基于扩散滤波的多尺度三维变分研究

将扩散方程引入三维变分分析,揭示了传统3D-VAR不能有效提取多尺度观测信息的根本原因,即观测导致的目标函数梯度在空间的不连续分布.将扩散滤波融入基于梯度的最优化算法,发展了基于扩散滤波的多尺度3D-VAR.海表面温度数据同化试验结果表明,新方法可从长波至短波有效地提取多尺度的观测信息.     

滤食性贝类在对虾综合养殖生态系统中的作用

就混养虾池中滤食性贝类如何影响虾池整个生态系统这个问题，综合了国内外这方面的文献，从滤食性贝类对混养虾池的水质、底质和其中的浮游植物、浮游动物的影响，以及混养对养殖效益的影响这几个方面作了探讨。     

一种基于OpenMP的高效GPS卫星钟差实时估计方法

提出基于单观测值的Kalman滤波快速计算方法,并引入共享存储并行编程（OpenMP）技术实现协方差快速更新,从而实现非差GPS卫星钟差的快速实时计算。均匀选取55个IGS参考站,计算2017-03-20~03-30采样率为60 s的卫星钟差。与IGS事后30 s钟差相比,两者具有很好的一致性,RMS互差优于0.5 ns。选取未参与钟差解算的10个IGS参考站进行精密单点定位,结果表明,实时静态PPP水平方向精度优于2 cm,高程方向精度为2~4 cm;实时动态PPP水平方向精度为2～4 cm,高程方向精度为4～6 cm,能够满足实时PPP的精度要求。该方法在主频1.2 GHz服务器上8线程并行模式下单历元耗时4 s,相比串行模式效率提升1/3。     

一种基于熵权法的小波去噪复合评价指标

传统的评价指标在真值未知的情况下不能满足小波去噪质量评价的要求。为此,借助变化率特征重新构建均方根误差变化量和平滑度变化量两个指标,利用熵权法定权将归一化后的两个指标线性组合,所得到的新指标即为复合评价指标。该方法借助指标的变化率随分解层数的增加表现出明显的收敛特性来确定去噪最优分解层数。实验表明,该方法能够在真值未知的情况下准确地指导小波分解,确定去噪最优分解层数,从而达到最优去噪效果。     

捷联式航空重力扰动矢量解算及误差补偿

介绍捷联式航空重力矢量测量的基本原理,利用波数相关滤波（WCF）、比力线性校正的方法对重力扰动的水平和垂向分量进行误差补偿,评定内符合精度。对国产捷联式航空重力矢量仪的某次试验数据进行处理,以验证和评估航空重力矢量仪的性能。结果表明,在半波长分辨率为7.5 km时,6条重复测线的重力扰动水平分量经波数相关滤波处理后,东、北向分量的平均内符合精度分别从9.77 mGal、9.18 mGal提高到5.95 mGal、3.83 mGal;对比力的垂向分量线性校正后,将解算的重力扰动垂向分量再用WCF方法处理,其平均内符合精度从1.27 mGal提高到0.59 mGal。     

速度传感反馈地震计的动态范围上限

在开环参数一定的条件下,速度传感反馈地震计中的环路滤波是影响地震计主要技术指标的关键环节之一.本文探讨了一阶极点高通、一阶极点低通、一阶零点高通、双一阶和零阶环路滤波在扩展地震计动态范围上限方面的优缺点.研究指出,对于用闭环反馈直接生成主导二阶极点的速度传感反馈地震计,一阶零点高通环路滤波的优点较多;若允许在环外生成主导二阶极点,则零阶环路滤波也不失为一个较好的方案.     

Integration of remote sensing data into hydrological models for reservoir management

Abstract

The purpose of this paper is to present the methodology set up to derive catchment soil moisture from Earth Observation (EO) data using microwave spaceborne Synthetic Aperture Radar (SAR) images from ERS satellites and to study the improvements brought about by an assimilation of this information into hydrological models. The methodology used to derive EO data is based on the appropriate selection of land cover types for which the radar signal is mainly sensitive to soil moisture variations. Then a hydrological model is chosen, which can take advantage of the new information brought by remote sensing. The assimilation of soil moisture deduced from EO data into hydrological models is based principally on model parameter updating. The main assumption of this method is that the better the model simulates the current hydrological system, the better the following forecast will be. Another methodology used is a sequential one based on Kalman filtering. These methods have been put forward for use in the European AIMWATER project on the Seine catchment upstream of Paris (France) where dams are operated to alleviate floods in the Paris area.     

The Mathematic Models of the Kalman Filtering for Across-Fault Measurement

This paper makes a probe into the application of the Kalman filtering method to the data processing of across-fault measurements.On the basis of statistical regression,the mathematic and stochastic models of filtration are established by combining the regression method with Kalman filtering.In the filtering computation,not only the randomness of fault movements but also the time-dependent variation of environmental effects have been taken into consideration.By use of the adaptive filtering method,an estimation of the dynamic noise variance matrix is obtained through iteration.Models for one measuring line(leveling line or baseline),two measuring lines(both leveling lines or both baselines)and four measuring lines(two leveling lines and two baselines)are derived and established systematically.By means of these models,the data of across-fault measurements can be processed dynamically in real-time to provide the filtered values of height difference between benchmarks or baseline length at different time in     

Cost-effective network design for groundwater flow monitoring

The extensive use of groundwater resources has increased the need for developing cost-effective monitoring networks to provide an indication of the degree to which the subsurface environment has been affected by human activities. This study presents a cost-effective approach to the design of groundwater flow monitoring networks. The groundwater network design is formulated with two problem formats: maximizing the statistical monitoring power for specified budget constraint and minimizing monitoring cost for statistical power requirement. The statistical monitoring power constraint is introduced with an information reliability threshold value. A branch and bound technique is employed to select the optimal solution from a discrete set of possible network alternatives. The method is tested to the design of groundwater flow monitoring problem in the Pomona County, California.