空间机器人一体化仿真系统的研究与实现

为对空间机器人关键算法进行验证和评估,开发了一套一体化仿真系统。该系统基于模块化设计思想,由遥测遥控接口、轨迹规划与控制、系统动力学模型、系统3D几何模型、相机成像模型、图像处理与位姿测量、碰撞检测与安全预警等模块组成。其中,3D实体模型及仿真场景由OSG(Open Scene Graph)建立,各关键模块的算法采用C语言编程实现,可对空间机器人执行在轨任务的关键算法进行闭环验证。最后对两种典型工况进行了仿真实验,结果表明了该系统的有效性。     

Application of Analytic Redundancy-based Fault Diagnosis of Sensors to Onboard Maintenance System

Analytic redundancy-based fault diagnosis technique (ARFDT) is applied to onboard maintenance system (OMS). The principle of the proposed ARFDT scheme is to design a redundancy configuration using ARFDT to enhance the functions of redundancy management and built in test equipment (BITE) monitor. Redundancy configuration for dual-redundancy and analytic redundancy is proposed, in which, the fault diagnosis includes detection and isolation. In order to keep the balance between rapid diagnosis and binary hypothesis, a filter together with an elapsed time limit is designed for sequential probability ratio test (SPRT) in the process of isolation. Diagnosis results would be submitted to central maintenance computer (CMC) together with BITE information. Moreover, by adopting reconstruction, the designed method not only provides analytic redundancy to help redundancy management, but also compensates the output when both of the sensors of the same type are faulty. Our scheme is applied to an aircraft’s sensors in a simulation experiment, and the results show that the proposed filter SPRT (FSPRT) saves at least 50% of isolation time than Wald SPRT (WSPRT). Also, effectiveness, practicability and rapidity of the proposed scheme can be successfully achieved in OMS.     

基于Hartmann技术的微小自适应光学系统的研究

采用微小型自适应光学系统提高系统的分辨率具有非常广泛的应用前景。建立了基于Hartmann技术的波前处理机系统,利用MEMS微变形镜进行波前校正并对结果进行了分析,验证了利用微小自适应光学系统校正畸变波前的科学性,给出了建立实用高分辨率传输型微小自适应光学系统的可行性建议。     

提高发动机火警环路工作可靠性的探析

以一起发动机空中停车事件为例,对降低发动机火警环路工作的可靠性的原因进行了分析。当火警探测器的接线桩受到污染时,可能引起错误的故障信号,甚至引起火警警告。通过采用耐高温的密封胶,或者对其进行改装,以此来提高火警环路的工作可靠性。     

一种非规则采样航空时序数据异常检测方法

航天器遥测数据的实时异常检测对于航天任务具有重要意义。以往方法大都考虑规则采样且缺失率较低的时序数据,然而航空时序数据具有维度大、噪声多、缺失率高、采样间隔不规则等特点,因此异常检测任务较为困难。针对非规则采样且具有缺失值的多维航空时序数据提出非规则采样多维时序数据异常检测（IMAD）算法。首先,采用带有可训练迟滞项的门控循环单元（GRU-D）对缺失值和非规则采样的时序数据进行建模;然后,采用变分自编码器建立随机性模型,学习正常时序数据的分布,从而对噪声数据具有鲁棒性;最后,利用基于极值理论的自适应阈值确定法确定合适阈值进行异常检测。结果显示,在两个真实航空时序数据集上,IMAD具有超出当前最新异常检测算法的性能;多个实验表明,IMAD在缺失率、参数以及数据集变化时,能够维持较好的异常检测效果,具有较强的鲁棒性。     

应用灰度特征的行星陨石坑自主检测方法与着陆导航研究

针对陨石坑阴影不明显的行星着陆导航图像,提出了基于图像灰度值特征的陨石坑自主检测方法,通过兴趣区快速确定陨石坑边缘分布,解决了一般陨石坑检测方法对图像太阳高度角的依赖问题。利用检测出的陨石坑视线信息,采用非线性预测滤波方法估计着陆器着陆阶段的位置和姿态;鉴于视觉着陆导航对照了场景状况的高度依赖性,提出了一种利用分形理论和相邻点分级方法的天体随机地景建模方法。最后验证了所提方法的有效性。     

基于层次化分类器的遥感图像飞机目标检测

在大量航空航天遥感图像中,快速发现和统计飞机目标并对其进行准确定位,在军事和民用方面均具有重要意义。结合遥感图像特点,针对飞机目标的特征,文章设计了一种基于层次化的分类器的遥感图像飞机目标检测方法。首先用基于哈尔（Haar）特征的底层AdaBoost分类器快速去除大部分非目标区域;然后用基于梯度方向直方图（Histogram of Oriented Gradient,HOG）特征的顶层支持向量机（Support Vector Machine,SVM）分类器进行精细检测。在分辨率为1m的遥感图像数据集上的实验结果表明,层次化分类器在保证较高检测率的前提下,大大降低了虚警率,可以有效解决遥感图像飞机检测问题。     

基于能量检测法的统计特性分析

能量检测法是一种适用范围广泛的信号盲检测方法,而统计特性分析的准确估计是其应用的基础和前提。针对其检测量的统计特性分析,通过系统分析和理论推导,发现在仅有噪声输入的情况下,检测量服从卡平方分布;信号加噪声输入时的检测量服从非中心卡平方分布。最后利用详细的仿真分析验证了检测量统计特性分析的正确性,为能量检测法的应用提供了参考和依据。     

Integrated method for crater detection from topography and optical images and the new PH9224GT catalogue of Phobos impact craters

In a large majority of lunar and planetary surface images, impact craters are the most abundant geological features. Therefore, it is not surprising that crater detection algorithms (CDAs) are one of the most studied subjects of image processing and analysis in lunar and planetary science. In this work we are proposing an Integrated CDA, consisting of: (1) utilization of DEM (digital elevation map)-based CDA; (2) utilization of an optical-based CDA; (3) re-projection of used datasets and crater coordinates from normal to rotated view and back; (4) correction of the brightness and contrast of a used optical image; and (5) tile generation for the optical-based CDA and an assembling of results with an elimination of multiple detections, in combination with a pyramid approach down to the resolution of the available DEM image; and (6) a final integration of the results of DEM-based and optical-based CDAs, including a removal of duplicates. The proposed CDA is applied to one specific asteroid-like body, the small Martian moon Phobos. The experimental evaluation of the proposed CDA is done by a manual verification of crater-candidates and a search for uncatalogued craters. The evaluation has shown that the proposed CDA was used successfully for cataloging Phobos craters. The major result of this paper is the PH9224GT – currently the most complete global catalogue of the 9224 Phobos craters. The possible applications of the new catalogue are: (1) age estimations for any selected location; and (2) comparison/evaluation of the different chronology and production functions for Phobos. This confirms the practical applicability of the new Integrated CDA – an additional result of this paper, which can be used in order to considerably extend the current crater catalogues.     

基于双重分类深度学习的低空目标自动检测方法

由于图像数量多,因此准确、高效的目标检测是提升靶场光测图像处理自动化程度的关键步骤.针对低空目标图像及目标类型多、目标特性变化等情况导致传统目标检测算法适应性差的问题,提出了一种基于双重分类深度学习的低空目标自动检测方法.该方法基于深度学习目标检测框架YOLO V3,根据低空目标的亮度和形状的双重属性特征,将网络输出层...