低相干光干涉法延时测量中的误差分析

低相干光干涉法通过测量宽谱光通过待测器件之后的相位变化得到其相对延时量。采集宽谱光时域干涉数据,利用傅里叶变换提取出频域相位信息后再进行相位展开、多项式拟合处理,所得相位曲线对频率求导可得待测延时曲线。延时测量误差来源于干涉信号强度误差和纯相位误差。理论分析和仿真计算表明,延时误差与相位误差成正比;强度噪声引起的相位误差与噪声强度成正比,且该类噪声可通过曲线拟合算法得到有效抑制。实验表明,温度等环境因素引起的纯相位误差是延时测量误差的主要因素。实验上,对约19 m光子晶体光纤于1540~1560 nm波段的相对延时进行了测量,达到了0.14 ps的精度。     

退火工艺对Al离子注入的4H-SiC表面形貌的影响

通过应用多次Al离子注入和CVD中的高温退火技术,在SiC片表面形成了p型层。p型层中各深度下Al的浓度均为110¹⁹cm^-3,层厚为550nm。本文应用三种不同的退火工艺对注入后的SiC进行退火。通过测量和比较表面粗糙度,发现通过石墨层覆盖来保护表面的退火工艺可以很好的阻止SiC表面在高温退火下的粗化,粗糙度保持在3.8nm。通过其他两种(在氩气保护下、在SiC保护片的覆盖下)退火工艺退火所得到的表面有明显的台阶,粗糙度分别为12.2nm和6.6nm。     

Using covariance intersection for change detection in remote sensing images

In this paper, an unsupervised change detection technique for remote sensing images ac-quired on the same geographical area but at different time instances is proposed by conducting Co-variance Intersection (CI) to perform unsupervised fusion of the final fuzzy partition matrices from the Fuzzy C-Means (FCM) clustering for the feature space by applying compressed sampling to the given remote sensing images. The proposed approach exploits a CI-based data fusion of the membership function matrices, which are obtained by taking the Fuzzy C-Means (FCM) clustering of the fre-quency-domain feature vectors and spatial-domain feature vectors, aimed at enhancing the unsuper-vised change detection performance. Compressed sampling is performed to realize the image local feature sampling, which is a signal acquisition framework based on the revelation that a small collection of linear projections of a sparse signal contains enough information for stable recovery. The experi-mental results demonstrate that the proposed algorithm has a good change detection results and also performs quite well on denoising purpose.     

A performance metric for codes with a high-order spectral at zero frequency

Sum-variance is a well-known metric for assessing the performance of dc-free codes (first-order spectral- codes), however, as we show in this paper, it is unsuitable for comparing the magnitude of spectral components of high-order spectral- (HOSN) codes at low frequencies. In this paper, we introduce a new performance metric for evaluating the spectrum compression of arbitrarily HOSN codes around zero frequency; we call this metric the low-frequency spectrum weight (LFSW). We show that the asymptotic low-frequency spectral components of Kth-order spectral- codes (K/spl ges/1) are exclusively determined by the order K and the LFSW, and that the LFSW equals the zero-frequency value in the spectrum of the corresponding sequence of Kth-order running digital sum values. We derive this result for symbol-by-symbol encoding, and then extend it to block HOSN codes. We then derive a closed-form expression for the LFSW of HOSN codes constructed through state-independent encoding. Closed-form expressions for LFSW of first-order zero-disparity codes and for the asymptotic LSFW of maxentropic dc-free sequences are also given.     

Blind feedforward cyclostationarity-based timing estimation for linear modulations

By exploiting a general cyclostationary (CS) statistics-based framework, this letter develops a rigorous and unified asymptotic (large sample) performance analysis setup for a class of blind feedforward timing epoch estimators for linear modulations transmitted through time nonselective flat-fading channels. Within the proposed CS framework, it is shown that several estimators proposed in the literature can be asymptotically interpreted as maximum likelihood (ML) estimators applied on a (sub)set of the second- (and/or higher) order statistics of the received signal. The asymptotic variance of these ML estimators is established in closed-form expression and compared with the modified Crame/spl acute/r-Rao bound. It is shown that the timing estimator proposed by Oerder and Meyr achieves asymptotically the best performance in the class of estimators which exploit all the second-order statistics of the received signal, and its performance is insensitive to oversampling rates P as long as P/spl ges/3. Further, an asymptotically best consistent estimator, which achieves the lowest asymptotic variance among all the possible estimators that can be derived by exploiting jointly the second- and fourth-order statistics of the received signal, is also proposed.     

Detection of buried targets via active selection of labeled data: application to sensing subsurface UXO

When sensing subsurface targets, such as landmines and unexploded ordnance (UXO), the target signatures are typically a strong function of environmental and historical circumstances. Consequently, it is difficult to constitute a universal training set for design of detection or classification algorithms. In this paper, we develop an efficient procedure by which information-theoretic concepts are used to design the basis functions and training set, directly from the site-specific measured data. Specifically, assume that measured data (e.g., induction and/or magnetometer) are available from a given site, unlabeled in the sense that it is not known a priori whether a given signature is associated with a target or clutter. For N signatures, the data may be expressed as {x/sub i/,y/sub i/}/sub i=1,N/, where x/sub i/ is the measured data for buried object i, and y/sub i/ is the associated unknown binary label (target/nontarget). Let the N x/sub i/ define the set X. The algorithm works in four steps: 1) the Fisher information matrix is used to select a set of basis functions for the kernel-based algorithm, this step defining a set of n signatures B/sub n//spl sube/X that are most informative in characterizing the signature distribution of the site; 2) the Fisher information matrix is used again to define a small subset X/sub s//spl sube/X, composed of those x/sub i/ for which knowledge of the associated labels y/sub i/ would be most informative in defining the weights for the basis functions in B/sub n/; 3) the buried objects associated with the signatures in X/sub s/ are excavated, yielding the associated labels y/sub i/, represented by the set Y/sub s/; and 4) using B/sub n/,X/sub s/, and Y/sub s/, a kernel-based classifier is designed for use in classifying all remaining buried objects. This framework is discussed in detail, with example results presented for an actual buried-UXO site.     

砷注入碲镉汞的激光退火

利用脉冲YAG激光器(脉宽为10ns,波长为1.06μm)对砷注入长波碲镉汞样品进行激光退火实验,分析注入退火引起的样品电学性质的变化,认为激光退火能够消除辐射损伤,并激活注入杂质.同时对电导率-迁移率谱这一实验方法也做了较详细的说明.     

Harmonic retrieval in colored non-Gaussian noise using cumulants

This paper addresses the harmonic retrieval problem in colored linear non-Gaussian noise of unknown covariance and unknown distribution. The assumptions made in the reported studies that the non-Gaussian noise is asymmetrically distributed and no quadratic phase coupling occurs are released. Using the elaborately defined fourth-order cumulants of the complex noisy observations, which are obtained by Hilbert transform, we can estimate either the correlation or the AR polynomial of the non-Gaussian noise via cumulant projections or ARMA modeling; then, the prewhitening or prefiltering techniques can be employed to retrieve harmonics, respectively. Simulation results are presented to demonstrate the effectiveness of the proposed algorithms     

一种新型激光扫描式大工件孔-孔同轴度测量仪

介绍了一种新型的基于激光扫描原理的大尺寸工件孔—孔同轴度测量原理和测量仪器。由于采用了反馈系统自动调节补偿光束漂移、大气扰动的误差 ,使精度有了较大提高。在3 0 m测量范围内相对误差可达 2× 1 0 -6。可应用于大型工件设备的制造和装配过程中的检测。     

认知无线电系统捷变频信号源设计

根据信道环境自适应调节数据速率的需求,设计了一款高性能的认知无线电系统信号源。该信号源以直接数字频率合成芯片AD9854（DDS）为核心,现场可编程门阵列（FPGA）芯片EP1C6Q240作为控制单元,实现频率捷变和调制速率捷变以及具有双路正交输出的功能。经测试,频率精度、稳定度及杂散抑制均达到设计要求,并可集成于认知无线电通信设备中。