Polymorphic phase transition in Superhydrous Phase B

We synthesized superhydrous phase B (shy-B) at 22 GPa and two different temperatures: 1200°C (LT) and 1400°C (HT) using a multi-anvil apparatus. The samples were investigated by transmission electron microscopy (TEM), single crystal X-ray diffraction, Raman and IR spectroscopy. The IR spectra were collected on polycrystalline thin-films and single crystals using synchrotron radiation, as well as a conventional IR source at ambient conditions and in situ at various pressures (up to 15 GPa) and temperatures (down to −180°C). Our studies show that shy-B exists in two polymorphic forms. As expected from crystal chemistry, the LT polymorph crystallizes in a lower symmetry space group (Pnn2), whereas the HT polymorph assumes a higher symmetry space group (Pnnm). TEM shows that both modifications consist of nearly perfect crystals with almost no lattice defects or inclusions of additional phases. IR spectra taken on polycrystalline thin films exhibit just one symmetric OH band and 29 lattice modes for the HT polymorph in contrast to two intense but asymmetric OH stretching bands and at least 48 lattice modes for the LT sample. The IR spectra differ not only in the number of bands, but also in the response of the bands to changes in pressure. The pressure derivatives for the IR bands are higher for the HT polymorph indicating that the high symmetry form is more compressible than the low symmetry form. Polarized, low-temperature single-crystal IR spectra indicate that in the LT-polymorph extensive ordering occurs not only at the Mg sites but also at the hydrogen sites.     

Prediction of creep characteristic of rock under varying environment

The strain developed due to creep is mainly proportional to the logarithm of the time under load, and is mostly proportional to the stress and temperature. At higher temperature the creep rate falls slowly with respect to time, and the creep strain is proportional to a fractional power of time, with the exponent increasing as the temperature increases and reaching a value approximately one-third at temperatures of about 0.5°C. At these temperatures, the creep increases with stress according to a power greater than unity and possibly exponentially. It increases with temperature as (−U/kT), where U is an activation energy and k is Boltzman’s constant. There are different methods to determine the creep strain and the energy of Jog (B) including experimental methods, multivariate regression analysis, and by numerical simulation. These methods are less cumbersome and time consuming. In the present investigation, artificial neural network technique has been used for prediction of the creep strain and energy of Jog (B). Two different networks have been tested and validated. Both the networks have four input neurons and one hidden layer with five neurons, and one output neuron. The data for different rocks at temperatures up to 750°C under conditions of compressive or tortional stress are taken from the literatures. The training and testing data sets used were 163 and 14, respectively. To deal with the problem of overfitting of data, Bayesian regulation has been used and network is trained with suitable training epochs. The coefficients of correlation among the predicted and observed values are found high and they improve the confidence of the users. The mean absolute percentage error obtained are also very low.     

Effects of temporal scales and space mismatches on the TRMM 3B42 v7 precipitation product in a remote mountainous area

The accurate measurement of precipitation is essential to understanding regional hydrological processes and hydrological cycling. Quantification of precipitation over remote regions such as the Tibetan Plateau is highly unreliable because of the scarcity of rain gauges. The objective of this study is to evaluate the performance of the satellite precipitation product of tropical rainfall measuring mission (TRMM) 3B42 v7 at daily, weekly, monthly, and seasonal scales. Comparison between TRMM grid precipitation and point‐based rain gauge precipitation was conducted using nearest neighbour and bilinear weighted interpolation methods. The results showed that the TRMM product could not capture daily precipitation well due to some rainfall events being missed at short time scales but provided reasonably good precipitation data at weekly, monthly, and seasonal scales. TRMM tended to underestimate the precipitation of small rainfall events (less than 1 mm/day), while it overestimated the precipitation of large rainfall events (greater than 20 mm/day). Consequently, TRMM showed better performance in the summer monsoon season than in the winter season. Through comparison, it was also found that the bilinear weighted interpolation method performs better than the nearest neighbour method in TRMM precipitation extraction.     

单片卫星影像在航测测图中的利用

在边境测图过程中,经常遇到较大面积云层问题,使航测测图无法顺利进行。能充分利用的影像资源是第一次全国地理国情普查的影像,有国产高分2号、SPOT-6、资源3号等单片卫星影像,无立体像对影像。通过对国情普查的影像分析选取,选取一试验区域进行试验,用国产高分2号卫星影像与SPOT-6卫星影像组成立体像对测制地物地貌,用Worldview卫星立体像对影像测制同一区域的地物地貌,将两种影像源组成立体模型测制的地物地貌进行比较及精度统计,说明单片卫星影像在航测测图中达到的精度。     

GPS精密卫星钟差估计研究

随着精密单点定位技术的发展,对于精确的卫星坐标以及卫星钟差改正精度的要求越来越高,精密卫星星历以及精密卫星钟差的求解成为制约精密单点定位技术发展的瓶颈。本文基于修复周跳的载波相位观测值与相位平滑伪距观测值,采用无电离层延迟星间单差精密卫星钟差估计模型,在先估计出整周模糊度后,进行了精密卫星钟差的估计,并采用与IGS事后精密钟差作二次差的方法进行精度分析,这对于提高精密单点定位精度具有一定的意义。     

高分二号卫星影像融合方法探析

图像融合技术是卫星影像处理过程中的一个重要步骤,它可以将全色影像的高空间分辨率特点与多光谱影像的高光谱分辨率特点有机地结合起来,使得融合后的影像更利于后续解译。由于融合处理方法的原理以及获取影像的传感器特性不同,不同的卫星影像适合于不同的融合方法。针对高分二号卫星影像的特点,本文采用Gram-Schmidt融合法、FIHS变换方法、HPF方法、Pansharp方法进行试验。实验结果表明:HPF方法所得融合结果在光谱特性保持方法性能最优,而Pansharp方法融合结果在信息量的保持以及清晰度方面效果更优,因此,在实际应用中,应根据具体需求进行方法选择。     

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。     

Pleiades高分辨率卫星影像道路提取技术

遥感影像上的道路提取是摄影测量与计算机视觉研究的一项重要内容,本文设计了一种高分辨率卫星影像道路提取方法,首先,利用Canny边缘提取算子提取左影像上的边缘,并利用霍夫变换对线特征进行检测,根据道路的几何特性检测平行直线,再基于影像匹配方法匹配立体像对上的道路;然后,利用卫星影像RPC参数前方交会原理实现道路的几何定位。利用Pleiades卫星影像开展试验,自动提取的道路与人工采集的道路几何定位误差在1个像素以内,试验结果验证了本文方法的有效性。     

AEKF在星敏感器低频误差补偿中的应用

高分辨率对地观测卫星需要精确的姿态信息来满足后续对地定位等工作,因此姿态确定精度十分重要。星敏感器的低频误差是影响卫星姿态确定精度的重要因素之一,主要是由空间周期性的热环境变化引起的。为进一步提高卫星姿态确定精度,对星敏感器的低频误差产生机理即星敏感器主光轴做周期性扰动进行了分析,设计了星敏感器低频误差补偿方案,建立了考虑星敏感器低频误差在内的组合定姿模型,利用拓维卡尔曼滤波(AEKF)对低频误差进行补偿,并引入RTS平滑滤波进一步提高姿态确定精度。仿真实验表明,设计的星敏感器低频误差补偿方案能有效对其进行补偿,提高卫星姿态确定精度。     

Verification and Correction of Cloud Base and Top Height Retrievals from Ka–band Cloud Radar in Boseong,Korea

In this study,cloud base height(CBH) and cloud top height(CTH) observed by the Ka-band(33.44 GHz) cloud radar at the Boseong National Center for Intensive Observation of Severe Weather during fall 2013(September-November) were verified and corrected.For comparative verification,CBH and CTH were obtained using a ceilometer(CL51) and the Communication,Ocean and Meteorological Satellite(COMS).During rainfall,the CBH and CTH observed by the cloud radar were lower than observed by the ceilometer and COMS because of signal attenuation due to raindrops,and this difference increased with rainfall intensity.During dry periods,however,the CBH and CTH observed by the cloud radar,ceilometer,and COMS were similar.Thin and low-density clouds were observed more effectively by the cloud radar compared with the ceilometer and COMS.In cases of rainfall or missing cloud radar data,the ceilometer and COMS data were proven effective in correcting or compensating the cloud radar data.These corrected cloud data were used to classify cloud types,which revealed that low clouds occurred most frequently.