粒子像斑三维定位的透视成像原理和方法

在三维粒子成像测速（ＰＩＶ）方面,可运用体积光照明同时从不同光轴用多个照相机获得ＰＩＶ图像,如何根据这些不同光轴获得的ＰＩＶ图像确定出粒子物点的空间位置是实现三维粒子成像测速的前提。基于此,提出了根据多幅不同光轴的ＰＩＶ图像的粒子像斑实现粒子物点三维定位的透视成像定位原理和方法。精确确定透视平面与透视中心在空间的位置是实现粒子物点三维定位的关键,妆测定透视中心（照相机的光学中心）和透视平面在空间的     

激光型基准平台的研制

介绍了一种新型的激光型基准平台.该平台运用重力摆技术使光平台在一定范围内达到了自动安平的功能;运用激光在球面镜单根母线上的光学成像原理、光学补偿技术,解决了宽范围正交光平面的聚集问题;输出了两条正交的水平光基准面与垂直光基准面,通过水平旋转机构与支架升降机构实现了两基准面上、下、左、右位置的任意移动,并保持输出信号基本特性不变.     

空间自旋目标宽带雷达干涉三维成像方法

空间目标三维成像可为目标的特征提取、分类与识别提供重要依据。基于L型三天线干涉成像原理,提出了一种宽带雷达条件下空间自旋目标干涉三维成像方法。首先,分析了雷达发射线性调频(LFM)信号条件下,空间自旋目标在距离-慢时间平面上的成像特点,建立了基于距离-慢时间平面的空间自旋目标干涉三维成像模型;其次,针对建立的干涉三维成像模型中,不同散射点的回波在距离-慢时间平面上会相互交叠的问题,对回波曲线分离、交叉点处理以及一维距离旁瓣的影响等进行了讨论,并给出了解决方法,从而获得目标三维图像。与已有方法相比,该方法可有效克服单基雷达三维成像无法获得目标各散射点真实三维位置以及在双/多基雷达三维成像时多部雷达回波联合处理较困难的问题。最后,仿真实验结果验证了所提方法的有效性。     

平面应力裂端约束与J控制裂纹稳态扩展

利用有限元法计算模拟了紧凑拉伸和中心裂纹两种试样在Ⅰ型平面应力条件下的裂纹准静态扩展过程。结果表明:两种不同的薄板试样中扩展裂纹尖端约束和应力场完全满足静态裂纹HRR奇异性解的相应要求,即对于扩展裂纹J主导裂端场条件依然有效。值得注意的是:与平面应变情形相反,在平面应力条件下,较高的J主导水平发生在纯拉伸条件下,而较低的J主导水平发生在纯弯曲条件。由两种试样实测及有限元计算模拟的平面应力J阻力曲线符合良好。因而,作为一个独立于试样几何的准则,平面应力J阻力曲线适于表征材料抵抗裂纹稳态扩展阻力,并且能够合理地用于评估给定材料状态条件下的薄壁含裂纹构件和结构的安全性。     

轨道运动对高轨卫星成像的影响及补偿

针对三轴稳定静止轨道气象卫星图像运动补偿技术,分析了轨道运动误差源对有效载荷成像仪成像光轴的影响.基于轨道确定数据,采用空间成像矢量修正方法,对轨道运动引起的光轴偏离进行补偿.根据高分辨率成像对光轴高指向精度的指标要求,研究了轨道确定误差和有效载荷伺服控制系统误差对图像配准精度的影响关系,并指出了进一步提高图像配准精度的措施.仿真结果表明了补偿方法的可行性.     

火箭助推器对雷达观测的影响研究

针对运载火箭二级助推器及分离时产生的大的碎片对雷达观测可能造成的影响,阐述了雷达成像重叠轨道(ROIO)的概念,并就雷达处于火箭载荷轨道平面内的情况分析了ROIO的存在条件、确定方法和观测中火箭载荷轨道及其ROIO上所对应的位置相对于雷达的角度差.仿真结果表明,目标轨道的观测范围及雷达相对于该观测范围的距离决定了ROIO的确定.     

标准轨迹制导中准平衡滑翔条件优化研究

对于可重复使用运载器标准轨迹再入制导,准平衡滑翔条件可以将高度-速度平面内各项再入约束形成的飞行走廊,转换为倾侧角-速度空间内的倾侧角走廊.通过在倾侧角走廊内设计倾侧角曲线,可以生成满足飞行走廊的标准轨迹.通过论证标准轨迹再入制导过程中的准平衡滑翔条件及其物理意义,说明了由倾侧角走廊内的倾侧角曲线生成的标准轨迹,存在突破再入飞行走廊边界的可能性.通过对倾侧角走廊边界设置余度,极大地降低了标准轨迹突破再入飞行走廊边界的可能性,提高了标准轨迹的设计成功率.     

不同加载应变率下有机玻璃的压缩破坏与力学行为

对有机玻璃试件进行准静态和动态压缩试验,研究加载应变率对有机玻璃材料力学性能的影响,分析不同加载应变率下有机玻璃材料的微观损伤破坏模式.通过简化黏弹性本构方程拟合出适用于有机玻璃材料的黏弹性模型参数,并与试验结果进行比较.结果表明:在准静态加载条件下,有机玻璃表现为延性破坏,在动态加载条件下则表现为脆性破坏;随着加载应变率的提高,有机玻璃的流动应力明显增加,且动态加载条件下的峰值应力增加速率高于准静态.     

一种基于重叠子孔径回波信息的SAR图像配准算法

合成孔径雷达（SAR）图像配准是寻找多幅SAR图像之间的几何变换关系的过程，使不同图像校正到统一空间坐标系。传统光学图像配准方法，如尺度不变特征变换（SIFT）结合随机抽样一致（RANSAC）用于SAR图像配准时，由于受到乘性相干斑噪声的干扰，配准性能受到较大影响。提出一种基于重叠子孔径回波信息的SAR图像配准算法，在对SAR回波复数据进行成像处理的过程中，利用相位信息并结合子孔径自聚焦方法得到强相关的重叠子孔径图像，并利用多图像配准方法实现成像孔径内和孔径间的子孔径图像配准，提高图像配准精度。多个不同场景的实测数据处理结果表明：所提算法相比于SIFT+RANSAC算法，同名点数量增加，误匹配点对减少，均方根误差减小，对相干斑噪声具有较强的鲁棒性，配准效果得到了显著提高。     

天/地基多平台空间目标光电观测时效性分析

针对如何部署光学探测设备才能更好实现对空间目标的高精度高频度监视问题,考虑光照条件、相对关系及探测性能,构建了天/地基空间目标探测与成像仿真模型;按照轨道特征选取了94颗LEO（Low Earth Orbit,低地球轨道）卫星、63颗GEO（Geosynchronous Earth Orbit,地球同步轨道）卫星和18颗大椭圆轨道卫星,选用春夏秋冬典型季节的特定时间长度,仿真分析了国内地基、南北极科考站、LEO卫星、准GEO卫星等多平台光电手段的位置探测和成像观测能力;比对分析地基平台纬度和季节、天基平台轨道高度和倾角对探测能力的影响得出：南北极科考站相比于国内站点可提高重点季节的探测时效性,98°倾角LEO平台对低轨目标成像时效性方面更具优势,等.在此基础上,提出了我国空间目标光电观测设备天地一体的布局构想.     

图像匹配中的相似性度量比较与分析

图像匹配作为一种重要的图像处理技术是图像信息融合、目标定位、变化检测、图像重建等后续工作的重要基础.选择合适的相似性度量对于图像匹配的结果至关重要.分析和讨论了图像匹配中常用的相似性度量;针对典型的基于灰度统计的图像匹配方法SSDA,实验比较了采用不同相似性度量对匹配结果的不同影响;对实验结果进行了分析和讨论,并得出了结论.     

Range-Doppler Imaging of Rotating Objects

During the integration time required to obtain fine Dopplerfrequency resolution in a range-Doppler imaging radar, a point on a rotating object may move through several range and Doppler resolution cells and produce a smeared image. This motion can be compensated by storing the appropriately processed return pulse, and the angular coordinates are determined by the angular coordinates of the radar antenna. The resulting stored data represents the three-dimensional Fourier transform of the object reflectivity density, and hence can be processed by an inverse Fourier transformation. Also included is an analysis of the three-dimensional radar/object geometry with separate source and receiver locations. The effects of various system aberrations are investigated and experimental results from a microwave test range which demonstrate the image improvement are presented.     

Video surveillance applications using multiple views of a scene

Automatic video surveillance techniques are used to detect intruders within a scene. This task is mostly reduced to the problem of detecting moving objects evaluating image sequences of a monocular camera. An essential problem of this monocular approach is its inability to measure the 3D-size and 3D-position of objects reliably, as object size and velocity are estimated within the 2D-image plane. To include 3D-information about the scene an approach using a second camera is proposed in this paper which combines the evaluation of the measurement data of the two cameras using an efficient 3D-scene model. Here, two cameras are used with an overlapping field of view, which represents an installation often used in existing video surveillance applications. It is shown that using the combined evaluation of the two cameras, the false detection rate in the case of moving shadows, leaves, birds and insects or blindings can be further reduced compared to a pure monocular evaluation     

Spatio-temporal pattern recognition using hidden Markov models

A spatio-temporal method for identifying objects contained in an image sequence is presented. The Hidden Markov Model (HMM) technique is used as the classification algorithm, making classification decisions based on a spatio-temporal sequence of observed object features. A five class problem is considered. Classification accuracies of 100% and 99.7%, are obtained for sequences of images generated over two separate regions of viewing positions. HMMs trained on image sequences of the objects moving in opposite directions showed a 98.1% successful classification rate by class and direction of movement. The HMM technique proved robust to image corruption with additive correlated noise and had a higher accuracy than a single-look nearest neighbor method. A real image sequence of one of the objects used was successfully recognized with the HMMs trained on synthetic data. This study shows the temporal changes that observed feature vectors undergo due to object motion hold information that can yield superior classification accuracy when compared with single-frame techniques     

“同翔”号无人机的升阻特性与纵向静稳定性

介绍了"同翔"号无人机设计的基本情况;采用涡格法气动软件AVL,对"同翔"号飞机的气动特性进行了理论分析,并根据计算结果讨论了该飞机的升阻特性和纵向静稳定性等。研究表明,"同翔"号无人机的气动性能良好,升阻特性及纵向静稳定性满足既定要求。     

基于ASM实现视频中物体的定位

对目标进行有效跟踪是目前许多国家获取信息的重要手段,主动形状模型(ASM)主要应用于灰度图像中物体的跟踪与定位,本文针对Koschan等提出的结合金字塔模型的ASM方法作进一步改进,使之应用于视频(本文视频采用MPEG数字视频压缩编码标准)中物体的定位:首先将视频解码还原成图像序列,从人眼视觉特征出发,将RGB颜色模型转换为HSV颜色模型,用色调信息取代灰度信息进行物体定位;并研究图像序列帧之间物体的重合度对提高定位效率的作用.实验结果说明在ASM中使用色调信息能有效地实现视频中的物体定位.     

利用图像相关等级的目标判别方法及其应用

提出一种根据PCA重构图像与原目标相关等级进行的目标识别方法,解决伪目标参与识别影响识别准确度的问题。首先建立目标模板库特征空间,将定位到的目标对象映入特征空间,利用PCA变换进行图像重构,定义降维重构图像与原目标之间的相关度函数,根据该函数判别图像等级;若原目标与其重构图像相似度很低,认定原目标为伪目标,将其剔除,不进入识别过程;若认定为真实目标后,根据相似性程度,分别选用降维重构图像或原图像作为识别对象,利用Hu不变矩距离分类器进行识别。该方法可有效剔除伪目标,并根据图像质量选用识别目标,提高了目标识别准确度,交通卡口获取的实测车辆图像车标识别试验验证了该方法的鲁棒性和有效性。     

应用复合型网格求解叶栅气动设计杂交型问题

建立在流线坐标系上的叶栅气动设计反命题与杂交命题是在映象平面(由流线坐标与周向坐标构成H上求解的.以往在映像平面只采用H型网格,本文首次将H加C型复合网格用于这类反命题计算,使叶栅前缘附近网格构造趋于合理,从而明显提高了计算精度.本文采用的解法是基于叶轮机气动变分原理的有限元方法.     

基于边缘区域增长法的飞机图像目标分割研究

对边缘区域增长算法进行了理论分析,介绍了用边缘区域增长法对飞机图像进行目标分割的主要步骤,并将该算法对飞机图像进行目标分割的效果与Otsu算法进行了对比。结果表明,该算法所分割的图像目标边缘和实际目标边缘一致性较好,边界精确、清晰。     

Detection of obstacles in the flight path of an aircraft

The National Aeronautics and Space Administration (NASA), along with members of the aircraft industry, recently developed technologies for a new supersonic aircraft. One of the technological areas considered for this aircraft is the use of video cameras and image-processing equipment to aid the pilot in detecting other aircraft in the sky. The detection techniques should provide high detection probability for obstacles that can vary from subpixel to a few pixels in size, while maintaining a low false alarm probability in the presence of noise and severe background clutter. Furthermore, the detection algorithms must be able to report such obstacles in a timely fashion, imposing severe constraints on their execution time. Approaches are described here to detect airborne obstacles on collision course and crossing trajectories in video images captured from an airborne aircraft. In both cases the approaches consist of an image-processing stage to identify possible obstacles followed by a tracking stage to distinguish between true obstacles and image clutter, based on their behavior. For collision course object detection, the image-processing stage uses morphological filter to remove large-sized clutter. To remove the remaining small-sized clutter, differences in the behavior of image translation and expansion of the corresponding features is used in the tracking stage. For crossing object detection, the image-processing stage uses low-stop filter and image differencing to separate stationary background clutter. The remaining clutter is removed in the tracking stage by assuming that the genuine object has a large signal strength, as well as a significant and consistent motion over a number of frames. The crossing object detection algorithm was implemented on a pipelined architecture from DataCube and runs in real time. Both algorithms have been successfully tested on flight tests conducted by NASA.