浅海多径时延估计的功率谱加权自相关方法

针对浅海近距离时倒谱多径时延峰变弱难以提取的问题,提出了一种功率谱加权自相关多径时延估计方法。该方法采用FFT估计信号功率谱,对功率谱取1-α次幂(0<α<1),再进行IFFT变换,对其实部进行峰值检测获得多径时延估计。根据目标能量通过特性在正横前递增正横后递减的特点,在已检测时延前后一定区间内搜索下一个时延值,实现多径时延的自动提取.理论分析表明,多径时延估计的倒谱法与自相关法都可以看作功率谱加权自相关法的特例.海试数据处理与基于Bellhop射线模型的仿真计算表明,该方法在近距离时多径时延峰比倒谱法更清晰,输出信噪比提高了3~4 dB.采用该方法自动提取的海底反射多径时延用于单个水听器对目标距离的估计,与GPS测量距离基本相符,验证了方法的有效性.      

一种252Cf裂变中子源的中子、γ射线飞行时间谱测量新方法

 针对²⁵²Cf快中子、γ射线的飞行时间谱测量要求,提出并建立一种基于高速数据采集卡的新型测量系统。采用1 GHz高速A/D转换单元和现场可编程门阵列高速处理单元,进行脉冲时间序列的在线检测,时间精度为1 ns。使用相关函数法,通过PC机的数据处理、互相关函数计算和数值统计等实现中子、γ射线飞行时间谱的测量。实验结果表明,该系统可以获得²⁵²Cf自发裂变中子源的中子、γ射线飞行时间谱,与经典的飞行时间谱测量方法相比较,其图谱表达及数值结果有着很高的吻合度。     

Imprints of spherical nontrivial topologies on the cosmic microwave background

The apparent low power in the cosmic microwave background (CMB) temperature anisotropy power spectrum derived from the Wilkinson Microwave Anisotropy Probe motivated us to consider the possibility of a nontrivial topology. We focus on simple spherical multiconnected manifolds and discuss their implications for the CMB in terms of the power spectrum, maps, and the correlation matrix. We perform a Bayesian model comparison against the fiducial best-fit cold dark matter model with a cosmological constant based both on the power spectrum and the correlation matrix to assess their statistical significance. We find that the first-year power spectrum shows a slight preference for the truncated cube space, but the three-year data show no evidence for any of these spaces.     

The properties of liquid nitrogen

The light-scattering ‘anisotropy’ spectrum of liquid nitrogen has been measured for the liquid along the liquid-vapour coexistence line from 69·4 K (almost the triple point) to near the critical point at 125 K and for the gas under pressure at 128 K. The spectrum is very broad (HWHH～50 cm^-1) due to rapid molecular reorientation. The molecular anisotropy spectrum is approximately gaussian, corresponding to a correlation time for molecular reorientation of order 2 × 10^-13 s at 80 K which is comparable with that obtained from nuclear magnetic resonance. A gaussian rather than a lorentzian form arises because molecular reorientation is not a ‘slow’ variable.

Above the critical temperature the molecular anisotropy spectrum can be roughly described as a collision-broadened rotational line spectrum.

The spectrum and its time Fourier Transform are analysed in terms of the dynamical correlation of orientation of the molecules.

A component of the spectrum due to induced polarization is separated from the anisotropy contribution by a study of the far wing of the spectrum and is observed on the Stokes side out to about 250 cm^-1. This depends exponentially on frequency shift and is interpreted in terms of molecular collision dynamics. The correlation time for this motion is about a factor three shorter than that for molecular reorientation.

The spectra are markedly asymmetric after all experimental corrections for asymmetry have been made. The asymmetry is shown to correspond to the detailed balance factor. It is pointed out that this factor should be allowed for in the case of induced scattering, in particular.

A theoretical analysis is given of the effect of correlation of molecular orientation on the light-scattering spectrum for centrosymmetric linear molecules. In particular it is shown that the normalized second moment of the spectrum is unaffected by correlation of orientation.     

Asymptotic Similarity of Time Correlation Functions and Shape of the <Superscript>13</Superscript>C and <Superscript>29</Superscript>Si NMR Spectra in Diamond and Silicon

Based on the proposed theory, we have investigated the shape of the NMR absorption spectra for ¹³C and ²⁹Si nuclei in diamond and silicon crystals attributable to the internuclear dipole–dipole interaction. In accordance with the available experimental data, we have considered both crystals with a 100% content of magnetoactive isotopes and crystals with a comparatively low dilution by nonmagnetic nuclei. The time correlation functions (the first of which is the Fourier transform of the NMR spectrum) arising in an infinite chain of coupled differential equations are shown to be mutually similar with a slight time delay. The proposed theory allows the spectrum to be calculated analytically. The results obtained agree satisfactorily with the experimental ones. It is noted that the mutual similarity of the time correlation functions is probably a corollary of the development of dynamical chaos in the system     

Nonlinear real-life signal detection with a supervised principal components analysis

A novel strategy named supervised principal components analysis for the detection of a target signal of interest embedded in an unknown noisy environment has been investigated. There are two channels in our detection scheme. Each channel consists of a nonlinear phase-space reconstructor (for embedding a data matrix using the received time series) and a principal components analyzer (for feature extraction), respectively. The output error time series, which results from the difference of both eigenvectors of the correlation data matrices from these two channels, is then analyzed using time-frequency tools, for example, frequency spectrum or Wigner-Ville distribution. Experimental results based on real-life electromagnetic data are presented to demonstrate the detection performance of our algorithm. It is found that weak signals hidden beneath the noise floor can be detected. Furthermore, the robustness of the detection performance clearly illustrated that signal frequencies can be extracted when the signal power is not too low.     

Improved approach for target detection and recognition on optoelectronic hybrid joint transform correlator

A conventional joint transform correlator (JTC) often generates large correlation sidelobes as well as a large correlation peak width, strong zero-order peak, and low diffraction efficiency in target detection and recognition, which make the detection ability of JTC lower. To conquer these difficulties, firstly, a joint power spectrum (JPS) subtraction technique was proposed in Fourier plane, where power spectrum of reference image and power spectrum of object image are subtracted from the JPS before inverse Fourier-transform operation, it is evident that the improved JPS removes the zero-order term. Secondly, a fringe-adjusted filter (FAF) was presented to restrain sidelobes and noises. The revised JPS is multiplied by a FAF before the inverse Fourier-transform operation to obtain the cross-correlation peak. Computer simulations showed the improved method can markedly eliminate zero-order diffraction and effectively control the sidelobes and noises compared to traditional JTC, and then enhance the detection ability for JTC. Experimental results presented the sharp correlation peak and also demonstrated this approach effectiveness.     

基于空间谱的玉米叶片铜铅污染区分及程度监测

利用高光谱遥感技术监测并识别农作物受重金属污染信息是当今热点,研究设置了不同浓度铜离子(Cu2+)、铅离子(Pb2+)胁迫梯度的玉米盆栽实验,并测取了玉米叶片的光谱及叶片中重金属离子与叶绿素含量。基于获取的光谱数据,将光谱划分为紫谷、蓝边、绿峰、红谷、红边和红肩六个光谱特征区间,通过光谱的一阶微分和二维多重信号分类(2D-MUSIC)算法构造空间谱,对各光谱特征区间进行变换分析。实验结果表明：蓝边、绿峰和红边阵列信号的空间谱在Cu2+胁迫下为双高峰,在Pb2+胁迫下为单高峰,以此能够快速、直观地区分玉米叶片所受重金属污染的Cu2+和Pb2+元素类别。红谷和红肩阵列信号空间谱的方位角谱峰值与玉米叶片中Cu2+含量的相关系数分别达到-0.954 5和-0.964 8,说明用于监测Cu2+污染程度时效果理想;紫谷阵列信号空间谱的方位角谱峰值与玉米叶片中Pb2+含量的相关系数达到-0.999 8,说明用于监测Pb2+污染程度时效果理想。同时通过与常规重金属污染监测方法绿峰高度(GH)、红边位置(REP)、红边最大值(MR)、红边一阶微分包围面积(FAR)的应用结果进行比较分析,空间谱法的应用结果与玉米叶片中重金属离子含量的相关性较高,从而验证了空间谱应用于玉米重金属污染信息监测具有更好的有效性和优越性。     

Experimental demonstration of spread spectrum communication over long range multipath channels

This paper presents a spread spectrum scheme, which is designed for long range underwater acoustic communications of low signal-to-noise ratios. This scheme uses two maximum length sequences, which are overlapped in time. One is used as a time reference, and the other applies code cyclic shift keying (CCSK) to carry information. Compared with conventional spread spectrum techniques, CCSK achieves a higher spectral efficiency, and this property is of significance in spread spectrum communications. With the help of a time reference, performance impairment from timing errors for CCSK is reduced, as each CCSK symbol has its own time reference. For this scheme, three receiver structures are presented, and they are: (1) correlation receiver, (2) passive-phase conjugation receiver, and (3) time reversal receiver structures. A recent sea experiment was carried out in a range dependent channel over a distance of 10 km. By real data processing, performance of the three receiver structures are compared and discussed. The presented results demonstrate the feasibility of this spread spectrum scheme.     

应用近红外光谱分析不同年度工业分级烟叶的特性

以红塔集团2007年—2010年在云南省玉溪烤烟产区内采集的主要工业分级烟叶样品为试验对象,其品种为红大,包括不同部位及色组的主要工业分级,共计近红外光谱5 730条;应用光谱特征投影及相关分析方法对不同年度的主要分级烟叶近红外光谱的分析结果表明：相同年度下,将各类型工业分级样品随机按2∶1划分为分析集与验证集后,其分析集与验证集特征投影均值的相关系数达0.98以上,具有较好的一致性;不同年度间,其工业分级样品光谱特征投影均值的相关系数在0.97以上,其中年度一致性最高的是2008年和2009年,较低的是2007年和2010年。同时,应用一种相似度计算方法得到了各工业分级样品光谱之间的相似度值,该相似度值以及不同年度之间的一致性系数,可为烟叶的模块配方组合或替代等提供量化的参考数据。     

A spectrum auction algorithm based on joint power control and beamforming in small cell networks

Spectrum auction is considered as a suitable approach to efficiently allocate spectrum among unlicensed users. However, in previous studies of spectrum auction, competition can hardly be reflected in the traditional spectrum allocation and the spectrum efficiency is still not high after the allocation. In this paper, we enhance the factor of competition in the auctions, in which bidders need to pay for the competition and the interference to macro cell users (MUs). We consider a communication system with one macro cell and several small cells, thus a licensed radio spectrum is shared by both MUs and small cell users (SUs). A truthful auction algorithm is proposed for spectrum allocation and the spectrum is divided into multiple channels in different time slots, so that SUs can make their choice for bidding under the guidance of history. In order to raise the communication quality, we propose a power control and beamforming algorithm in the heterogeneous network to enhance the system performance. Simulation results are presented to verify the effectiveness of the proposed algorithm in the small cell network.     

Chaotic dynamics of sea clutter

The notion that a deterministic nonlinear dynamical system (with relatively few degrees of freedom) can display aperiodic behavior has a strong bearing on sea clutter characterization: random-looking sea clutter may be the outcome of a chaotic process. This new approach envisages deterministic rules for the underlying sea clutter dynamics, in contrast to the stochastic approach where sea clutter is viewed as a random process with a large number of degrees of freedom. In this paper, we demonstrate, convincingly for the first time, the chaotic dynamics of sea clutter. We say so on the basis of results obtained using radar data collected from a series of extensive and thorough experiments, which have been carried out with ground-truthed sea clutter data sets at three different sites. The study includes correlation dimension analysis (based on the maximum likelihood principle) and Lyapunov spectrum analysis. The Lyapunov (Kaplan-Yorke) dimension, which is a byproduct of Lyapunov spectrum analysis, shows that it is indeed a good estimator of the correlation dimension. The Lyapunov spectrum also reveals that sea clutter is produced by a coupled system of nonlinear differential equations of order five or six. (c) 1997 American Institute of Physics.     

Enhanced spectral resolution by high-dimensional NMR using the filter diagonalization method and "hidden" dimensions

High-dimensional (HD) NMR spectra have poorer digital resolution than low-dimensional (LD) spectra, for a fixed amount of experiment time. This has led to "reduced-dimensionality" strategies, in which several LD projections of the HD NMR spectrum are acquired, each with higher digital resolution; an approximate HD spectrum is then inferred by some means. We propose a strategy that moves in the opposite direction, by adding more time dimensions to increase the information content of the data set, even if only a very sparse time grid is used in each dimension. The full HD time-domain data can be analyzed by the filter diagonalization method (FDM), yielding very narrow resonances along all of the frequency axes, even those with sparse sampling. Integrating over the added dimensions of HD FDM NMR spectra reconstitutes LD spectra with enhanced resolution, often more quickly than direct acquisition of the LD spectrum with a larger number of grid points in each of the fewer dimensions. If the extra-dimensions do not appear in the final spectrum, and are used solely to boost information content, we propose the moniker hidden-dimension NMR. This work shows that HD peaks have unmistakable frequency signatures that can be detected as single HD objects by an appropriate algorithm, even though their patterns would be tricky for a human operator to visualize or recognize, and even if digital resolution in an HD FT spectrum is very coarse compared with natural line widths.     

Generation of broadband biphotons and their compression in an optical fiber

The generation of biphoton wave packets with a broad spectrum owing to quasi-phase-matched spontaneous parametric down-conversion in a crystal with an aperiodic poling has been considered. Biphotons at the exit of such a sample are not Fourier limited; i.e., their correlation time is much larger than the inverse width of the spectrum. It has been shown that if the inverse grating vector varies linearly along the sample length, the generated biphoton wave packets can be compressed in time by transmitting two-photon light through an optical fiber.     

Spectrum,intensity and coherence in weighted networks of a financial market

We construct a correlation matrix based financial network for a set of New York Stock Exchange (NYSE) traded stocks with stocks corresponding to nodes and the links between them added one after the other, according to the strength of the correlation between the nodes. The eigenvalue spectrum of the correlation matrix reflects the structure of the market, which also shows in the cluster structure of the emergent network. The stronger and more compact a cluster is, the earlier the eigenvalue representing the corresponding business sector occurs in the spectrum. On the other hand, if groups of stocks belonging to a given business sector are considered as a fully connected subgraph of the final network, their intensity and coherence can be monitored as a function of time. This approach indicates to what extent the business sector classifications are visible in market prices, which in turn enables us to gauge the extent of group-behaviour exhibited by stocks belonging to a given business sector.     

Recognition and Clarification of Cross Peaks in Crowded Two-Dimensional Correlation Spectra

A new scheme is suggested for the automated recognition of cross peaks in two-dimensional correlation spectra. It makes use of prior knowledge of the chemical shifts derived from a symmetry-based search of the two-dimensionalJspectrum, using this information to construct a two-dimensional “chemical-shift grid” that may be overlaid on the corresponding correlation spectrum (COSY, TOCSY, EXSY, or NOESY). The search for local symmetry (or antisymmetry) in the correlation spectrum may then be restricted to intersections on the chemical-shift grid instead of a point-by-point examination of the entire two-dimensional array. This greatly accelerates the search program. Applied to the 400 MHz proton correlation (DQ-COSY) spectrum of 1-dehydrotestosterone, this automated routine locates 28 pairs of cross peaks, and in particular, identifies a tight cluster ofeightinterpenetrating spin multiplets. This latter finding is confirmed by a different method that reconstructs individual cross peaks from partially exposed segments and then strips them away one at a time.     

Restricted linear least square treatment processing of heteronuclear spectra of biomolecules using the ANAFOR strategy

We explore the use of a processing procedure based on restricted least square minimization as a tool for reducing the time versus resolution dilemma often encountered for biomolecular multidimensional spectra. Using a 2D spectrum as a reference, we obtain the necessary input of frequency components and linewidths. Combined even with a limited time evolution in the indirect dimension, the amplitudes of the correlation peaks in all planes of the 3D spectra can be extracted, and can be used to reconstruct the interferograms in the third dimension. Parameters such as number of lines, threshold choice, resolution, lineshape, number of experimental data points and finally signal to noise ratio of the spectrum are examined starting from a triple-resonance HNCA spectrum of ubiquitin.     

The effect of ocean wave on the vertical spatial correlation of ocean ambient noise

The effect of the correlation function of noise sources derived from the ocean wave spectrum on the vertical spatial correlation of ocean ambient noise is investigated. The spatial correlation models of ocean ambient noise usually assume that the surface noise sources are uncorrelated. This assumption can be used to explain some physical phenomena, but it is not consistent with the real situation. Considering the relation between the ocean wave motion and the ambient noise generated by wind, the spectrum of ocean wave is introduced to calculate the vertical correlation of ocean ambient noise as the correlation function of noise sources by using the Kuperman-Ingenito(K/I) noise model. The comparison of the simulations and the experimental data shows that the simulations of vertical correlation of ambient noise have some differences with the experimental data by assuming the noise sources are uncorrelated and the simulations of vertical correlation of ambient noise have a good agreement with the experimental data by using the correlation function of noise sources derived from the ocean wave spectrum under the situation of high wind speed.     

Weak signal detection based on underdamped stochastic resonance with an exponential bistable potential

Stochastic resonance (SR) is a vital approach to detect weak signals submerged in strong background noise, which is useful for mechanical fault diagnosis. The underdamped bistable SR (UBSR) is a kind of the most used SR, however, their potential structures are deficient to match with the complicated and diverse mechanical vibration signals and their parameters are selected subjectively which probably resulting in poor performance of UBSR. To overcome these shortcomings, this paper proposes an underdamped SR with exponential potential (UESR) which is generalized by using a harmonic model and a Gaussian potential (GP) model. The dynamics in UESR system is evaluated by the signal-to-noise ratio (SNR) which represents the effectiveness of noise utilization. Then, the effects of system parameters on system performance are investigated by output SNR versus noise intensity D for different parameters. Finally, the proposed method is used to process bearing experimental data and further perform bearing fault diagnosis. The experimental results demonstrate that a larger output SNR and higher spectrum peaks at fault characteristic frequencies can be obtained by the proposed method compared with the UBSR method, which confirm the effectiveness of the proposed method.