南极冰貌卫星影像条带噪声的剔除

本文在简要叙述条带噪声形成原因的基础上 ,针对南极地区的ASTER 1A的可见光影像中出现的条带噪声的现象 ,通过设计了基于切比雪夫窗、凯瑟窗的FIR滤波器和约束最小二乘FIR滤波器对其条带噪声进行剔除 ,这两种滤波器能够尽可能地剔除条带 ,同时使影像的灰度分布发生最小畸变。并通过与其他方法 (例如 :低通滤波 ,直方图匹配等 )比较 ,说明这两种滤波的方法优于其他的方法     

Data Fusion in Distributed Multi-sensor System

This paper presents a data fusion method in distributed multi-sensor system including GPS and INS sensors“ data processing. First, a residual X^2-test strategy with the corresponding algorithm is designed.Then a coefficient matrices calculation method of the information sharing principle is derived. Finally, the federated Kalman filter is used to combine these independent, parallel, real-time data. A pseudolite (PL) simulation example is given.     

基于光谱信息的遥感图像空间域自适应滤波

遥感图像往往由于内外因素的干扰含有各种噪声 ,为提高图像质量人们对其进行滤波。常规的滤波方式完全基于图像空间域 ,在消除异常点使图像平滑的同时使边界变得不清楚从而使图像模糊 ;或者正相反 ,在边缘信息得到增强时也放大了图像噪声而使图像变得粗糙。该文的自适应滤波方法充分利用多光谱和高光谱遥感图像的光谱维信息 ,滤波时不仅要使均匀的地块得到平滑 ,而且要使地块间的边缘、局部的异常点、线仍然得到保存、在光滑的同时尽量保持原有的数值特征     

Simultaneous identification of time and space variant dynamic soil properties during the 1995 Hyogoken-Nanbu earthquake

Time and space variant soil properties at a liquefied site were simultaneously identified in the time domain by using borehole array strong motion records. During soil liquefaction at a site, soils usually show a wide variety of non-linear behavior along the depth as well as non-stationary behavior. Strong ground motion records were obtained at Port Island borehole array observatory, Kobe, during the 1995 Hyogoken-Nanbu earthquake. In this study, the instrumented soil was modeled by the equivalent linear MDOF system, and an extended Kalman filter with local iteration was employed for the identification of the soils. The identification process was successfully conducted, and the stress–strain relationships of the soils at the liquefied site were obtained from different depths all at once.     

Ocean current estimation using a Multi-Model Ensemble Kalman Filter during the Grand Lagrangian Deployment experiment (GLAD)

In the summer and fall of 2012, during the GLAD experiment in the Gulf of Mexico, the Consortium for Advanced Research on Transport of Hydrocarbon in the Environment (CARTHE) used several ocean models to assist the deployment of more than 300 surface drifters. The Navy Coastal Ocean Model (NCOM) at 1 km and 3 km resolutions, the US Navy operational NCOM at 3 km resolution (AMSEAS), and two versions of the Hybrid Coordinates Ocean Model (HYCOM) set at 4 km were running daily and delivering 72-h range forecasts. They all assimilated remote sensing and local profile data but they were not assimilating the drifter’s observations. This work presents a non-intrusive methodology named Multi-Model Ensemble Kalman Filter that allows assimilating the local drifter data into such a set of models, to produce improved ocean currents forecasts. The filter is to be used when several modeling systems or ensembles are available and/or observations are not entirely handled by the operational data assimilation process. It allows using generic in situ measurements over short time windows to improve the predictability of local ocean dynamics and associated high-resolution parameters of interest for which a forward model exists (e.g. oil spill plumes). Results can be used for operational applications or to derive enhanced background fields for other data assimilation systems, thus providing an expedite method to non-intrusively assimilate local observations of variables with complex operators. Results for the GLAD experiment show the method can improve water velocity predictions along the observed drifter trajectories, hence enhancing the skills of the models to predict individual trajectories.     

利用水准数据的天津市地面沉降时空特征分析

地面不均匀沉降可能对城市的发展与人民的安全造成危害，天津市的地面沉降情况尤为严重。针对该问题，本文收集天津市2005—2012年、2016—2017年水准观测数据，以固定水准点位的沉降量、沉降速率、沉降加速率为状态向量，构建卡尔曼滤波模型，对天津市历年的水准观测数据进行滤波；根据滤波后的结果，本文利用多项式加权内插的方法，以距离、沉降速率、沉降加速率信息确定权值大小，对地面沉降情况进行内插；并以中误差作为精度评定参数，比较多种内插方法的精度。通过对内插结果的试验分析发现，2005—2017年天津市地面累计平均沉降量为394.477 5 mm，最大沉降量为1 143.5 mm；主要沉降区域为北辰、大港、塘沽等地区，且随着时间的增长，这些区域呈现漏斗式下沉。试验证明本文结合卡尔曼滤波与多项式加权内插的方式能够较好地反映地面沉降的时空特征分布情况并对未来一段时间的沉降情况进行预测，对天津市的城市发展及建设有一定的参考意义。     

顾及局部与结构特征的稀疏多项式逻辑回归高光谱图像分类方法

稀疏多项式逻辑回归在分类中仅利用图像光谱信息，导致分类效果不太理想。本文提出了一种顾及局部与结构特征的稀疏多项式逻辑回归高光谱图像分类方法。首先利用加权均值滤波与拓展形态学多属性剖面对原始高光谱图像进行局部与结构特征提取；然后对二者进行加权平均特征级融合以获取更具唯一性的像元特征；最后由稀疏多项式逻辑回归分类器对融合结果进行分类。结果表明，本文方法能有效地提高分类精度，而且具有较强的稳健性。     

Combining two filter paper‐based analytical methods to monitor temporal variations in the geochemical properties of fluvial suspended particulate matter

Many of the commonly used analytical techniques for assessing the properties of fluvial suspended particulate matter (SPM) are neither cost effective nor time efficient, making them prohibitive to long‐term high‐resolution monitoring. We present an in‐depth methodology utilizing two types of spectroscopy which, when combined with automatic water samplers, can generate accurate, high‐temporal resolution SPM geochemistry data, inexpensively and semi‐destructively, directly from sediment covered filter papers. A combined X‐ray fluorescence spectroscopy and diffuse reflectance infrared Fourier transform spectroscopy approach is developed to estimate concentrations for a range of elements (Al, Ca, Ce, Fe, K, Mg, Mn, Na, P, Si, Ti) and compounds (organic carbon, Al_dithionate, Al_oxalate, Fe_dithionate, and Fe_oxalate) within SPM trapped on quartz fibre filters at masses as low as 3 mg. Calibration models with small prediction errors are derived, along with mass correction factor models to account for variations in retained SPM mass. Spectral pre‐processing methods are shown to enhance the reproducibility of results for some compounds, and the importance of filter paper selection and homogeneous sample preparation in minimizing spectral interference is emphasized. The geochemical signal from sediment covered filter papers is demonstrated to be time stable enabling samples to be stored for several weeks prior to analysis. Example results obtained during a heavy precipitation event in October 2012 demonstrate the methodology presented here has considerable potential to be utilized for high‐resolution monitoring of SPM geochemistry under a range of in‐stream hydrological conditions. Copyright © 2013 John Wiley & Sons, Ltd.     

基于NDVI时间序列数据的江西省水稻种植制度变化研究

利用Savitzky-Golay滤波对覆盖江西省范围的SPOT VGT NDVI时间序列数据进行平滑处理的基础上,结合坡度数据,通过非监督分类的方法提取了江西省2000、2005和2010年水稻种植范围,并根据NDVI的年内动态变化,从水稻种植范围、水稻生长季起始时间、水稻复种指数和NDVI最大振幅等分析了江西省水稻种植和生长情况,探讨2000~2010年江西省水稻生产的变化。     

基于方差递推法的Kalman滤波在钟差预报中的应用

卫星导航系统中星载原子钟的钟差预报对于导航、定位及授时具有重要的作用。为了提高卫星钟差预报的精度,设计了一种两步确定卫星钟噪声协方差矩阵的Kalman滤波钟差预报模型。该方法首先基于Hadamard总方差确定卫星钟噪声协方差矩阵的初值,然后,使用方差递推法得到滤波过程中卫星钟的噪声协方差矩阵。使用GPS系统的星载铷钟数据进行短期预报,并与常用的二次多项式模型、灰色模型进行对比,结果表明:本文中提出的方法可以实现高精度的卫星钟差预报且预报效果优于两种常用模型,同时,该方法能够在一定程度上弥补预报误差随预报时间增加而不断变大的不足。