Testing the correctness of the sequential algorithm for simulating Gaussian random fields

The sequential algorithm is widely used to simulate Gaussian random fields. However, a rigorous application of this algorithm is impractical and some simplifications are required, in particular a moving neighborhood has to be defined. To examine the effect of such restriction on the quality of the realizations, a reference case is presented and several parameters are reviewed, mainly the histogram, variogram, indicator variograms, as well as the ergodic fluctuations in the first and second-order statistics. The study concludes that, even in a favorable case where the simulated domain is large with respect to the range of the model, the realizations may poorly reproduce the second-order statistics and be inconsistent with the stationarity and ergodicity assumptions. Practical tips such as the multiple-grid strategy do not overcome these impediments. Finally, extending the original algorithm by using an ordinary kriging should be avoided, unless an intrinsic random function model is sought after.     

汶川地震同震形变场的GPS和InSAR邻轨平滑校正与断层滑移精化反演

为克服InSAR观测汶川地震同震形变场的邻轨不连续问题,提出联合GPS观测值与邻轨平滑约束的同震位移校正方法,采用GPS观测形变去除PALSAR轨道误差引入的残留平地相位,基于形变平滑条件校正邻轨干涉相位的不连续性.ALOS/PALSAR干涉处理结果表明,校正后同震形变场的准确度与平滑性得以显著提高,InSAR高相干点残差达3.6 cm,校正后精度提高约60%,低相干点精度提高约40%,校正后形变场的邻接平滑因子标准差减小约33%,验证了轨道误差校正与邻轨平滑约束方法的准确性与可靠性.进一步基于弹性半空间位错模型的断层滑移反演结果表明,断层滑移主要分布于映秀、北川和青川地区,集中于地壳深度0~16 km范围,最大滑动量（位于北川县城）约为9.0 m,GPS反演模型残差为5.5 cm,InSAR反演模型残差达9.2 cm,InSAR反演精度约有30%的显著提高,由模型反演计算得到的地震矩为8.0469×1020 N·m.     

检测前跟踪框架下利用蒙特卡洛算法的空间碎片跟踪策略研究（英文）

在轨卫星或者空间碎片数量的增多,是对空间目标地基自动观测的一个挑战。尽管北美防空司令部编目管理了绝大多数直径超过10 cm的空间物体,但由于轨道摄动,空间目标的位置信息(基于6个轨道根数)依然非常重要,并需要定期更新。在过去的几十年里,配备电子传感器的现代地基光电望远镜已广泛用于天体测量领域。然而,这种设备的跟踪性能主要取决于空间目标的大小和亮度。这些目标所在的天文图像会有不同的背景;而且,在基于凝视模式的短曝光实时观测过程中,运动目标和背景恒星在不同的信噪比下显示为类似的点扩散函数,难以辨认。本研究是为了实现对非高斯和动态背景的高灵敏度检测和跟踪能力的提高,并具有简单的系统机制和出色的计算效率。为突破该限制,将重点放在利用状态估计技术对微小卫星和暗弱目标进行跟踪上。提出一种基于神经网络的自适应运行高斯平均算法,用以从恒星背景及干扰下提取运动的空间目标。该方法随后被集成到了一个检测前跟踪框架中。该框架利用基于蒙特卡洛的粒子滤波跟踪空间目标。三段来自亚太地基光学空间目标观测系统(APOSOS)图像序列被用来对该跟踪策略进行评估。实验结果表明,该方法能够达到满意的跟踪性能。     

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。     

Improved estimators of correlation and R2 for skewed hydrologic data

ABSTRACT

The coefficient of determination R² and Pearson correlation coefficient ρ = R are standard metrics in hydrology for the evaluation of the goodness of fit between model simulations and observations, and as measures of the degree of dependence of one variable upon another. We show that the standard product moment estimator of ρ, termed r, while well-behaved for bivariate normal data, is upward biased and highly variable for bivariate non-normal data. We introduce three alternative estimators of ρ which are nearly unbiased and exhibit much less variability than r for non-normal data. We also document remarkable upward bias and tremendous increases in variability associated with r using both synthetic data and daily streamflow simulations from 905 calibrated rainfall–runoff models. We show that estimators of ρ = R accounting for skewness are needed for daily streamflow series because they exhibit high variability and skewness compared to, for example, monthly/annual series, where r should perform well.     

Image smoothing of multispectral imagery based on the HNN and geo-statistics

A new method for image down-scaling using geostatistical interpolation or smoothing based on the Hopfi eld Neural Network (HNN) and zero semivariance value is introduced. The method utilises the smoothing effect of the semivariogram matching process to produce the smoothened sub-pixel multispectral (MS) image with smaller RMSEs in comparison with the bilinear interpolation. In fact, the zero semivariograms increase the spatial correlation between the adjacent sub-pixels of the superresolution image. Containing higher spatial correlation, the resulting super-resolution MS image has smaller RMSEs compared with the original coarse image.     

B样条与磨光样条在基于矩形格网的DEM内插中的应用

本文研究了Ｂ样条和磨光样条应用在基于矩形格网的ＤＥＭ内插中的思想、方法及实现过程。并从逼真性,保凸性,光滑性,运算速度等方面对Ｂ样条、磨光样条与双线性内插算法做了实验比较。理论和实验表明,所述方法具有较好的效果。     

Exact computation of Feynman-type integrals involving Gaussian random fields

We calculate explicitly some expectations (integrals over Hilbert spaces) of functionals of Gaussian random fields. Our work is inspired by the formulas for the harmonic oscillator. We also show how to do similar calculations by considering continuum limits of sequences of coupled harmonic oscillators. The results obtained in this work have applications in the study of random media, renormalization and scaling, and in engineering perturbation analysis.     

融合GNSS和加速度计监测数据的超高建筑动态特性分析

GNSS和加速度计是目前动态监测超高建筑环境载荷变形的主要手段。GNSS具有无需通视、可直接获取三维位移等优点,但受精度和采样率的限制,其对微变形及高频振动信息不敏感;而加速度计具有高精度和高采样率等优点,但无法监测超高建筑低频的似静态变形。为充分发挥这两种传感器的各自优势,提出利用多速率Kalman滤波和RTS平滑方法对超高建筑GNSS和加速度计监测数据进行融合处理。试验结果表明,与单一的GNSS监测技术相比,该方法有利于削弱GNSS高频噪声的影响,提高位移数据的采样率,可有效识别超高建筑的低频和高频振动频率,提高对微变形振动的监测能力;与单一的加速度计监测技术相比,该方法可以准确监测超高建筑的低频变形信息,具有良好的工程应用价值。