Improving orbit prediction accuracy through supervised machine learning

Due to the lack of information such as the space environment condition and resident space objects’ (RSOs’) body characteristics, current orbit predictions that are solely grounded on physics-based models may fail to achieve required accuracy for collision avoidance and have led to satellite collisions already. This paper presents a methodology to predict RSOs’ trajectories with higher accuracy than that of the current methods. Inspired by the machine learning (ML) theory through which the models are learned based on large amounts of observed data and the prediction is conducted without explicitly modeling space objects and space environment, the proposed ML approach integrates physics-based orbit prediction algorithms with a learning-based process that focuses on reducing the prediction errors. Using a simulation-based space catalog environment as the test bed, the paper demonstrates three types of generalization capability for the proposed ML approach: (1) the ML model can be used to improve the same RSO’s orbit information that is not available during the learning process but shares the same time interval as the training data; (2) the ML model can be used to improve predictions of the same RSO at future epochs; and (3) the ML model based on a RSO can be applied to other RSOs that share some common features.     

空时自适应处理张量波束成形器的外积合成法

为了解决空时自适应处理（Space-Time Adaptive Processing，STAP）对足量平稳训练快拍的要求，给出了一种设计STAP张量波束成形器的新算法——空时自适应处理张量子波束合成（TSS-STAP）法。分析表明：STAP中所需要的张量波束成形器，可首先在张量的各个子维度上分别进行子波束成形器的设计，然后再由张量的外积运算合成各子波束成形器而得到。进一步分析表明：由于本文算法可在较低自由度（DoF）的子维度上对张量波束成形器进行设计，因此降低了设计所需要的训练快拍数和计算复杂度，同时也实现了有效的去相关处理，使得其在非均匀杂波环境下有更好的目标检测性能。在仿真实验中，所提算法有效提升了目标检测结果，同时降低了目标检测所消耗的时间。     

A survey on life prediction of equipment

Once in the hands of end users, such durable equipment as spacecraft, aircraft, ships,automobiles, computers, etc. are in a state of debugging, working or storage. In either state, availability, reliability and super-efficiency are the ultimate goals, which have been achieved through constant monitoring as well as regular, preventive, routine and corrective maintenance. Although some advanced instruments can visualize certain invisible malfunctioning phenomena into visible ones, deeply hidden troubles cannot be found unless monitoring and testing data are addressed using tools that process the data statistically, analytically and mathematically. Some state-of-theart trouble-shooting and life-predicting techniques and approaches are introduced in this paper.     

多模切换控制方法及其在分导飞行器姿态机动控制中的应用研究

研究一类离散切换系统的鲁棒保性能状态反馈控制器设计问题。利用切换Lyapunov函数和线性矩阵不等式方法,得到了鲁棒保性能控制器存在的一个充分条件,给出了控制器的参数化表示,并将次优保性能控制器的设计问题转化为基于线性矩阵不等式约束下的凸优化问题。最后将所提理论应用于某飞行器的控制方案设计中,说明了本文所提设计方法的有效性。     

旋涡破裂对单独翼气动特性的影响及其工程估算方法

本文介绍了旋涡破裂对单独翼纵向和横向气动特性的影响,在分析和归纳实验数据的基础上,提出估算旋涡破裂对单独翼纵向和横向气动特性影响的工程方法。     

基于二分法的EKF SLAM算法

针对基于点特征的SLAM算法对实际环境描述运算量大的缺陷,提出了基于二分法的线特征SLAM仿真算法。通过判断机器人点到线特征直线的垂足所在位置选择不同的计算顺序,避免了直接求解带来的较大运算量。算法分析表明,该SLAM算法可以减少运算量,提高计算速度,并增强机器人的构图定位能力。基于该算法进行了仿真实验,实验结果表明,该算法有效地提高了运算速度,使得机器人可以更好地完成构图定位任务。     

软件无线电中FSK信号解调的一种快速算法

本文介绍了采用差分检波解调算法实现软件无线电中移频键控信号(FSK)快速解调方祛，并通过数字信号处理技术验证了该解调方祛。     

连续最小阶奇异滤波器

 本文讨论了当动态噪声统计特性未知时,奇异线性定常连续随机系统最小阶滤波器的设计问题。在系统部分观测量能精确测量的情况下,利用广义逆阵方法选择L矩阵,以消除动态噪声对降阶系统的影响,从而推导出缺动态噪声统计特性时的降阶奇异最优滤波器,其阶数为n-m+r。当量测方程奇异假设条件成立及引理有解时,本文证明了最小阶奇异滤波器必定存在。文中举例说明了这一降阶滤波方法的可行性。     

基于STF的Jerk模型自适应机动目标跟踪算法

在Jerk模型的基础上,提出了一种新的机动目标自适应跟踪算法STF-Jerk。该算法通过引入强跟踪滤波器(STF)的渐消因子,实时调节滤波器增益,增强了系统对突发机动的自适应跟踪能力,从而很好地改善了Jerk模型在跟踪机动目标时的跟踪精度。仿真结果表明,提出的STF-Jerk自适应跟踪算法显著提高了Jerk模型自适应算法的机动目标跟踪性能。     

涡轮叶片疲劳寿命公式及可靠性预测方法

本文推导了液体火箭发动机涡轮叶片疲劳寿命公式,并用概率统计、断裂力学方法,分析了可靠性预测方法.