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。     

一种顾及有色噪声的四星座GNSS动态导航滤波算法

经典Kalman滤波要求噪声是高斯白噪声,而动态GNSS定位的观测误差和状态预测误差往往是有色噪声。本文提出一种简便的有色噪声函数模型拟合滤波算法,采用前面历元的观测残差和状态残差建立有色噪声模型,削弱有色噪声对动态导航解算的影响。采用四星座GNSS接收机观测数据进行动态导航实验,结果表明,顾及有色噪声的动态导航滤波算法比未顾及有色噪声的经典Kalman滤波算法定位精度更高,三维位置精度提升9%以上。     

Ingestion of <Emphasis Type="Italic">Brachionus plicatilis</Emphasis> under different microalgae conditions

The effects of four microalgae,Chlorella vulgaris,Platymonas helgolandicavar,Isochrysis galbana,and Nitzschia closterium on the grazing and filtering rates of the marine rotifer,Brachionus plicatilis,were evaluated under laboratory conditions.The grazing rates in separate cultures of the four microalga were as follows:C.vulgaris > P.helgolandicavar > I.galbana > N.closterium.However,the filtering rates occurred in the following order:P.helgolandicavar > N.closterium > C.vulgaris > I.galbana.A mixed diets ex...     

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双偏振雷达差分传播相移的五种滤波方法对比分析

为了对双线偏振雷达的差分传播相移ΦDP进行滤波降噪处理,提高双线偏振雷达识别粒子、估测降水的能力。通过对C波段双线偏振雷达差分传播相移分别采用滑动平均、中值滤波、FIR滤波、卡尔曼滤波和小波分析5种不同方法地介绍,利用中国气象科学研究院灾害天气国家重点实验室移动式C波段双线偏振雷达(POLC)2013年外场试验观测资料,对比分析了经5种方法处理后的差分传播相移ΦDP径向数据,及其分别在降水估测中应用的效果。结果表明:采用FIR滤波方法、卡尔曼滤波方法和小波分析方法对ΦDP径向数据进行处理的效果比传统的滑动平均和中值滤波方法好;其中小波分析处理的ΦDP径向数据波动最小,再经过变距离法拟合的KDP数据的负值能够得到最有效地抑制,最后应用到R(KDP)降水估测中的精度最高。     

抗差卡尔曼滤波在聊城古建筑动态数据处理中的应用

古建筑在日照、风压等因素的影响下,易产生老化变形,一般会采用及时补救的方法,有时并没有分析其根本原因,本文在布设动态监控网,获得监控数据后,用抗差卡尔曼滤波对监控数据进行分析的方法,对变形方向进行预测,预测值与平差值的误差均在限差范围内,且变化方向大致相同,可以将它作为古建筑变形方向的预报,做到防患于未然。     

GPS车载导航的交互式多模型算法

GPS动态定位数据的处理广泛采用卡尔曼滤波技术,而应用卡尔曼滤波要求运动模型准确可靠,但由于载体真实运动的复杂多变,任何单一模型都难以全面描述,致使单一模型的滤波都容易出现模型误差。针对这一问题,将机动目标跟踪领域广泛应用的交互式多模型算法引入到车载导航中。通过分析车辆的运动特点,选取匀速直线模型和当前统计模型进行交互;同时考虑到车载终端计算能力有限,将状态变量在各方向解耦。仿真显示,在机动时改进的算法和单一模型的自适应算法基本相当,但在非机动时改进的算法明显占优。     

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.     

环流分解及其在沉积地层旋回分析中的应用

本文应用马尔柯夫链进行地层序列分析。当一个地层序列形成一个具有马尔柯夫性质和极限概率分布的马尔柯夫链时,它的转移概率矩阵可分解为细致平衡部分和环流部分。根据环流矩阵可确定该序列中的主要沉积旋回趋势,为地层序列分析提供重要依据。本文给出了两个研究实例。