神经网络辅助的GPS/INS组合导航自适应滤波算法

首先利用预报残差构造的最优自适应因子设计GPS/INS组合导航自适应滤波器。并针对BP神经网络存在的训练速度慢、容易陷入局部极小等问题,给出网络的改进算法。利用神经网络对自适应滤波器状态方程的预报值进行在线修正,给出神经网络辅助的GPS/INS组合导航自适应滤波算法。最后,利用实测数据进行验证。结果表明,改进的神经网络算法明显提高网络收敛速度;两种自适应滤波算法相对标准组合导航算法都能够可靠地反映载体运动轨迹;神经网络辅助的GPS/INS组合导航自适应滤波算法相对GPS/INS组合导航自适应滤波算法在精度和可靠性方面又有明显提高。     

有偏迭代估计在短基线集形变模型中的应用

进行SBAS技术时,选择的干涉对一般会出现一景影像和其他几景影像干涉的现象,导致构建的线性形变模型病态。在这种情况下,最小二乘法求解SBAS线性形变模型已不太适合。针对这一问题,本文结合Liu估计的有偏迭代法在求解病态线性模型时能够克服病态性对结果的影响,提出将此方法应用到求解SBAS线性形变模型中。以覆盖济宁地区的13景ENVISAT ASAR数据展开了SBAS技术在城市地面沉降监测中的应用实验,分别利用LS法、基于Liu估计的有偏迭代法解算形变模型。结果表明,基于Liu估计的有偏迭代法获得研究区的年平均沉降速率标准差比LS法获得的低1.4,且其求解的结果相较于LS法获得的结果更准确、稳定。     

具有LMS稳健初值的选权迭代法

基于选权迭代法的基本理论,文中提出先用LMS稳健估计来确定残差的初值,然后再进行选权迭代方法。其估计结果既继承LMS方法的高失效点(BP)稳健性,又具有选权迭代法的高估计效率,其计算结果与无异常点时最小二乘估计结果基本一致。     

爬山法在影像匹配中的应用

对传统的爬山法进行改进,通过两个方向的整体搜索来预测峰值可能出现的区域,使其能很快的找到峰值位置。试验表明这种方法减少了相关系数的计算,提高匹配的速度并且保证了匹配的精度。     

基于DEM的USLE土壤侵蚀方程地形因子获取与分析

坡长和坡度是研究水土流失问题中必须要考虑的重要地形因子,坡长的空间分布特征和规律、地貌发育对坡长的影响,以及坡长与坡度之间的关系,是研究水土流失、侵蚀规律的重要条件之一。利用GIS以及相关软件为平台,在黑龙江省通河地区建立USLE水土流失方程模型,研究LS因子在水土流失中的影响以及作用,并探讨DEM数据分辨率变化对LS值的影响。     

Correlated V/R and infrared photometric variations in the Be/X-ray binary LS I +61° 235/RX J0146.9+6121

We report on the long-term variability of the Be/X-ray binary LS I +61° 235/RX J0146.9+6121. New optical spectroscopic and infrared photometric observations confirm the presence of global one-armed oscillations in the circumstellar disc of the Be star, and allow us to derive a V R band quasi-period of 1240±30 d. Pronounced shell events, reminiscent of the spectacular variations in Be stars, are also seen. We have found that the J , H and K infrared photometric bands vary in correlation with the spectroscopic V R variations, implying that the one-armed disc oscillations are prograde. The effect of the oscillations is not only seen in the H α line but is also seen in the He  i λ 6678 and Paschen lines. As these lines are formed at different radii in the equatorial disc of the Be star, such effects confirm the global nature of the perturbation. The Keplerian disc has been found to be denser than the average for a sample of isolated Be stars, which may be indicative of some kind of interaction with the compact companion. Finally, from a Rossi X-ray Timing Explorer observation we derive a spin period of the neutron star of 1404.5±0.5 s.     

瞬时属性估计器在探地雷达数据处理中的应用

为了提高浅层埋藏目标识别的瞬时物理属性的精度,根据极平坦频率特性有限脉冲相应滤波器的思想,首次提出用它作为微分器和延时器组成解析信号瞬时属性估计器（FIFM）,对探地雷达信号的瞬时属性进行提取。结果表明,瞬时属性剖面的分辨率得到了明显的提高;采用瞬时属性估计器进行探地雷达信号瞬时参数的研究是一种非常有效的方法,可用于公路、桥梁、隧道等结构物的无损检测数据分析。      

Stochastic inversion of pneumatic cross-hole tests and barometric pressure fluctuations in heterogeneous unsaturated formations

The distributions of permeability and porosity are key factors that control airflow and gas phase transport in unsaturated formations. To understand the behavior of flow and transport in such formations, characterization procedure is a typical approach that has been widely applied to laboratories and fields. As is recognized by most investigations, this approach relies on accurate measurements, and more importantly, an adequate tool to interpret those measurements from experiments. This study presents a pneumatic inverse model that is capable to estimate the distributions of permeability (k) and porosity () with high resolution in heterogeneous unsaturated formations. Based on the concept of sequential successive linear estimator (SSLE), the developed model accounts for compressibility and density of air and estimates the geologic parameters using air pressure measurements from sequential cross-hole pneumatic pumping or injection tests. Four synthetic examples, including a one-dimensional well-posed, a horizontally two-dimensional, and two three-dimensional problems, are used to evaluate the developed model in estimating the distributions of permeability and porosity in unsaturated formations. Results of the numerical experiments are promising. The developed pneumatic inverse model can reconstruct the property (i.e., permeability and porosity) fields if the well-defined conditions are met. With a relatively small number of available measurements, the proposed model can accurately capture the patterns and the magnitudes of estimated properties for unsaturated formations. Results of two complex three-dimensional examples show that the proposed model can map the fracture connectivity using a small number of subsurface pressure measurements and estimate k and in shallow soil layers using spatial variations of barometric pressure.     

Spatial interpolation of marine environment data using P-MSN

ABSTRACT

When a marine study area is large, the environmental variables often present spatially stratified non-homogeneity, violating the spatial second-order stationary assumption. The stratified non-homogeneous surface can be divided into several stationary strata with different means or variances, but still with close relationships between neighboring strata. To give the best linear-unbiased estimator for those environmental variables, an interpolated version of the mean of the surface with stratified non-homogeneity (MSN) method called point mean of the surface with stratified non-homogeneity (P-MSN) was derived. P-MSN distinguishes the spatial mean and variogram in different strata and borrows information from neighboring strata to improve the interpolation precision near the strata boundary. This paper also introduces the implementation of this method, and its performance is demonstrated in two case studies, one using ocean color remote sensing data, and the other using marine environment monitoring data. The predictions of P-MSN were compared with ordinary kriging, stratified kriging, kriging with an external drift, and empirical Bayesian kriging, the most frequently used methods that can handle some extent of spatial non-homogeneity. The results illustrated that for spatially stratified non-homogeneous environmental variables, P-MSN outperforms other methods by simultaneously improving interpolation precision and avoiding artificially abrupt changes along the strata boundaries.