基于小波包分析的地震资料联合去噪方法研究

在地震记录中,随机噪声严重影响了有效信号的提取,为此必须进行消噪处理。这里首先使用小波包变换对不同频段的信号进行精细分离,有效信号和噪声经小波包分解后,其小波包系数将表现出不同特性,然后根据这种不同特性进行去噪处理,对小波包分析法处理后的剩余地震信号再进行KL(Karhunen-Loeve)变换,提取相关有效信号,最后对提取的有效信号进行中值滤波处理,进一步去除剩余噪声。经合成地震剖面和实际地震剖面处理实验证明,小波包分析、KL变换和中值滤波联合去噪方法,能有效地消除较强的随机噪声,提高地震剖面信噪比和分辨率。     

承压含水层非完整反滤回灌井的稳定流计算

反滤回灌井是地下水库中一种有效的回灌设施,它由回灌井和井口反滤层组成。非完整反滤回灌井井流运动由砂反滤层的竖向流和非完整回灌井井流组合而成。文中提出了承压含水层非完整反滤回灌井稳定流的计算方法,分析了反滤层、井损和回灌堵塞等因素对回灌量的影响,并结合实例证明了反滤回灌井回灌量大大低于普通回灌井的回灌量。     

Geography of asbestos contamination near the World Trade Center site

Despite the dust cleanup and indoor air testing program led by the U.S. Environmental Protection Agency (EPA) and offered to all residents of Lower Manhattan (south of Canal Street), concern remains about local chemical residues from the collapse of the World Trade Center (WTC) buildings. Data on post-cleanup indoor airborne asbestos concentration, available from EPA Region 2, were analyzed to assess the possibility that the WTC site is the source of geographically concentrated rare post-cleanup exceedances of the health-based standard for asbestos. Recognizing that these rare exceedances may be attributable to sources other than the WTC disaster, and that these sources are very likely to exhibit geographic patterns, the data were analyzed using a spatial filter specification of the auto-Poisson probability model. Our analysis shows that ignoring geographic patterns latent in these exceedances affects the empirical probability of exceeding the health-based standards for airborne asbestos. We did not find any statistically-significant geographic pattern in the exceedance events that would indicate the WTC site as the source of the post-cleanup exceedances. Apparent geographic patterns may be due to the geographic variability in sampling intensity. Our analysis indicates the Residential Dust Cleanup Program lead by EPA Region 2 has been effective at reducing the concentration of air-borne asbestos in indoor air to below the health-based benchmark.     

数字滤波器在高台地震台地震记录日常分析中的应用

简要介绍了滤波器的一般原理与Butterworth低通滤波器、高通滤波器和带通滤波器在高台地震台日常工作中的应用。     

Fast ensemble smoothing

Smoothing is essential to many oceanographic, meteorological, and hydrological applications. There are two predominant classes of smoothing problems. The first is fixed-interval smoothing, where the objective is to estimate model states within a time interval using all available observations in the interval. The second is fixed-lag smoothing, where the objective is to sequentially estimate model states over a fixed or indefinitely growing interval by restricting the influence of observations within a fixed window of time ahead of the evolving estimation time. In this paper, we use an ensemble-based approach to fixed-interval and fixed-lag smoothing, and synthesize two algorithms. The first algorithm is a fixed-interval smoother whose computation time is linear in the interval. The second algorithm is a fixed-lag smoother whose computation time is independent of the lag length. The complexity of these algorithms is presented, shown to improve upon existing implementations and verified with identical-twin experiments conducted with the Lorenz-95 system. Results suggest that ensemble methods yield efficient fixed-interval and fixed-lag smoothing solutions in the sense that the additional increment for smoothing is a small fraction of either filtering or model propagation costs in a practical ensemble application. We also show that fixed-interval smoothing can perform as fast as fixed-lag smoothing, and it may not be necessary to use a fixed-lag approximation for computational savings alone.     

岩土力学参数空间变异性的集合卡尔曼滤波佶值

岩土参数具有结构性和随机性的空间变异特征，该特征导致岩土参数具有不确定性。以地质统计学作为岩土参数空间变异性分析的理论基础，将分布于研究区的岩土参数视为区域化变量，变异函数既描述了岩土参数整体的空间结构性变化，又描述了其局部的随机性变化，用变异函数理论模型作为描述岩土参数空间变异规律的数学模型。引入集合卡尔曼滤波（EnKF）分析方法，利用时空分布的观测数据，对岩土参数空间变异性进行估值。数值算例表明，EnKF能够有效地融合观测数据，较好地提供岩土参数空间变异性的估值。     

两种渐消滤波与自适应抗差滤波的综合比较分析(英文)

Two kinds of fading filters and their principles are introduced. An adaptive robust filter is given with corresponding principle. The basic abilities of the fading filters and adaptively robust filter in controlling the in- fluences of the kinematic model errors are analyzed. A practical example is given. The results of the fading filter and adaptively robust filter are compared and analyzed.     

UKF在惯性/重力组合导航中的应用

将UKF(Unscented Kalman Filter)方法用于惯性/重力组合导航系统。UKF方法设计了少量的呈高斯分布的σ点,在每个更新过程中,σ点随着非线性状态方程和测量方程传播,从而获得滤波值及较高的计算精度,而且避免了对非线性方程的线性化过程。仿真结果表明:UKF方法比传统卡尔曼滤波及其改进的滤波模型都有更高的估计精度,并能有效的克服非线性严重时出现的滤波发散问题。     

一种迭代的GPS／INS组合导航滤波算法

简要介绍了GPS/INS松组合导航系统状态方程和观测方程。针对标准Kalman滤波算法存在的状态方程截断误差、噪声统计特性的不确定性以及状态扰动异常的影响,给出了一种应用于GPS/INS组合导航系统的迭代滤波算法。该算法采用迭代策略,不断利用观测信息实时修正状态预报值。实测数据计算结果表明,通过对状态预报值的实时修正,该算法能够很好地抑制状态预报信息的不确定性和扰动异常等对导航解的影响。其滤波解精度明显优于标准Kalman滤波。     

有色噪声作用下的抗差卡尔曼滤波

根据用GPS载波相位三差观测量进行动态定位或精密导航的需求,推导了动态噪声、观测噪声为有色噪声的抗差卡尔曼滤波公式。白噪声的抗差卡尔曼滤波是有色噪声的抗差卡尔曼滤波的特例,有色噪声的抗差卡尔曼滤波为白噪声的抗差卡尔曼滤波的推广。