拦截高速目标的比例与反比例导引捕获区分析

针对拦截高速目标的作战特点，分析了比例导引(PN)与反比例导引(RPN)的捕获区。首先，通过分析拦截弹与目标的相对运动关系，推导得到了顺轨和逆轨的零控拦截条件，此条件由目标和拦截弹的速度前置角以及二者速度比确定；其次，以拦截弹和目标速度前置角为坐标系，推导得到了PN以及RPN捕获区以及各自导航比设置范围。PN的捕获区由逆轨零控拦截条件以及与其相切且斜率为1/(N-1)的两条直线构成，RPN的捕获区由顺轨零控拦截条件以及与其相切且斜率为1/(-N-1)的两条直线构成；然后，利用函数对称性将PN与RPN捕获区转换到同一坐标区间，得到了相同条件下RPN捕获区要大于PN捕获区的结论；最后，开展了四种情形下的仿真，验证了本文捕获区分析的合理性及有效性。     

不同密度弹丸对水冰的超高速撞击成坑实验

为了研究冰冻天体表面撞击坑的形成与演化，开展了水冰的超高速撞击成坑实验。使用二级轻气炮发射1.0 mm直径的球形弹丸，以3 km/s、5 km/s和7 km/s速度对圆柱状冰块进行撞击。弹丸材料包括聚碳酸酯和不锈钢两种，冰块温度为253 K。实验观察到了不同弹丸和不同速度条件下，冰块中撞击坑的形貌特征。对撞击坑直径、深度和剖面形状进行了测量，并与文献中铝弹丸对水冰的撞击坑进行了比较分析。获得了水冰撞击坑特征随撞击参数的变化规律，结果表明：撞击坑直径和深度的主导机制不同，坑深主要由弹丸侵彻作用形成，而坑径主要由冰块的剥落所致；坑深比坑径具有更强的对于弹丸密度的依赖性，高密度弹丸撞击坑直径具有比低密度弹丸更强的对于撞击速度的依赖性；撞击坑体积与撞击能量成正比，高密度弹丸形成的撞击坑直径表现出“能量缩比”行为，而低密度弹丸形成的撞击坑直径表现出“动量缩比”行为。     

Predictive fault-tolerant control of an all-thruster satellite in 6-DOF motion via neural network model updating

The problem of controlling an all-thruster spacecraft in the coupled translational-rotational motion in presence of actuators fault and/or failure is investigated in this paper. The nonlinear model predictive control approach is used because of its ability to predict the future behavior of the system. The fault/failure of the thrusters changes the mapping between the commanded forces to the thrusters and actual force/torque generated by the thruster system. Thus, the basic six degree-of-freedom kinetic equations are separated from this mapping and a set of neural networks are trained off-line to learn the kinetic equations. Then, two neural networks are attached to these trained networks in order to learn the thruster commands to force/torque mappings on-line. Different off-nominal conditions are modeled so that neural networks can detect any failure and fault, including scale factor and misalignment of thrusters. A simple model of the spacecraft relative motion is used in MPC to decrease the computational burden. However, a precise model by the means of orbit propagation including different types of perturbation is utilized to evaluate the usefulness of the proposed approach in actual conditions. The numerical simulation shows that this method can successfully control the all-thruster spacecraft with ON-OFF thrusters in different combinations of thruster fault and/or failure.     

热防护系统损伤容限分析

建立了含初始矩形损伤的热防护系统(Thermal protection system,TPS)气动热分析的CFD数值模型,分析结果表明损伤区域侧壁出现了很高的热流密度峰值,并且迎风面侧壁峰值高于背风面,而损伤区域底部热流密度却很低。利用分析获得的热流密度建立了含损伤和无损伤TPS的有限元传热分析模型。分析结果表明:损伤的存在导致防热瓦最高温度急剧上升,超过其材料能承受的极限温度(1 500℃),防热瓦首先失效,而损伤对机体最高温度影响较小。最后进行了TPS损伤容限分析,在防热瓦极限温度约束下,外部热流密度最大值从100kW/m2增加到140kW/m2,矩形损伤宽度最大容许值从22.7mm减小到12.6mm,而弧形损伤宽度最大容许值从34.6mm减小到25.1mm,即随着外部热流密度最大值增加,损伤宽度的最大容许值降低,并且相同外部热流密度水平下弧形损伤宽度的最大容许值大于矩形损伤。     

基于深度学习的空间站舱内服务机器人视觉跟踪

为提升舱内跟随服务机器人的任务辅助能力,解决机器人对航天员的视觉跟踪问题,提出了一种基于深度学习和概率模型的人体视觉跟踪算法。利用深度卷积神经网络实现了对穿着多样、姿态任意人体的稳定检测。结合人体检测结果,设计了运动预测概率模型,实现了对指定人员准确、连续的跟踪。算法对包含大多数航天员活动的多个数据集进行了验证。实验结果表明:提出的跟踪算法实现了对穿着多样、姿态任意人体的稳定跟踪,并有效避免了由于穿着相似、遮挡可能造成的误跟踪问题。该算法为空间站舱内跟随服务机器人对航天员的视觉跟踪提供了有效的解决方法。算法基于融合的RGB-D图像,工程上易于构建和实现,也可拓展到其他跟随服务机器人视觉跟踪任务中。     

空间太阳能电站统一调度设计及电能管理分析

针对多旋转关节空间太阳能电站(Space Solar Power Station, SSPS)，提出一种环形拓扑的电力系统架构。基于功率分层准则对SSPS电力拓扑架构进行设计，提出U1~U7共7个层级、母线电压5000V、功率等级为MW的太阳能电站电力系统。针对分层架构中多太阳电池阵子阵并联(U6层)，提出分层功率平衡统一控制策略，对MPPT控制、MPPT控制+稳定直流母线电压混合控制、MPPT算法+下垂稳定直流母线电压混合控制三种控制方法开展仿真分析。结果表明，提出的基于虚拟阻抗的下垂控制策略可以有效调节、分配功率，解决了空间发电站母线电压无法稳定的问题。     

A boundary vector cell model of place field repetition

Hippocampal place cells are thought to form the neural substrate of a global cognitive map. However, in multicompartment mazes, these cells exhibit locally repeating representations, undermining the global cognitive map view of place cells. This phenomenon appears to be related to the repetitive layout of these mazes, but still no hypothesis adequately explains it. Here, we use a boundary vector cell (BVC) model of place cell firing to model the activity of place cells in numerous multicompartment environments. The activity of modeled place cells bears a striking resemblance to experimental data, replicating virtually every major experimental result. Our results support the BVC model and indicate that locally repeating place cell firing could result purely from local geometry.     

直升机惯性传感器结构的模态优化

提出了一种基于迭代抽样和径向基插值的自适应代理模型方法。这种自适应方法以减少仿真计算数量和提高代理模型自适应能力为目的,使用多岛遗传算法选择新增样本点并使新增样本点位于设计空间的稀疏区域,使得所有的样本点均匀分布于设计空间。标准误差用来判断代理模型的精度大小以决定是否对代理模型进行更新。这种自适应代理模型结合多岛遗传算法对直升机的惯性传感器结构模态进行优化。用拉丁超立方抽样方法选择10个样本点构建初始的代理模型,自适应代理模型的计算结果表明2%的误差条件下需要额外增加7个样本点。优化结果表明不同的权重系数对最优模态特性的影响很大,惯性传感器结构的一至六阶模态值更加远离直升机的激励频率。     

Development and performance evaluation of tropospheric scintillation model on Ku-band satellite link over Akure,Nigeria

Existing amplitude scintillation prediction models often perform less satisfactorily when deployed outside the regions where they were formulated. This necessitates the need to evaluate the performance of scintillation models developed in one region using data data from other regions while documenting their relative errors. Due to its variation with elevation angle, frequency, other link parameters and meteorological factors, we employed three years (January 2016 to December 2018) of concurrently measured satellite radio beacons and tropospheric weather parameters to develop a location-based amplitude scintillation prediction model over the Earth-space path of Akure (7.17^oN, 5.18^oE), South-western Nigeria. The satellite beacon measurement used Tektronix Y400 NetTek Analyzer at 1 s integration time while meteorological parameters, namely; temperature, pressure and relative humidity were measured using Davis Vantage Vue weather station at 1 min integration time. Comparative study of the model’s performance with nine (9) existing scintillation prediction models indicates that the best and worst performing models, in terms of root mean square error (RMSE), are the Statistical Temperature and Refractivity (STN) and direct physical and statistical prediction (DPSP) models with values 11.48 and 51.03 respectively. Also, worst month analysis indicates that April, with respective enhancement and fade values of 0.88 and 0.90 dB for 0.01% exceedance, is the overall worst calendar month for amplitude scintillation.     

蜂窝状薄壁管拉伸时的内陷分析

蜂窝材料因具备广阔的结构设计空间,已广泛应用于航空航天等工业领域。探索蜂窝元胞的组织结构、组分性质与材料整体性能之间的关系有助于新型功能性材料的设计开发。本文从非平面Vertex模型的势能形式出发,结合蜂窝薄壁圆管拉伸时的轴对称特征,通过变分法得到了圆管拉伸时母线满足的控制方程,揭示了边界效应是蜂窝状薄壁圆管受拉时产生内陷的原因,并结合母线控制方程的若干特解,考察了非平面Vertex模型势能形式中包含的材料性质参数与圆管拉伸后内陷程度及范围的关系。研究还指出,蜂窝材料的材料性质包含在非平面Vertex模型的势能形式中,为蜂窝状材料整体性能的研究提供了一种新的思路。