二单元DPCA在机载相控阵雷达AMTI中的应用

二单元偏置相位中心天线技术 (DPCA)在机载相控阵雷达自适应动目标指示 (AMTI)中占有重要地位 ,其原理在很多文献中都有讨论。文中主要提出了将二单元DPCA应用到机载相控阵雷达的具体方法和实验步骤 ,针对接收数据是M×N矩阵的情况 ,分析了数据降维变换的具体过程 ,并从仿真结果中得到有效性证明。该方法对DPCA在实际工程中的应用具有重要参考价值     

Automatic fog detection and estimation of visibility distance through use of an onboard camera

In this paper, we will present a technique for measuring visibility distances under foggy weather conditions using a camera mounted onboard a moving vehicle. Our research has focused in particular on the problem of detecting daytime fog and estimating visibility distances; thanks to these efforts, an original method has been developed, tested and patented. The approach consists of dynamically implementing Koschmieder's law. Our method enables computing the meteorological visibility distance, a measure defined by the International Commission on Illumination (CIE) as the distance beyond which a black object of an appropriate dimension is perceived with a contrast of less than 5%. Our proposed solution is an original one, featuring the advantage of utilizing a single camera and necessitating the presence of just the road and sky in the scene. As opposed to other methods that require the explicit extraction of the road, this method offers fewer constraints by virtue of being applicable with no more than the extraction of a homogeneous surface containing a portion of the road and sky within the image. This image preprocessing also serves to identify the level of compatibility of the processed image with the set of Koschmieder's model hypotheses. Nicolas Hautiére graduated from the École Nationale des Travaux Publics de l'État, France (2002). He received his M.S. and Ph.D. degree in computer vision, respectively, in 2002 and 2005 from Saint-Étienne University (France). From 2002, he is a researcher in the Laboratoire Central des Ponts et Chaussées (LCPC), Paris, France. His research interests include trafic engineering, computer vision, and pattern recognition. Jean-Philippe Tarel graduated from the École Nationale des Ponts et Chaussées, Paris, France (1991). He received his Ph.D. degree in Applied Mathematics from Paris IX-Dauphine University in 1996 and he was with the Institut National de Recherche en Informatique et Automatique (INRIA) from 1991 to 1996. From 1997 to 1998, he was a research associate at Brown University, USA. From 1999, he is a researcher in the Laboratoire Central des Ponts et Chaussées (LCPC), Paris, France, and from 2001 to 2003 in the INRIA. His research interests include computer vision, pattern recognition, and shape modeling. Jean Lavenant graduated from the École Nationale des Travaux Publics de l'État, Lyon, France (2001). He received the M.S. degree in Computer Vision from Jean Monnet university of Saint-Étienne in 2001. In 2001, he was a researcher in the Laboratoire Central des Ponts et Chaussées (LCPC). In 2002, he was a system engineer in Chicago (USA). He is currently an engineer for the french ministry of transports. Didier Aubert received the M.S. and Ph.D. degree, respectively, in 1985 and 1989 from the National Polytechnical Institut of Grenoble (INPG). From 1989--1990, he worked as a research scientist on the development of an automatic road following system for the NAVLAB at Carnegie Mellon University. From 1990–1994, he worked in the research department of a private company (ITMI). During this period he was the project leader of several projects dealing with computer vision. He is currently a researcher at INRETS since 1995 and works on Road traffic measurements, crowd monitoring, automated highway systems, and driving assistance systems for vehicles. He is an image processing expert for several companies, teaches at Universities (Paris VI, Paris XI, ENPC, ENST) and is at the editorial board of RTS (Research - Transport - Safety).     

雷达间的电磁兼容性判决

通过对雷达信号(或干扰)处理过程的分析,对发现概率和虚警概率的定义作了合理的扩展,使二者可以直接用于雷达间的电磁兼容判定,并在此基础上建立了雷达间电磁兼容判决模型.这种基于经典雷达信号检测理论的模型能客观、真实地反映出雷达间的干扰情况,并且可以应用在雷达间电磁兼容性预测模型中.     

一种新颖的基于非压缩数字视频的水印盲检测算法

数字水印是一种嵌入到多媒体数据中用来进行版权标识的工具。在众多的宿主媒体中，数字视频因具有隐藏容量大、透明性好、鲁棒性强等诸多优点而受到日益广泛的关注。但是很多文献中提到的视频水印都是从数据流中提取单帧图像进行处理，这类算法与静态图像的水印方法如出一辙，没有充分利用视频文件的各种特性。而且对帧平均、视频压缩等常见的运动图像攻击方法十分敏感。针对这些问题，本文以非压缩视频文件为实验对象，结合人类视觉模型和彩色图像场景分割的方法，提出并实现了一种基于视频时间轴的数字水印盲检测算法。实验结果表明算法有效实用。     

雷达抗干扰中随机数产生技术分析研究

随机频率捷变和脉冲重复周期随机抖动可以使雷达具有较强的抗侦察、抗干扰能力。某型雷达具有伪随机频率捷变和脉冲周期参差捷变功能。本文分析了在该雷达上实现随机频率捷变和脉冲重复周期随机抖动的技术途径和可行性。     

传感器管理及其在相控阵雷达中的应用

传感器管理是数据融合的一部分。介绍了传感器管理的概念和框架 ,概述了国内外传感器管理算法的研究现状。主要工作是针对相控阵雷达这一传感器 ,通过对其不同工作模式以及不同参数的管理 ,来说明传感器管理的原理。提出了一种新的自适应采样周期算法 ,仿真结果表明该算法的优越性     

结合功率控制的时-空多用户检测器

针对CDMA系统中抗干扰技术,提出一种结合多用户检测、波束成形和功率控制的算法,对接收信号在时域和空间上进行联合处理,能大大抑制干扰,提高系统容量。     

一种基于HMM模型的弱小点目标的检测算法

讨论复杂背景、强干扰条件下移动平台下弱小目标的检测，提出一种基于隐Markov模型的快速检测算法，该算法通过计算摄像机视场的运动，消除背景的干扰，通过计算模型中的目标转移概率和似然函数，确定点目标的运动轨迹，实验表明了该算法的有效性。     

自由曲面五坐标数控加工干涉检查

提出了一种新方法，用于环刀五坐标数控加工的干涉检查。该方法将干涉检查分为刀轴及侧刃干涉检查和端面干涉检查。首先将加工曲面分片，选取合适的初始点。然后利用自由曲面的微分特性，确定跟踪方向和步长，迅速计算出工件和刀具的最短距离，从而判断是否发生干涉。实验仿真表明，达到同样精度时，该算法计算效率远高于常规的三角面片法。     

基于Gabor展开的水下目标激光探测的信号检测与识别

针对水下目标激光探测的信号检测与识别的问题 ,通过对回波信号的Gabor展开进行分析 ,建立了局部窗口多重相关的峰值检测方法 ,以及利用系数矩阵的迹和特征值描述目标的反射性能 ,实现了对目标的分类识别。实验表明 ,上述方法对目标的有效检测率达 93 0 % ,分类识别有效率达 83 2 %。