一种宽响应带通滤波器的设计

本文介绍一种由四参差调谐回路和反相输入模拟加法器构成的宽响应带通滤波器,并给出电路结构,实验测试和结果。     

航空重力测量中数字滤波器的设计与应用

根据航空重力测量的要求以及滤波器的性能特点, 选择设计了适用于航空重力测量中ＧＰＳ高精度确定垂直扰动加速度的ＦＩＲ 低通滤波器和ＦＩＲ 低通微分器。并通过模拟数据的检测, 证明所设计的滤波器质量令人满意。     

Biases and accuracy of, and an alternative to, discrete nonlinear filters

The biases and accuracy of the extended Kalman filter (EKF) and a second-order nonlinear filter (SONF) are discussed from the point of view of a frequentist; these are often derived by applying the relevant conditional quantities to the linear Kalman algorithm under the Bayesian framework. The EKF and the SONF are biased, although the SONF has been derived in the hope of improving first-order filters. Unfortunately the biases of the SONF may be magnified further, because the second-order terms of the relevant Bayesian conditional quantities have never been properly used to derive the SONF from the frequentist point of view. The variance–covariance matrix of the SONF given in the literature is proven to be incorrect up to the second-order approximation, and the correct one is derived. Finally, also from the point of view of a frequentist, an alternative, almost unbiased SONF is proposed, if the randomness of partials is neglected. Received: 12 July 1997 / Accepted: 5 October 1998     

相关估计显著水平的Monte Carlo模拟检验

相关分析技术是多种研究领域常用的数值处理工具,本文应用蒙特 罗方法,通过大量的数值计算,获得一个容量大,稳定性好的相关系数临界值表。对于数字滤波的情形,蒙特卡罗模拟结果表明,样本自由度降低到滤波前的ｘ分之一。其中,ｘ为奈魁斯特频率与滤波器通频带宽度的比值。文中还给出两个资料分析的应用实便。     

Improving hydrodynamic modeling of river networks by incorporating data assimilation using a particle filter

Numerical modeling is a well-recognized method for studying the hydrodynamic processes in river networks. Multi-source measurements also offer abundant information on the patterns and mechanisms within the processes. Therefore, improving hydrodynamic modeling of river networks through the use of data assimilation techniques has become a hot research topic in recent years. The particle filter (PF) is a commonly used data assimilation method and has been proven to be applicable to various nonlinear and non-Gaussian models. In the current study, an improved numerical hydrodynamic model for large-scale river networks is established by incorporating the advanced PF algorithm. Furthermore, the PF method based on the Gaussian likelihood function (GLF) and the method based on the Cauchy likelihood function (CLF) are compared for a complex river network scenario. The feasibility of the PF-based methods was evaluated through application to the Yangtze-Dongting River-lake Network (YDRN) by assimilating water stage data collected at six hydrometric stations during the entire hydrodynamic process in 2003. Additionally, the parameters used in the likelihood function, which affect the assimilation performance, also were explored in the current study. The study results found that the accuracy of the model-derived water stage data was improved when the PF-based methods are utilized, with improvement not only at the data assimilation (calibration) sites but also at three hydrometric stations not used in the data assimilation (i.e., verification sites). The highest average Nash-Sutcliffe Efficiency result for the six assimilation sites were 0.98 while the lowest summed root-mean-square-error result was 1.801 m. The comparison results also indicated that the CLF-based PF outperformed the GLF-based PF when high-accuracy observed data are available. Specifically, the CLF can effectively resolve the filtering failure problem and the dispersion problem of PFs, and further improve the accuracy of the filtering results for a river network scenario. In summary, the CLF-based PF method along with high-accuracy observation data shows promise to provide reliable reference and technical support for hydrodynamic modeling of large-scale river networks.     

基于DSP和CPLD的数字ADCP信号处理系统

利用声学多普勒流速剖面仪(ADCP)测量流速是20世纪80年代初发展起来的一种流速流量测验新技术。文章介绍了一种以DSP和CPLD为核心的数字ADCP信号处理系统,阐述了系统工作原理、系统结构和软硬件设计。系统以TMS320C5410芯片作为系统控制和信号处理的核心,采用数字滤波和直接数字合成技术为接收和发射模块,提高系统的速度到10ns运算级,极大的降低了输入输出信号的漂移,水体空间分辨率达到1m。     

Assessing the impact of distributed snow water equivalent calibration and assimilation of Copernicus snow water equivalent on modelled snow and streamflow performance

Accuracy of the Copernicus snow water equivalent (SWE) product and the impact of SWE calibration and assimilation on modelled SWE and streamflow was evaluated. Daily snowpack measurements were made at 12 locations from 2016 to 2019 across a 4104 km² mixed-forest basin in the Great Lakes region of central Ontario, Canada. Sub-basin daily SWE calculated from these sites, observed discharge, and lake levels were used to calibrate a hydrologic model developed using the Raven modelling framework. Copernicus SWE was bias corrected during the melt period using mean bias subtraction and was compared to daily basin average SWE calculated from the measured data. Bias corrected Copernicus SWE was assimilated into the models using a range of parameters and the parameterizations from the model calibration. The bias corrected Copernicus product agreed well with measured data and provided a good estimate of mean basin SWE demonstrating that the product shows promise for hydrology applications within the study region. Calibration to spatially distributed SWE substantially improved the basin scale SWE estimate while only slightly degrading the flow simulation demonstrating the value of including SWE in a multi-objective calibration formulation. The particle filter experiments yielded the best SWE estimation but moderately degraded the flow simulation. The particle filter experiments constrained by the calibrated snow parameters produced similar results to the experiments using the upper and lower bounds indicating that, in this study, model calibration prior to assimilation was not valuable. The calibrated models exhibited varying levels of skill in estimating SWE but demonstrated similar streamflow performance. This indicates that basin outlet streamflow can be accurately estimated using a model with a poor representation of distributed SWE. This may be sufficient for applications where estimating flow is the primary water management objective. However, in applications where understanding the physical processes of snow accumulation, melt and streamflow generation are important, such as assessing the impact of climate change on water resources, accurate representations of SWE are required and can be improved via multi-objective calibration or data assimilation, as demonstrated in this study.     

适用于海洋动态观测设备嵌入式系统的低功耗管理预测模型

能耗是制约海洋设备在水下工作时长的关键因素。为进一步降低海洋动态观测设备嵌入式系统的动态功耗, 本文针对前人提出的用于预测空闲时间的指数平滑算法所存在的权重系数基于凑数法确定、算法难以适应大波动等问题, 设计了一种新的权重系数, 并构建了一种自适应的低功耗管理预测模型。当模型检测到预测的空闲时间超过工作和休眠状态切换的时间阈值后, 中央处理器关停系统的部分外设, 使系统进入低功耗休眠状态。仿真和单片机实验均表明,本文提出的低功耗管理预测模型能够有效地提高对处理器工作的空闲时间预测的准确性, 且面对突发状况具有良好的自适应性, 可显著降低嵌入式系统的功耗, 有效延长设备的工作时间。     

理论模型分析卡尔曼滤波在航空全张量磁力梯度测量中的应用效果

航空全张量磁力梯度测量数据中包含非常复杂的运动噪声,在频谱图中从低频至高频均有分布,并以白噪声为主,如何有效压制运动噪声是一个较大的挑战.传统的数字滤波只能滤除指定频段的噪声,对于混叠在全张量磁力梯度有用信号中的噪声不能有效分离.鉴于卡尔曼滤波是一种快速、高效和实时的最优估计方法,笔者将其应用到航空全张量磁力梯度数据处...     

浚县地震台地磁秒采样数据高频干扰分析

为识别及分析浚县地震台地磁秒采样观测数据中的高频干扰成分,采用别尔采夫滤波剔除其日波及半日波,然后通过时频分析得到高频干扰时段。通过查询工作日志及进行毕奥萨伐尔定律分析,认为浚县地震台地磁秒采样数据所受高频干扰除磁暴外,主要来自电焊施工和雷电,同时发现2种干扰类型有不同的典型干扰形态。