupling strength. To overcome this limitation, a statistical approach that combines the bispectrum with a surrogate data method to determine the statistical significance of the phase coupling is introduced. Our method does not rely on the use of the BCI, where the normalization procedure of the BCI is the major culprit in its poor specificity. We demonstrate the accuracy of the proposed approach using simulation examples that are designed to test its robustness against noise contamination as well as varying levels of phase coupling. Our results show that the proposed approach outperforms the bicoherence index in both sensitivity and specificity and provides an unbiased and statistical approach to determining the presence of quadratic phase coupling. Application of this new method to renal hemodynamic data was applied to renal stop flow pressure data obtained from normotensive (N = 7) and hypertensive (N = 7) rats. We found significant nonlinear interactions in both strains of rats with a greater magnitude of coupling and smaller number of interaction peaks in normotensive rats than hypertensive rats.