一种模型误差鲁棒的卫星姿态确定方法

提出一种结合非线性预测滤波和二阶插值滤波实现基于星光/陀螺的高精度姿态确定的新算法.该算法用非线性预测滤波估计模型误差,再对补偿后的模型用高精度的二阶插值滤波来估计姿态参数.解决了在卫星实际运行中难以获得姿态确定系统的精确动力学模型,采用传统EKF(Extended Kalman Filter)将模型误差作为零均值白噪声处理,导致滤波精度降低甚至发散的问题.同时,二阶插值滤波将非线性模型按照二阶近似,无需计算函数偏导数,得到高精度的卫星姿态估计.仿真验证了该方法能有效地实时估计并补偿模型误差,提高了姿态估计的精度,且估计精度受滤波周期的影响不大,从而验证了算法的鲁棒性和有效性.      

A fatigue damage-cumulative model in peridynamics

While the present structural integrity evaluation method is based on the philosophy of assumed similitude, Fatigue and Damage Tolerance (F&DT) evaluations for next generation of air-vehicles require high-fidelity physical models within cyberspace. To serve the needs of F&DT evaluation in digital twin paradigm, a fatigue damage-cumulative model within peridynamic framework is proposed in this paper. Based on the concept of fatigue element block and damage accumulation law in form of Coffin-Manson relationship, the proposed model applies to both fatigue crack initiation and fatigue crack growth; fatigue crack growth rates under constant-amplitude and simple variable-amplitude block loading cases can be well predicted for three common structural materials without inputs of Paris law parameters. Additionally, the proposed model can also be easily extended to a probabilistic version; for verification, multiple-site-damage problems are simulated and the statistic nature of fatigue process in experiments can be well captured. In the end, main features of the proposed model are summarized, and distinctions from the other models are discussed. There may be a potential for the peridynamic damage-cumulative model proposed in this work to numerically predict fatigue problems in digital twin paradigm for future generations of aerospace vehicles.     

基于稀疏重建的MIMO-OTH雷达多模杂波抑制算法

针对由多模传播引起的多普勒扩展杂波(SDC)严重影响天波超视距雷达(OTHR)对慢速船舰目标的检测这一问题,在基于多输入多输出体制的新一代天波超视距(MIMO-OTH)雷达系统下,利用空域信息抑制多模SDC。传统处理方法需要目标角度先验信息,而在实际中,该信息往往很难获得。为此,提出一种新的基于稀疏重建的多模杂波抑制算法。该算法将二维的稀疏角度搜索转变为一维的角度搜索,使运算量大大降低,且估计出的收发角(DOA-DOD)自动配对,同时可获得各个传播路径下信号的时间多普勒信息,达到了理想的MIMO-OTH雷达多模杂波抑制效果。仿真结果证明了所提算法的有效性。     

失效卫星远距离相对位姿估计与优化方法

针对远距离非合作慢旋目标位姿估计精度问题,提出一种融合图像超分辨与视觉SLAM的相对位姿估计方法。算法主要包含3个步骤：通过梯度引导生成式对抗超分辨技术,提升目标图像的质量以获取更多更高质量的特征点;构建特征数据库实现当前帧与特征数据库的匹配,提升旋转目标的特征跟踪稳定性;利用图优化对多帧图像进行联合位姿优化,消除累计误差,得到更为精确的估计结果。为稳定网络的训练,将自然进化算法引入到对抗训练中。为增强模型的泛化性和鲁棒性,实验中的数据集采用半物理仿真获得。实验结果表明,当等效距离为25 m且失效卫星以25（°）/s的速度旋转时,目标图像经超分辨网络增强后,能够实现连续稳定的长时间测量。     

Effects of pressure oscillation on aerodynamic characteristics in an aero-engine combustor

The effects of pressure oscillation on aerodynamic characteristics in an aero-engine combustor are investigated. A combustor test rig is designed to simulate the pressure drop characteristics of a practical annular combustor. The pressure drop characteristics are firstly measured under atmosphere condition with non-reacting flow (or cold flow), and the air mass flow proportion of each component (dome/liner) are obtained; these properties are base lines for comparison with combustion state. The combustion tests are then carried out under conditions of inlet temperature 340–450 K, fuel air ratio 0.010–0.028. The stability map and the oscillation frequencies are obtained in the tests, the results show that pressure oscillation amplitude increases with the increase of fuel air ratio. Phase trajectory reconstruction is applied to classify the pressure oscillation motion; there are three motions captured in the tests including: “disk”, “ring” and “cluster”. The pressure drops across the dome under strong pressure oscillation are distinctly divergent from the cold flow, and the changes of pressure drops are mainly affected by pressure oscillation amplitude, but is less influenced by pressure oscillation motion nor oscillation frequencies. Based on the mass flow conservation, the reduction of effective flow area of combustor under strong pressure oscillation is demonstrated. Liner wall temperatures are analyzed through Multiple Linear Regression (MLR) method to estimate the reduction of the air mass flow proportion of the liner cooling under strong pressure oscillation. Finally, the air mass flow proportions of each component under strong pressure oscillation are estimated, the results show that the pressure oscillation motion also has influence on air mass flow proportion.     

火星进入段探测器自校准状态估计

由于大气密度、气动参数、突风和沙尘暴等因素的影响,火星探测器在进入段高速飞行的动力学模型中往往带来未知输入,这些未知输入使传统的滤波方法出现较大的偏差。研究采用一种新的自校准扩展Kalman滤波方法,对火星进入段的探测器进行状态估计,可以成功地消除这些未知输入带来的影响。数值仿真结果表明,该方法能有效提高导航精度。     

空间绳系机器人抓捕非合作目标的质量特性参数辨识

针对空间绳系机器人抓捕非合作目标/空间垃圾后需要对其进行回收/拖曳的精确控制问题,提出了一种利用抓捕后保持阶段的振动特性辨识目标参数的方法。首先,根据质量特性参数辨识的需要,推导了系统的动力学模型。不同于以往将本体卫星和被抓捕目标简化为质点的动力学模型,本文针对任意的目标抓捕位置,在考虑重力梯度影响的基础上,利用拉格朗日法获得系统各广义坐标的动力学公式。然后,分析非合作目标和系绳在后抓捕保持阶段的姿态运动。最后,在非合作目标与本体卫星没有任何信息交互的情况下,利用后抓捕阶段目标卫星和系绳特有的振动,并使用具有鲁棒性可遗忘因子的递推最小二乘法,提出了包括转动惯量和质心到任意抓捕点距离在内的质量特性参数辨识算法。     

对空间碎片的相对位姿估计

针对几何、质量特性参数均未知的空间碎片,提出一种基于扩展卡尔曼滤波（EKF）的相对位姿估计算法。该算法以单目相机获得的目标图像特征视线信息作为测量输入,以目标姿态、姿态角速度、惯量比、相对位置、相对速度和特征位置作为滤波状态。对算法进行可观性分析,给出两个可以保证算法可观性的条件。分别针对不同条件进行数值仿真,仿真结果表明新算法能够对几何和质量参数未知的空间碎片进行有效的相对位姿 估计。     

基于STLS的卫星惯量矩阵在轨估计

提出了一种采用结构总体最小二乘（Structured total least squares, STLS）进行卫星惯量矩阵在轨估计的方法,与当前估计方法相比,该方法在考虑敏感器测量噪声时能获得一致估计。首先由动量守恒定律得到估计方程,针对该方程的特点定义了惯量矩阵的STLS估计,并使用结构总体最小范数（Structured total least norm, STLN）算法进行求解。证明了当噪声为高斯分布时该STLS估计为极大似然估计,给出了该STLS估计具有一致性的充分条件,仿真结果验证了文章所提估计方法的有效性。     

非质心特征点相对位置和姿态估计方法研究

卫星编队飞行中,从星星体上偏离质心的任意特征点,其相对位置和相对姿态运动耦合。本文针对任意点的相对状态估计问题,推导了耦合相对轨道动力学方程和无陀螺相对姿态动力学方程,并且基于PSD敏感器对主星上点光源的视线测量值,提出了基于特征点耦合动力学和质心传统动力学的两种相对状态估计策略。针对每种策略分别设计了EKF和UKF两种滤波算法对相对状态进行估计。最后通过数学仿真对算法的有效性进行了验证,并对其计算量进行了分析。结果表明,四种算法均能对特征点的相对状态进行较高精度的估计。