Motion prediction of a non-cooperative space target

Capturing a non-cooperative space target is a tremendously challenging research topic. Effective acquisition of motion information of the space target is the premise to realize target capture. In this paper, motion prediction of a free-floating non-cooperative target in space is studied and a motion prediction algorithm is proposed. In order to predict the motion of the free-floating non-cooperative target, dynamic parameters of the target must be firstly identified (estimated), such as inertia, angular momentum and kinetic energy and so on; then the predicted motion of the target can be acquired by substituting these identified parameters into the Euler’s equations of the target. Accurate prediction needs precise identification. This paper presents an effective method to identify these dynamic parameters of a free-floating non-cooperative target. This method is based on two steps, (1) the rough estimation of the parameters is computed using the motion observation data to the target, and (2) the best estimation of the parameters is found by an optimization method. In the optimization problem, the objective function is based on the difference between the observed and the predicted motion, and the interior-point method (IPM) is chosen as the optimization algorithm, which starts at the rough estimate obtained in the first step and finds a global minimum to the objective function with the guidance of objective function’s gradient. So the speed of IPM searching for the global minimum is fast, and an accurate identification can be obtained in time. The numerical results show that the proposed motion prediction algorithm is able to predict the motion of the target.     

天基雷达高速微弱目标的积累检测

本文研究天基雷达高速微弱目标的相干积累检测问题。首先根据回波高阶相位影响包络补偿效果的程度对数据进行分段处理;然后对每个数据段采用速度滤波器组进行划分和Keystone变换补偿包络走动并结合分数阶傅立叶变换估计回波相位历程;最后利用最小二乘方法拟合出目标的运动参数并对目标回波进行长时间相干积累。仿真结果表明本文方法具有良好的高速微弱目标积累检测性能。     

旋转失效卫星的运动观测及消旋接触方案设计

以旋转失效卫星的消旋为研究背景,提出一种双重光流约束的特征点运动跟踪识别方法。该方法利用双目视觉,可实现对非合作旋转失效卫星的运动观测,并为机械臂消旋操作提供接触方案。首先,跟踪识别序列图像中稳定存在的特征点并记录其轨迹,采用频域分析的方法检测特征点轨迹的变化频率,从而获取目标旋转角速度,通过地面物理实验,验证所提目标运动观测的有效性;随后,利用特征点轨迹分析目标的运动包络与适宜接触区域,并根据目标运动特性和接触消旋的时间约束,给出完成消旋的接触强度约束,继而得到机械臂的操作性能需求,为接触式消旋的工程实践提供参考。     

关于地球卫星运动中的坐标系附加摄动问题

关于卫星运动中的坐标系附加摄动，早期是从两种赤道坐标系中卫星轨道根数的差别采用大量球面三角公式的方法导出的，本文将改用与当今高精度数值解中的坐标转换关系，在岁差章动等参数完全一致的情况下，简要清晰地导出相应的坐标系附加摄动解，既容易被读者接受，又便于与对应的数值解进行比对。     

面向飞机蒙皮对缝的移动机器人自主跟踪方法

提出一种面向飞机蒙皮对缝的移动机器人自主跟踪方法,用以解决大型蒙皮上表面装配对缝的自动化测量问题.移动机器人包括对缝测量模块和运动控制模块,对缝测量模块在测量对缝间隙阶差的同时得到机器人相对于对缝的位姿,运动控制模块控制机器人自主调姿.基于双线结构光与对缝的相对位置关系,提出机器人在不同情况下的自主调姿方法,解决了机器...     

遥感图像运动模糊恢复方法及评价标准研究

遥感成像系统与目标在曝光时间内的相对运动将导致成像的运动模糊。文章结合匀速直线运动造成的图像模糊特点,讨论图像模糊的产生机理并建立相关退化模型;利用点扩散函数（PSF）在频率域和空间域上分别对匀速直线运动产生的模糊图像进行恢复;验证各算法对高斯噪声的抗干扰性;提出使用HVS对比度的方法作为客观评价标准验证恢复算法的可行性,并与传统的灰度平均梯度（GMG）相对比表明该评价标准的合理性。     

基于UG和ADAMS的新型夹持器虚拟设计与仿真

采用UG和ADAMS研究了一种新型夹持器机构BHG-1的虚拟设计和仿真方法,运用UG来实现夹持器三维模型的虚拟设计和虚拟装配;运用ADAMS对夹持器夹持不同形状物体进行运动学和动力学仿真.通过对夹持器机构的虚拟设计和仿真,不但可以直观地了解夹持物体的具体过程,还可以通过仿真曲线了解其速度、加速度以及接触力的变化情况.     

滑移铰空间机器人基于分级Lyapunov方法的避障碍非完整运动规划

基于分级Lyapunov方法,讨论了载体姿态与位置均不受控制的滑移铰空间机器人末端运动轨迹的避障碍运动学规划问题.首先以系统动量矩守恒关系及运动.Jacobi关系为基础,建立了控制设计所需的系统状态方程及控制输出方程.此后,在Lyapunov函数的选取上采取分两级采取的方式,即初级Lyapunov函数确保滑移铰空间机器人的末端抓手从初始位置运动到指定的终点位置,次级Lyapunov函数则确保末端抓手避开工作空间中的障碍区域;两级合成则使空间机器人的末端抓手既实现了指定的位置移动又避开了障碍区域.系统数值仿真,证明了方法的有效性.     

Standing wave drift of hemispherical resonator with quality factor non-uniformity under a ring electrode excitation

Hemispherical Resonator Gyroscope(HRG) is a classical high precision Coriolis Vibration Gyroscope(CVG), which performs attitude estimation of carrier by detecting the precession of standing wave of resonator, thus, the drift of standing wave of resonator has a great influence on the output accuracy of gyroscope, where the quality factor nonuniformity of resonator is one of main error sources. Ring electrode is a classical excitation structure of HRG because the standing wave can precess freely u...     

Super-resolution reconstruction of astronomical images using time-scale adaptive normalized convolution

In this work, we describe a new multiframe Super-Resolution (SR) framework based on time-scale adaptive Normalized Convolution (NC), and apply it to astronomical images. The method mainly uses the conceptual basis of NC where each neighborhood of a signal is expressed in terms of the corresponding subspace expanded by the chosen polynomial basis function. Instead of the conventional NC, the introduced spatially adaptive filtering kernel is utilized as the applicability function of shape-adaptive NC, which fits the local image structure information including shape and orientation. This makes it possible to obtain image patches with the same modality, which are collected for polynomial expansion to maximize the signal-to-noise ratio and suppress aliasing artifacts across lines and edges. The robust signal certainty takes the confidence value at each point into account before a local polynomial expansion to minimize the influence of outliers. Finally, the temporal scale applicability is considered to omit accurate motion estimation since it is easy to result in annoying registration errors in real astronomical applications. Excellent SR reconstruction capability of the time-scale adaptive NC is demonstrated through fundamental experiments on both synthetic images and real astronomical images when compared with other SR reconstruction methods.