基于改进K-SVD字典学习方法的地震数据去噪

为实现更好的地震数据去噪技术,笔者引入一种新的算法:快速迭代收缩阀值法(FISTA),通过FISTA和K-奇异值分解(K-SVD)不断迭代更新K-SVD字典,利用更新得到的K-SVD字典对地震数据进行稀疏表示,去除稀疏系数中较小的数值,使数据中的随机噪声得到压制。对层状模型合成地震记录,Marmousi模型合成地震记录以及实际地震数据进行对比实验,得出FISTA算法较OMP算法能更好地提高地震数据的信噪比,同时有效地保护了反射信号。     

Geometric-constrained multi-view image matching method based on semi-global optimization

Targeting at a reliable image matching of multiple remote sensing images for the generation of digital surface models, this paper presents a geometric-constrained multi-view image matching method, based on an energy minimization framework. By employing a geometrical constraint, the cost value of the energy function was calculated from multiple images, and the cost value was aggregated in an image space using a semi-global optimization approach. A homography transform parameter calculation method is proposed for fast calculation of projection pixel on each image when calculating cost values. It is based on the known interior orientation parameters, exterior orientation parameters, and a given elevation value. For an efficient and reliable processing of multiple remote sensing images, the proposed matching method was performed via a coarse-to-fine strategy through image pyramid. Three sets of airborne remote sensing images were used to evaluate the performance of the proposed method. Results reveal that the multi-view image matching can improve matching reliability. Moreover, the experimental results show that the proposed method performs better than traditional methods.     

A geometric-based approach for road matching on multi-scale datasets using a genetic algorithm

Object matching is used in various applications including conflation, data quality assessment, updating, and multi-scale analysis. The objective of matching is to identify objects referring to the same entity. This article aims to present an optimization-based linear object-matching approach in multi-scale, multi-source datasets. By taking into account geometric criteria, the proposed approach uses real coded genetic algorithm (RCGA) and sensitivity analysis to identify corresponding objects. Moreover, in this approach, any initial dependency on empirical parameters such as buffer distance, threshold of spatial similarity degree, and weights of criteria is eliminated and, instead, the optimal values for these parameters are calculated for each dataset. Volunteered geographical information (VGI) and authoritative data with different scales and sources were used to assess the efficiency of the proposed approach. According to the results, in addition to an efficient performance in various datasets, the proposed approach was able to appropriately identify the corresponding objects in these datasets by achieving higher F-Score.     

低剖面紧凑的圆盘加载单极子天线

本文介绍了一种低剖面小型化圆盘加载单极子天线.通过盘加载的方式,在中心频率5.8 GHz处,首先将单极子天线的剖面从大约12.9 mm（0.25λ₀）降低到2 mm（0.039λ₀）,实现了低剖面的特性.加载在单极子天线上方的圆盘,尺寸大概为21 mm（0.41λ₀）,因此天线具有结构紧凑的特点.接着,为了使天线具有良好的匹配,在加载圆盘四周加入4个接地通孔,并且在馈电端口加入集总电感.最终,天线在中心工作频率5.8 GHz处实现了反射系数-15 dB的匹配性能.     

地磁匹配特征量的选择

论文旨在选择合适的地磁特征量用于匹配制导.从地磁匹配的实际要求出发,提出了选择匹配特征量时应重点考虑的几个因素,通过理论分析初步拟定了选取准则,并针对特定区域,依据IGRF(International Geomagnetic Reference Field)和WMM(World Magnetic Model)计算出的地磁数据,结合选取准则进行了综合分析,给出了初选结果,对地磁匹配基准图的制备、实时图的获取、匹配算法的研究,以及地磁场资源应用于其他领域的相关研究有一定的借鉴意义.     

微震研究与应用进展

随着地震观测台站密度的不断增加以及地震检测技术的快速发展,微震研究受到了地震学界的广泛关注.与发震周期较长的大地震相比,微震复发周期短、发生频次高,可以获得更高分辨率的地壳内部介质物性和应力状态等变化信息.微震在许多领域具有广泛的应用,如研究断层几何形态、前震与地震成核的关系、余震时空演化特征及余震触发机理、远程动态触...     

Discrimination of spurious self-correlation in nondimensionalized analyses of fluid dynamical data

Nondimensionalization of variables enables us to treat experiment data much more simply and efficiently by decreasing the number of variables. In some cases, trivial conclusions (which Kenney, 1982, called spurious self-correlation) result from a formal application of dimensional analyses. In contrast, in some cases fully significant conclusions can be derived. We first discuss how to construct nondimensional variables retaining the physical meanings of variables. We then propose simple and efficient methods, especially the use of “spurious triangle (SpT)”, to discriminate between significant conclusions and spurious self-correlations in the analysis of nondimensionalized variables.     

鄂尔多斯盆地西缘羊虎沟组物源区分析

鄂尔多斯盆地西缘羊虎沟组物源特征对天然气勘探尤为重要。通过砂岩的碎屑组分、岩屑组分、重矿物组合以及石英阴极发光等研究,认为研究区羊虎沟组受到北部、西南部、南部物源控制,各个方位物源在研究区中部吴忠—马家滩地区汇合。通过砂岩轻、重矿物组合和碎屑组分的Dickinson三角图解,以及泥岩的稀土元素特征等分析,认为研究区羊虎沟组源岩以大陆上地壳岩石为主。研究区北部砂岩物源区为再旋回造山带物源区,泥岩球粒陨石标准化稀土元素配分模式与阿拉善古陆浅变质岩相似,具有亲缘性;西南部及南部砂岩物源区为稳定陆块区和再旋回造山带物源区,泥岩球粒陨石标准化稀土元素配分模式与祁连—北秦岭造山带中浅变质岩相似。综上所述,研究区北部母岩主要为阿拉善古陆的浅变质岩夹少许火山岩,西南部及南部母岩主要为祁连—北秦岭造山带的中浅变质岩,其次为碳酸盐岩和火山岩。     

基于正交匹配追踪的声层析方法

声速剖面的变化会对声传播产生较大的影响,经验正交函数模型经常用来实现对声速剖面数据的简化描述。然而在内波、湍流等海水不均匀性存在时,这种正则化操作会造成声速重构精度的大幅降低。本文利用字典学习生成声速剖面的非正交原子,在稀疏编码时采用正交匹配追踪（OMP,Orthogonal Matching Pursuit）算法,更新字典则使用KSVD （Kernel Singular Value Decomposition）的字典更新算法。由于字典学习不需要强制使用正交条件,对于训练数据更加灵活,从而可以使用少数的原子组合达到更高的重构精度。利用一次浅海声学实验多次测量的声速剖面研究了海水声速剖面的经验正交函数表示和字典学习,研究表明：相比于正交函数表示,学习字典可以利用少数原子（甚至一个原子）更好的解释声速剖面扰动。字典学习可以提高声速剖面的稀疏性,从而提高声速剖面的反演精度。     

面向城区宽基线立体像对视角变化的结构自适应特征点匹配

提出一种基于结构自适应特征的城区宽基线影像特征点匹配方法。首先,对影像提取点特征和直线特征,挖掘点特征与其邻域内直线特征之间的几何关系,构建结构自适应的特征区域和特征描述符,并通过双向匹配策略获得初始匹配结果。然后,基于初匹配结果估计影像基础矩阵,构建核线约束的结构自适应特征匹配算法进行二次匹配。最后,将已匹配特征作为控制基础设计匹配扩展算法,进一步增加匹配点数量。本文方法以特征点邻域几何结构为出发点,构建自适应的特征区域,能够在显著的影像视角变化下,为同名特征点提取影像内容一致的特征区域,进而获得相似的特征描述符。试验结果证明,与传统算法相比,本文方法在城区宽基线影像上能够同时获得更多的正确匹配特征和更高的匹配正确率。