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.     

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。     

鲁棒变结构制导规律研究

研究存在相对速度测量噪声时的鲁棒制导问题，根据一类变结构制导规律，分析了相对速度测量噪声、制导参数对导引收敛性的影响，以弹道收敛为准则，给出了实现鲁棒制导的条件，研究结果对设计先进的雷达制导系统具有重要意义。     

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。     

刀刃法在轨MTF测量性能分析

文章主要研究采用刀刃法测量在轨遥感器的MTF。刀刃法MTF测量准确程度如何，需要有一个定量的客观的评价，文章用仿真的方法对MTF测量精度进行了检验，对于噪声对MTF的影响进行了研究。     

压控振荡器品质因数与其相位噪声的关系

讨论了压控振荡器的相位噪声与其品质因数的关系,某实际压控振荡器的相噪测试结果验证了经理论推导的相位噪声谱的正确性。     

一种高速低噪声信号处理电路的方案研究

文章针对中国遥感高分辨率传输型相机的发展趋势，提出了一种高速低噪声的遥感CCD相机信号处理电路的设计方案。从信号完整性理论出发，利用Cadence软件进行了仿真与验证，取得了良好的效果。