Manifold structure preservative for hyperspectral target detection

A nonparametric method termed as manifold structure preservative (MSP) is proposed in this paper for hyperspectral target detection. MSP transforms the feature space of data to maximize the separation between target and background signals. Moreover, it minimizes the reconstruction error of targets and preserves the topological structure of data in the projected feature space. MSP does not need to consider any distribution for target and background data. So, it can achieve accurate results in real scenarios due to avoiding unreliable assumptions. The proposed MSP detector is compared to several popular detectors and the experiments on a synthetic data and two real hyperspectral images indicate the superior ability of it in target detection.     

A robust object-based shadow detection method for cloud-free high resolution satellite images over urban areas and water bodies

Unwanted contrast in high resolution satellite images such as shadow areas directly affects the result of further processing in urban remote sensing images. Detecting and finding the precise position of shadows is critical in different remote sensing processing chains such as change detection, image classification and digital elevation model generation from stereo images. The spectral similarity between shadow areas, water bodies, and some dark asphalt roads makes the development of robust shadow detection algorithms challenging. In addition, most of the existing methods work on pixel-level and neglect the contextual information contained in neighboring pixels. In this paper, a new object-based shadow detection framework is introduced. In the proposed method a pixel-level shadow mask is built by extending established thresholding methods with a new C₄ index which enables to solve the ambiguity of shadow and water bodies. Then the pixel-based results are further processed in an object-based majority analysis to detect the final shadow objects. Four different high resolution satellite images are used to validate this new approach. The result shows the superiority of the proposed method over some state-of-the-art shadow detection method with an average of 96% in F-measure.     

在二元柔壁自适应风洞中利用面元法进行三元模型实验

简要叙述了在西北工业大学二元柔壁自适应风洞中利用面元法进行二元半机翼模型试验的研究情况，分析了面元法的基本思想和部分试验结果。     

八丝热线探针制作及其应用

介绍了八丝热线探针的制作工艺,有效地消除了各热丝探头之间的电信号干扰和动力学干扰。实验中使用该探针检测到了湍流边界层内的大尺度旋涡,并测量了它们的强度和尺度。与此同时还获得了速度、湍流强度和功率谱等流场参数,结果与现有典型数据一致。说明本文所述的多丝热线探针具有很强的实用性。     

故障检测与分离的广义一致性算子法

本文提出了故障检测与分离的广义一致性算子法的一般形式。得出了两个故障可分离的充要条件和多个故障可分离的充要条件。最后给出了检测和分离故障的过程。     

尾支杆干扰非线性修正方法的初步研究

利用CFD方法 ,采用两套网格重叠的形式 ,研究了一种对尾支杆干扰进行修正的非线性方法。运用本方法 ,研究了尾支杆等直段长度、直径和锥角对模型气动特性的影响 ,研究了四个模型有攻角时的尾支杆干扰 ,并对GBM 0 4A模型的零阻进行了尾支杆干扰的修正。     

跨音速翼型风洞的洞壁干扰研究

利用三个几何相似的 RAE104翼型模型,用实验方法确定西工大翼型风洞(TAWX)的无堵塞干扰开闭比。对于不带测压轨及带测压轨两种状态的开槽壁分别采用2%及4%开闭比可认为近似于无堵塞干扰。利用测压轨测量该翼型风洞上下壁附近控制面的静压分布,并利用快速富里叶变换法计算马赫数及迎角修正量。由 TAWX 风洞与西德 DFVLR TWB 风洞实验结果的比较可以看出,当迎角为零时,两者结果吻合较好,说明无堵塞干扰开闭比的确定基本上是正确的,经过快速富里叶变换法进行马赫数及迎角修正后的 TAWX 有升力的实验结果也与 TWB 结果接近。     

神经网络在未来超分辨雷达中的应用

最新的技术发展已为研制超分辨雷达创造了条件。它能够突破普通雷达基于匹配滤波原理的分辨能力,而实现超分辨。超分辨雷达的巨大计算量通常来自求解非线性最小二乘问题时的多维搜索。本文针对这一问题,研究了雷达信号处理中的两个典型例子:(1)利用阵列处理检测个数已知而方向未知的雷达目标;(2)对波音727飞机进行超分辨距离多普勒成像。说明Hop-field神经网络通过集体运算能够求解各种困难的最优化问题,因而在未来的超分辨雷达中有广阔的应用前景。     

一种适于动态环境的盲多用户检测算法

比较两种盲多用户检测算法在动态环境中的收敛性能,并通过计算机进行模拟仿真。其中一种是能随输入信号矢量变化而变化的变步长最小输出能量盲算法;另一种是既保持最小输出能量检测器的全局收敛性,又具有最小均方误差检测器高输出信干比优点的判决反馈变步长盲算法。利用前者在动态强干扰下收敛快及后者在稳态时输出信干比高的优势,将二者结合起来应用到动态环境中,提高系统性能,同时抑制多址干扰和窄带干扰。