星像抖动的时域频谱

本顾及湍流外尺度的影响导出了星像抖动频谱的普遍表达式，在均匀光路的情况下得到了分析表达式。理论结果与实验数据相当一致，同时讨论了测量星像抖动所需要的频带宽度以及有限带宽所产生的测量误差。     

1992年11月2日的太阳射电爆发事件的特征分析

本文详细地分析了1992年11月2日0233UT发生的太阳大爆发的射电特征,发现此爆发的峰值频谱是U型谱并伴有大的质子事件。爆发过程中,在9.4GHz频率上有快速脉动现象,脉动个数R(重复率)同相应平均流量S之间是紧密相关的。     

GPR探测中管线异常自动提取与识别

在目前的探地雷达管线探测中,埋藏管线产生的双曲线特征是专业人员用来推断和解释目标的主要依据,但双曲线特征尚不能精准界定管线目标的属性材料.为了进一步对管线反射双曲线区域特征的解释分析,本文首先对经过预处理的GPR数据,运用图像处理手段对感兴趣的管线回波双曲线异常区域进行自动圈定,定位管线位置.然后综合分析管线信号时频谱特征和瞬时相位特征这些具有区分力的多参数特征,判定管线属性材料,完成对管线的提取与识别.最后,将该方法运用于模拟数据与实测数据之中,实现了管线的自动提取与参数特征分类识别,为GPR数据解释提供了指导意义.     

纹理频谱分析的高分辨率遥感影像最佳尺度选择

基于对纹理频谱的分析提出了一种高分辨率遥感影像最佳尺度的选择方法。首先,分析四种典型地物在傅里 叶变换频域的频谱响应特性。然后,采用点扩散函数对原始影像进行尺度扩展,进而根据地物纹理的径向与角向曲线 随尺度扩展的变化选择最佳尺度。最后,通过分析四种地物在6个尺度下的纹理特征可分性,说明本文方法能客观反映 出地物的尺度效应,具备最佳尺度选择的可行性。利用支持向量机对QuickBird全色影像进行面向对象的分类,实验结 果表明在最佳尺度下可取得较高精度。     

地震和爆炸的P波层析成像——第二部分：由时频地震图得到的2004年苏门答腊-安达曼地震的断层破裂特征（英文）

本文分析了2004年12月26日苏门答腊-安达曼地震的宽频带地震图。目的是通过不同频率成分的子事件的发生时间了解断层的破裂过程。具体分析的是由相应宽频带地震记录得到的P波的时频地震图。分析结果说明,在S波到达前的时窗内发生了最大辐射强度的相应频率低于1 Hz的15次较大子事件,但在同样的时窗内,还发生了最大辐射强度的频...     

新一代天气雷达发射机寄生频谱分析与处理方法

针对新一代天气雷达(CINRAD)发射机频谱中存在寄生谱线的现象,建立了雷达发射信号寄生调制的数学模型,根据CINRAD雷达发射机组成原理框图,分析了寄生谱线产生的原因,并提出了解决雷达发射机寄生谱线问题的方法,利用该方法在某CINRAD雷达系统联调和测试中基本消除了发射机输出频谱的寄生谱线,提高了发射机的频谱纯度.     

结合Fourier域约束的多帧盲解卷积图像恢复算法

大气湍流严重限制了地对空光学系统的成像质量,自适应光学系统对大气湍流的补偿仅仅是部分的、有限的。当前的图像恢复技术对重建过程中的PSF施加的先验约束主要有非负性、归一化、支持域等空间域约束。这里对图像的Fourier频谱特性进行分析,将一种基于Fourier域的先验约束引入到多帧迭代盲解卷积算法中。实验结果表明,该算法可有效对模糊图像进行恢复,尤其是对强湍流观测下的重度模糊图像具有较好的恢复效果。     

Numerical simulation and preliminary analysis on ocean waves during Typhoon Nesat in South China Sea and adjacent areas

Using the wave model WAVEWATCH III(WW3), we simulated the generation and propagation of typhoon waves in the South China Sea and adjacent areas during the passage of typhoon Nesat(2011). In the domain 100°–145°E and 0°–35°N, the model was forced by the cross-calibrated multi-platform(CCMP) wind fi elds of September 15 to October 5, 2011. We then validated the simulation results against wave radar data observed from an oil platform and altimeter data from the Jason-2 satellite. The simulated waves were characterized by fi ve points along track using the Spectrum Integration Method(SIM) and the Spectrum Partitioning Method(SPM), by which wind sea and swell components of the 1D and 2D wave spectra are separated. There was reasonable agreement between the model results and observations, although the WW3 wave model may underestimate swell wave height. Signifi cant wave heights are large along the typhoon track and are noticeably greater on the right of the track than on the left. Swells from the east are largely unable to enter the South China Sea because of the obstruction due to the Philippine Islands. During the initial stage and later period of the typhoon, swells at the fi ve points were generated by the propagation of waves that were created by typhoons Haitang and Nalgae. Of the two methods, the 2D SPM method is more accurate than the 1D SIM which overestimates the separation frequency under low winds, but the SIM method is more convenient because it does not require wind speed and wave direction. When the typhoon left the area, the wind sea fractions decreased rapidly. Under similar wind conditions, the points located in the South China Sea are affected less than those points situated in the open sea because of the infl uence of the complex internal topography of the South China Sea. The results reveal the characteristic wind sea and swell features of the South China Sea and adjacent areas in response to typhoon Nesat, and provide a reference for swell forecasting and offshore structural designs.     

Mesoscale predictability of moist baroclinic waves: Variable and scale-dependent error growth

This study seeks to quantify the predictability of different forecast variables at various scales through spectral analysis of the difference between perturbed and unperturbed cloud-permitting simulations of idealized moist baroclinic waves amplify- ing in a conditionally unstable atmosphere. The error growth of a forecast variable is found to be strongly associated with its reference-state （unperturbed） power spectrum and slope, which differ significantly from variable to variable. The shallower the reference state spectrum, the more spectral energy resides at smaller scales, and thus the less predictable the variable since the error grows faster at smaller scales before it saturates. In general, the variables with more small-scale components （such as vertical velocity） are less predictable, and vice versa （such as pressure）. In higher-resolution simulations in which more rigorous small-scale instabilities become better resolved, the error grows faster at smaller scales and spreads to larger scales more quickly before the error saturates at those small scales during the first few hours of the forecast. Based on the reference power spectrum, an index on the degree of lack （or loss） of predictability （LPI） is further defined to quantify the predictive time scale of each forecast variable. Future studies are needed to investigate the scale- and variable-dependent predictability under different background reference flows, including real case studies through ensemble experiments.     

多元回归与频谱分析在地铁自动化监测分析中的应用研究

多元回归分析是变形监测数据分析的常用方法。本文首先给出多元线性回归模型以及模型显著性检验方法,然后结合频谱分析可以确定时间序列数据的周期性,综合使用两种方法进行地铁保护区自动化监测数据分析,结果表明:该综合模型对变形数据的处理有着显著的优越性。