2016HO3探测任务星载光学观测量建模及定轨

以中国首次小行星探测任务为背景,根据星载相机获取的光学影像构造三种观测量,分别为小行星相对于航天器的高度角和方位角、赤经赤纬以及探测器与行星/小行星之间的夹角,分析了其在探测器定轨中的作用。仿真定轨结果表明,观测时长为100 h,探测器三轴位置误差小于50 km,满足工程上对巡航段的轨道精度要求,但x和y方向的位置和速度分量具有较强自相关性。此外还发现,使用单一观测数据类型比联合观测量的定轨精度低3~4个量级,第三类观测量相对于其他两类观测量在定轨精度方面具有显著作用,这表明在2016HO3探测中,利用太阳系大天体的位置信息有助于约束探测器轨道,提高探测器的定轨精度。     

对流层雷暴源所产生的柱形重力波

已有充分的证据表明, 大气对流层的雷暴迹象是大气中间层重力波活动的显著代表源.在雷暴迹象的上方, 通过火箭已观测到大气中间层出现的热效应, 也已通过雷 达探测到大气平流层出现的上行重力波, 从地面和卫星平台上观察到夜间气辉有序而 成环状的重力波波形. 所有这些实验结果都与位于观测点下方的雷暴活动有紧密联系. 此类雷暴通常主要集中在中国东部沿海以及地球其他沿海海湾地域. 关于此类雷暴对大 气中间层的影响尚未被充分研究和了解. 为能有效地探究其成因, 利用所开发的一个二维计算机数值模型模拟和研究大气对流层的雷暴源所引发的上行重力波, 进而揭示 此类重力波产生的基本物理机理, 及其在大气中间层的能量耗散. 通过模拟研究发现, 雷暴源可以大面积高强度地聚集和释放积雨云的能量, 当这种周期性的对流变化引发大气对流层的不稳定性后, 就会有圆柱体重力波的产生和传播.     

利用神经元拓展正则极端学习机预测时间序列

为实现对于时间序列预测数据的准确预测,提出一种神经元拓展正则极端学习机(NERELM,Neuron-Expanding Regularized Extreme Learning Machine),并研究了其在时间序列预测中的应用.NERELM根据结构风险最小化原理权衡经验风险与结构风险,以逐次拓展隐层神经元的方式自动确定最佳的网络结构,以避免传统神经网络训练过程中需人为确定网络结构的弊端.应用于时间序列的仿真结果表明:NERELM可有效实现对于RELM最佳网络结构的自动确定,具有预测精度高与计算速度快的优点.      

脉冲星候选样本分类方法综述

脉冲星搜索是射电天文学中的重要前沿领域。随着现代搜索设备性能的不断提升,可以接收到更弱的信号,如何从海量信号中准确地识别出脉冲星疑似信号成为一个挑战。介绍了国内外关于脉冲星候选样本分类方法的发展历史和发展状态,归纳总结了发展过程中各个阶段的处理方法:人工识别方法和机器学习方法;最后对未来的发展趋势进行了分析。     

Hopper concepts for small body landers

The investigation of small bodies, comets and asteroids, can contribute substantially to our understanding of the formation and history of the Solar System. In situ observations by landers play an important role in this field.     

小天体的多种尺寸颗粒样品收集容器流域的数值模拟

采集小天体表面的样品并返回是当前小天体探测的核心目标之一,样品容器流域设计是氮气激励采样技术的关键.为了保证样品容器具备高效的收集性能,要求样品容器的流域设计能够对样品颗粒形成陷阱效应,并对样品颗粒进行有效的分级.旋风式样品收集容器方案利用旋风离心力和引导叶片的共同作用对样品颗粒进行收集和分级.为了验证这种方案在微重力环境下的性能和可行性,本文利用Fluent软件进行了流域的数值模拟.模拟结果表明：在确定容器的结构下,样品容器的最优氮气入口速度为0.6 m·s^-1,容器在该速度下的样品收集效率达到99.7%.样品容器的流域具备很好的颗粒分级功能,对小于2mm的样品颗粒的捕获率超过了90%,其压力损失也在合理的范围之内.本文研究结果可为小天体采样任务提供借鉴.     

Effects of restitution,friction, and attitude on 2D low-velocity rigid-body impacts

The impact of nonspherical bodies is complex, even at low velocities where contacting bodies are assumed to be rigid. Models of varying complexity (e.g. finite element methods) can be used to evaluate such impacts, but it is advantageous to use impulsive models such as that by Stronge, which are computationally inexpensive and governed by (fixed) material interaction coefficients. Stronge’s model parameterizes nonspherical rigid-body impacts with energetic restitution and Coulomb friction coefficients. This model was successfully used in large-scale simulations of ballistic lander deployment to asteroids and comets, whose trajectories involve dozens of chaotic bounces. To better understand the complex dynamics of these bouncing trajectories, this paper performs a dedicated study of idealized bouncing in two dimensions and on a flat plane, in order to limit the involved degrees of freedom. Using a numerical implementation of Stronge’s model, the motion of a bouncing square is simulated with different impact conditions: the square’s impact attitude, velocity, and mass distribution as well as the surface restitution and friction coefficients. The simulation results are used to investigate how these conditions affect the bouncing motion of the square, with a distinction between first impacts with zero angular velocity and successive impacts in which the square is spinning. This reveals how a single “macroscopic” bounce that separates two ballistic arcs may often consist of multiple micro-impacts that occur in quick succession. For the different impact conditions, we show how the number of micro-impacts per macro-bounce varies, as well as the normal, tangential, and total kinematic restitution coefficients. These are different from the energetic material restitution coefficient that parameterizes the impact. Finally, we examine how the settling time and distance of the bouncing trajectories change. These trends provide insight into the bouncing motion of ballistic lander spacecraft in small-body microgravity.     

Intracellular molecular distributions in spacecraft experiments in orbit around Earth

It is possible that the nucleolous inside the cell plays the role of a “gravity receptor”. Furthermore, cells up to 10 μm in diameter can demonstrate some effect due to the redistribution of mitochondria or nucleolous. Effects of gravity should be present in various cell systems where larger objects such as the ribosomes move from cell to cell. In this paper we study the effects of gravity on cells. In particular, we examine the resulting intracellular molecular distribution due to Brownian motion and the ordered distribution of molecules under the action of gravity, where n₀ is the number per unit volume at certain level, and n is the number per unit volume above that level. This is an experiment that takes place at a certain orbital altitude in a spacecraft in orbit around Earth, where the acceleration due to the central field is corrected for the oblateness and also the rotation of the Earth. We found that equatorial circular and elliptical orbits have the highest n/n₀ ratios. This experiment takes place in circular and elliptical orbits, with eccentricities e = 0, 0.1 and involves a bacterial cell at an orbital altitude of 300 km. We found that n/n₀ = 1.00299 and 1.0037 respectively, which is still a 0.6–0.7 % higher than n/n₀ = 0.0996685 calculated on the surface of the Earth. Examining mitochondria in similar orbital experiments we found that equatorial orbits result to higher n/n₀ ratios. In particular, we found that n/n₀ = 8.38119, where an elliptical orbit of eccentricity e = 0.1 results to n/n₀ = 13.8525. Both are high above 100%, signifying the importance of Brownian motion over gravity. Our results are of interest to biomedical applications. Molecular concentrations are important for various processes such as the embryogenesis, positional homeostasis and its relation to cell energy expenditure, cell torque, cell deformation, and more. These results indicate that statistical molecular distributions play an important role for the recognition of a particular environment by the cell, in biological space experiment to come.     

Adaptive double-saturated control for hovering over an asteroid

Hovering over an irregular-shaped asteroid is particularly challenging due to the large gravitational uncertainties and various external disturbances. An adaptive control scheme considering commanded acceleration and its change-rate saturation for hovering is developed in this paper. Taking full advantage of terminal sliding-mode control theory, first, we convert the double-saturated control problem to a new equivalent system by introducing a special bounded function, in which just control input saturation needs to be considered. Then, a continuous finite-time saturated controller is designed for the new system with the assistance of an constructed auxiliary subsystem. Additionally, an adaptive law is devised for the controller to avoid the requirement of the unknown upper bounds of the disturbances, rendering the control scheme especially suitable to asteroid hovering missions. The finite-time stability of the whole closed-loop system is proved via Lyapunov analysis. Numerical simulation studies are carried out, and the results demonstrate the design features and the desired performance.     

小行星表面有机物的红外光谱探测方法

小行星的有机物记录了太阳系早期有机物的形成发展历史,为地球早期生命前体出现的研究提供了重要依据,对于研究生命起源和演化具有重要意义。本文综合分析了小行星表面可能存在的有机物成分、种类及其赋存状态,利用红外光谱开展地面模拟实验,探讨有机物的红外光谱特征及其影响因素。结果表明,不同类型有机物的红外光谱特征与其类型、结构、温度和压力等有关。研究确定了小行星表面主要有机物的红外光谱识别标志,初步提出了小行星有机物红外光谱探测仪器的基本指标参数。

     

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.     

一种基于支持向量回归的混合建模方法

近年来,随着计算能力的不断提高,数据驱动的建模方法受到了广泛的关注,对单模式系统进行定量分析的建模方法获得了诸多研究。然而,实际应用中大多数系统为多模式系统,不但各个模式有着不同的连续行为,连续状态还会在模式之间进行切换。针对这一情形,本文提出了经验概率混合自动机模型,并提出了针对该模型的基于支持向量回归(SVR)的多模式定性定量混合建模方法。该方法使用小波技术识别模式切换点,并在各个模式下单独建立支持向量模型,最后使用D-Markov机整合模型。经实例验证,该方法与传统支持向量回归模型的稳定性接近,但精确程度显著提高。