用于圆形口径光学元件的功率谱密度检测

光学元件加工质量的检测和评价是保证整个光学系统安全、正常运行的关键.波前功率谱密度(Power Spectral Density,PSD)能给出光学表面的空间频谱分布,反映高精度光学元件加工质量的特殊要求.在总结现有功率谱密度指标基础上,提出由于圆形口径的旋转对称性,可以采用径向波前功率谱密度来表征圆形口径光学元件波前频谱分布特征的方法,并给出了采用三坐标仪作为测试仪器测量圆形口径光学元件的波前功率谱密度时相应的数值计算方法.     

基于功率谱AR模型估计的序列图像复原算法研究

在分析信号复原过程的基础上,提出基于功率谱AR模型估计的序列图像复原算法.对分段信号的功率谱进行估计,在保持图像整体信息良好的前提下,得到幅值谱的补偿滤波器,从而实现序列图像复原.利用所建模型对风洞试验图像进行实验研究,复原图像信噪比得到提高,复原以后的图像误差得到很大程度的减小,恢复效果明显.研究表明,采用功率谱AR模型估计的复原方法,可以有效地应用于气动光学效应序列图像复原.     

小波在基于功率谱密度特征曲线评价中的应用

为了解决功率谱密度仅仅是一种强激光条件下光学元件表面质量评价指标,无法对通过加工来消除某频段误差进行确定性指导这一问题,采用小波理论对光学元件表面误差进行了分析和试验验证,在利用功率谱密度特征曲线找到表面误差不合格频率带的基础上,利用二维连续小波变换得到了能作为加工过程反馈的不合格频率带的对应区域.结果表明,利用此方法能有效地找到特定误差频段对应的区域,从而指导加工,提高加工的效率.     

部分响应信号功率谱密度的计算

提出了一个基于维纳－辛钦定理的求部分响应功率谱密度的有效方法，分析了部分响应信号功率谱密度对于信号传输特性的影响。     

激光波前功率谱密度与焦斑旁瓣的关系

基于波前功率谱密度(PSD)的定义,分析了采用功率谱密度方法研究中频波前畸变与焦斑旁瓣关系的可行性。由于任意形状的波前畸变都可以由不同空间频率的正弦函数叠加组成,以正弦函数波前为例进行功率谱密度分析和远场分析。分析表明,当中频波前畸变的幅度满足一定条件时,远场二级以上的衍射非常低,可以忽略不计,此时波前功率谱密度与焦斑旁瓣具有非常好的相似性,并且这种相似性仅与中频波前畸变的幅度有关,与空间频率无关。最后还用数值模拟的方法验证了这个结论对叠加后的结果仍然成立。研究结果可以用于设计满足惯性约束聚变(ICF)驱动器打靶对焦斑旁瓣要求的光学元件中频段波前畸变指标。     

信号功率谱密度的物理基础

借助于信号对简谐振子和简谐振子阵列的作用,定义了信号的瞬时能量谱密度,进一步引入了信号的瞬时能量、功率谱密度、功率、能量谱密度及总能量等基本物理量,给出了功率谱密度的主要性质以及功率谱密度与其它各物理量之间的关系。     

PCC-OFDM功率谱密度及系统性能分析

针对多项式相消编码正交频分复用（PCC-OFDM）信号的功率谱密度以及循环前缀对PCC-OFDM功率谱密度的影响进行了理论分析与计算机仿真,研究了循环前缀长度（Cyclic Prefix,CP）与带外功率大小的关系,结果表明在同样长度的循环前缀下,PCC-OFDM比普通OFDM具有较低的带外功率。在不同信道条件下,对PCC-OFDM性能进行仿真,并与普通的OFDM系统进行比较,表明PCC-OFDM具有较高的性能和实用价值。     

光学表面功率谱密度的表征

以硅基板镀制单层HfO2薄膜前后的表面微观形貌的变化为例,开展了光学表面功率谱密度的计算及表征研究。首先给出了一维功率谱密度(PSD1D)、二维功率谱密度(PSD2D)以及各向同性功率谱密度(PSDISO)的计算方法和具体步骤。然后使用原子力显微镜测量了硅基板镀膜前后在1 m1 m、5 m5 m、10 m10 m、20 m20 m四种扫描尺寸下的表面轮廓。在此基础上使用MATLAB编程计算得到这四种扫描尺寸下的PSDISO,对这些PSDISO使用几何平均算法拼接得到具有足够大频率范围的PSDISO-Combined。结果显示,硅基板镀膜前后的PSDISO-Combined在低频段基本相同,中高频段出现了明显差异。分析指出这是由镀膜后表面柱状晶体结构引起的。提出了对PSDISO在频域上积分得到表面均方根粗糙度ISO,再同由定义式计算得到的STD作对比的方法。计算得到的ISO与STD基本相同,验证了PSDISO计算方法的准确性。     

压控振荡器功率谱密度的研究

本文在分析计算了压控振荡器电路中的输出功率谱密度的基础上,针对控制电压涨落的情况,求解了振荡频率随机时的朗之万（Ｌａｎｇｅｖｉｎ）方程,获得了振荡频率涨落的均方根（ｒｍｓ）值,给出了涨落－耗散定理的一种表述,这使我们能更好地研究功率谱密度的线宽和有关噪声的起源。     

EVALUATION OF POWER SPECTRAL DENSITY OF PASSIVE INTERMODULATION DISTORTION IN HIGH-POWER COMMUNICATION SATELLITE SYSTEMS

In order to analyze the deleterious effects of Passive InterModulation (PIM) on high power communication satellite systems, the basic concept of PIM is introduced, and an equation for the power spectral density of the n-th order PIM distortion insuch systems is derived by applying fiat signal-power spectrum assumption and Fourier transform method~ It is indicated that PIM level generally decreases with order and the lowest frequency receive channel in the receive band is the channel of most affected by PIM interference.     

Application of fuzzy image restoration in criminal investigation

The advancement of science and technology has a positive effect on the development of law disciplines. The development of algorithms and artificial intelligence also has a certain impact on judicial practice. Image restoration is a significant technique in image processing. It aims to objectively restore the content or quality of the original image from the degraded image. Image degradation is always generated in image transmission, such as distortion, blur. In modern video surveillance system, image restoration is significant for criminal investigation. However, image restoration based on conventional filter algorithms cannot achieve satisfactory performance. Thus, we first introduce the image restoration algorithms based on different degradation model. Then, we propose some applications of fuzzy image restoration in criminal investigation. We conduct experiments on both degraded images and videos and experimental results have shown the effectiveness of fuzzy image restoration applying to the criminal investigation.     

短波信道多普勒功率谱密度研究

为研究短波信道多普勒功率谱密度,将电离层的运动假设为正规层与不均匀团块两种不同的运动,推导出了多普勒频移的表达式;在忽略电子密度随时间变化和地磁场影响的情况下,推导出了多普勒频移的一种概率密度函数表达式;在假设接收天线是圆对称的条件下,推导出了信号散射分量的多普勒功率谱密度函数,结果表明,功率谱密度的形状为混合高斯形;采用寻找误差序列标准差最小值的方法对实验所得数据多普勒功率谱密度的形状进行了混合高斯形状拟合,拟合结果表明理论推导的正确性.     

Blind source separation for convolutive mixtures based on the joint diagonalization of power spectral density matrices

This paper studies the problem of blind separation of convolutively mixed source signals on the basis of the joint diagonalization (JD) of power spectral density matrices (PSDMs) observed at the output of the separation system. Firstly, a general framework of JD-based blind source separation (BSS) is reviewed and summarized. Special emphasis is put on the separability conditions of sources and mixing system. Secondly, the JD-based BSS is generalized to the separation of convolutive mixtures. The definition of a time and frequency dependent characteristic matrix of sources allows us to state the conditions under which the separation of convolutive mixtures is possible. Lastly, a frequency-domain approach is proposed for convolutive mixture separation. The proposed approach exploits objective functions based on a set of PSDMs. These objective functions are defined in the frequency domain, but are jointly optimized with respect to the time-domain coefficients of the unmixing system. The local permutation ambiguity problems, which are inherent to most frequency-domain approaches, are effectively avoided with the proposed algorithm. Simulation results show that the proposed algorithm is valid for the separation of both simulated and real-word recorded convolutive mixtures.     

一种新型的图像恢复算法

针对巨型图片恢复处理过程中所面,临的运算量庞大的技术瓶颈,从光学图像退化模型出发,发展了一种基于最小二乘方的恢复算法,在算法的实现过程中回避了变换到频域的常规做法,提出了一种新颖的级联模板的运算方法,在一定程度上减小了运算量,降低了复杂度,实验结果表明该方法是有效的。     

DECONVOLUTION IN TRANSFORM-DOMAIN FOR IMAGE DATA RESTORATION

A novel scheme for image data restoration is proposed in this letter. First, a windowfunction model is exploited to describe the data loss in images. It can change the restoration problem into deconvolution in transform-domain. Then, an iterative algorithm is presented to solve the deconvolution. Because the window-function is available to describe arbitrary shape, our algorithm is suitable for restoring irregular segment of data loss, including square-block. Finally,several simulation tests are done and results prove that the algorithm is valid.     

气动光学效应图像恢复IBD算法研究

采用迭代盲目反卷积进行气动光学效应图像恢复研究,编制了相应的计算程序,获得了恢复图像和相应的气动光学效应降质过程的点扩散函数,同时讨论了共轭梯度CG算法在盲目反卷积图像恢复计算过程中的收敛性,并提出算法策略。     

A rapid hybrid algorithm for image restoration combining parametric Wiener filtering and wave atom transform

Image restoration refers to removal or minimization of known degradations in an image. This includes de-blurring images degraded by the limitations of sensors or source of captures in addition to noise filtering and correction of geometric distortion due to sensors. There are several classical image restoration methods such as Wiener filtering. To find an estimate of the original image, Wiener filter requires the prior knowledge of the degradation phenomenon, the blurred image and the statistical properties of the noise process. In this work, we propose a new rapid and blind algorithm for image restoration that does not require a priori knowledge of the noise distribution. The degraded image is first de-convoluted in Fourier space by parametric Wiener filtering, and then, it is smoothed by the wave atom transform after setting the threshold to its coefficients. Experiment results are significant and show the efficiency of our algorithm compared with other techniques in use.     

基于多尺度功率谱子带梯度的宽带频谱感知算法与性能分析

为了应对复杂环境下非合作通信、电磁频谱监管等宽带接收中存在的先验信息缺失、信道失真严重以及频域呈现不平坦色噪声的挑战,提出一种基于多尺度功率谱子带梯度的宽带频谱感知算法,该算法不要任何的先验信息,对功率谱进行分段计算梯度,再进行自适应双阈值检测,通过多尺度的技巧提高了宽带频谱感知的稳定性。对该算法在不同信道模型下的统计特性、虚警概率、检测概率以及判决门限的表达式进行了理论推导。理论分析和实验仿真表明,算法适用于高斯噪声信道和平坦衰落信道,能够有效克服色噪声,并且能够实现用户频带范围定位,运算复杂度低、实时性强,对噪声不确定度具有稳健性,能够用于低信噪比场合。