Uncertainty-aware Cube algorithm for medium-term collision risk assessment

The number of Earth orbiting objects is constantly growing, and some orbital regions are becoming risky environments for space assets of interest, which are increasingly threatened by accidental collisions with other objects, especially in Low-Earth Orbit (LEO). Collision risk assessment is performed by various methods, both covariance and non-covariance based. The Cube algorithm is a non-covariance-based method used to estimate the collision rates between space objects, whose concept consists in dividing the space in cubes of fixed dimension and, at each time instant, checking if two or more objects share the same cube. Up to now its application has been limited to the long-term scenarios of orbital debris evolutionary models, where considering the uncertainties is not necessary and impractical. Within operative contexts, instead, medium-term collision risk analysis may be an important task, in which the propagation-related uncertainties play a prominent role, but the timescale poses challenges for the application of standard covariance-based conjunction analysis techniques. In this framework, this paper presents an approach for the evaluation of the medium-term collision frequency for objects in LEO, called Uncertainty-aware Cube method. It is a modified version of the Cube, able to take the possible errors in the space objects’ position into account for the detection of the conjunctions. As an object’s orbit is propagated, the along-track position error grows more and more, and each object could potentially be in a different position with respect to the one determined by numerical propagation and, thus, in a different cube. Considering the uncertainties, at each time instant the algorithm associates more than one cube to each object and checks if they share at least one cube. If so, a conjunction is detected and a degree of confidence is evaluated. The performance of the method is assessed in different LEO scenarios and compared to the original Cube method.     

空间目标预警阈值确定分析

针对目前通常采用计算碰撞概率来进行空间目标碰撞预警的方法,为提高其评判标准的精度以达到提高航天器精准预警的目的,分析了目前空间目标碰撞概率阈值确定过程的总体框架.对阈值确定过程中所涉及的误差协方差矩阵确定方法、碰撞概率计算以及碎片通量计算方法进行了研究.以国际空间站（ISS）为例,通过计算其所在空间的碎片通量,分析其轨道受空间环境的影响情况,并与早期结果进行比较,得出其以往的碰撞概率阈值可能被高估的结论.      

基于相控阵雷达波束篱笆的空间碎片数量与分布估计方法

随着载人航天与空间站等航天活动的增多,不能有效防护、也无法定期跟踪和编目的小尺寸(尤其是1～10 cm)碎片的危害越来越受到关注,这些碎片信息的获取依赖于统计采样技术.针对简化的相控阵雷达波束篱笆空间碎片探测模式,提出了一种采用统计技术估计空间碎片总数量以及高度和倾角分布的方法.将碎片穿越波束篱笆的过程用Poisson分布来建模,根据观测时段内穿越波束篱笆目标的平均到达率及测量的轨道高度和倾角数据来估计给定轨道高度范围或倾角范围内碎片的数量,进而得到碎片的总数量以及碎片数量随轨道高度或倾角的分布.在获取雷达散射截面信息时,该方法还可用于估计碎片数量随尺寸的分布.通过仿真实验验证了该方法的有效性.      

Fuzzy multi-criteria decision-making approach to prioritization of space debris for removal

As private companies and government space agencies begin to seriously consider the task of active space debris removal, it is becoming increasingly more important to determine the highest priority objects to deorbit. This work sets forth an approach for prioritization of space debris through the utilization of Multi-Criteria Decision-Making methodologies and fuzzy logic, as well as both quantitative and qualitative criteria. The proposed debris prioritization approach considers various criteria including the orbit, size, mass, pairwise and total collision probabilities, and decay timeframe of each debris object. The means of assigning attributes to each assessment criterion is discussed in detail. To determine the weighting scheme for the criteria, a questionnaire was prepared and shared with experts in the field of space situational awareness. The work examines over two thousand critical debris objects selected from the existing debris catalog with respect to these criteria. The quantified attributes for each debris object are then aggregated through the fuzzy versions of the Analytic Hierarchy Process and the Technique for Order Preference by Similarity to Ideal Solution. The results of the analysis identify high-priority debris objects for removal from Earth-bound orbits.     

Track detection of high-velocity resident space objects in Low Earth Orbit

The world’s economy has become heavily dependent on the services provided by satellites. With the exponential increase in satellite launches, the population of defunct or inactive hardware in space has grown substantially. This is especially true in sensitive orbits such as the Low Earth Orbit (LEO) and Geostationary Earth Orbit (GEO) regimes. These objects, collectively known as orbital debris, can reach speeds of up to 28 000km h^?1 in LEO. At these orbital speeds, even the smallest of objects can pose a considerable threat to operational satellites or astronauts. This makes the monitoring, and detection, of these objects of the utmost importance. This work describes the latest detection strategy used in one of Europe’s largest Space Situational Awareness (SSA) installation; the BIstatic RAdar for LEo Survey (BIRALES) space debris radar. We present a novel bottom-up approach that makes use of single-linkage clustering to identify faint radar streaks in spectrogram data. Tests on synthetic data have shown that the detection strategy presented in this study obtains a higher detection rate when it is compared against existing methods. Unlike other approaches, this detection strategy, using the Multi-beam streak detection strategy (MSDS) algorithm, was still able to recall 90% of the track information at an Signal-to-Noise Ratio (SNR) of 2dB.     

Imaging systems using modulation and coded aperture masks

The advent of improved γ-ray telescopes which incorporate high angular resolution imaging properties and adequate sensitivity will advance this branch of astronomy from the discovery phase to the exploratory phase. As in other fields, such as radio and X-ray astronomy, which have recently undergone this change, it will prove a fascinating era. The recent development of position sensitive γ-ray detection planes operated in conjunction with a suitable coded aperture mask have made γ-ray telescopes feasible which are capable of generating γ-ray images of the sky with a precision of 1 arc minute over the photon energy range 0.1 to 10 MeV. With a sensitivity of at least 1–10 milliCrab and scintillation standard spectral resolution not only can a large number of discrete γ-ray objects be identified and studied in detail but nuclear γ-ray line images of extended objects such as the Galactic Plane, Cloud Complexes, and supernovae remnants may be generated by this class of astronomical instrument.     

地气光辐射对空间目标成像特性影响分析

为分析地气光辐射对空间目标成像特性的影响,以地球同步轨道(GEO)卫星搭载的可见光成像器为探测平台,利用卫星工具包(STK)设计高椭圆轨道(HEO)及近地轨道(LEO)目标运动场景,根据空间目标、地球、太阳、探测平台之间的位置关系,采用微元法建立空间目标与地气光背景等效星等模型,推导出空间目标信噪比(SNR)计算公式。分析了距离、角度参数变化对不同轨道空间目标、地气光背景等效星等及空间目标信噪比的影响。仿真结果表明:当探测平台距离空间目标较远时,地气光背景等效星等低于空间目标等效星等,地气光辐射比空间目标信号强。当地气光辐射进入和离开空间目标探测视场时,空间目标信噪比最大,该时间段是进行空间目标探测的最佳“观测窗口”。仿真得出的空间目标信噪比值为空间目标探测识别提供了理论计算依据。      

试验设备检漏技术

以中国3200m^3大型空间环境模拟器为基础论述了环模试验设备的检漏技术，目的是为大型试验设备的检漏提供一些有益的思路和方法。文章重点分析了氦质谱检漏仪法，并从理论和实践的基础上对其最小可检灵敏度进行了分析。最后文章对环模试验设备的总体检漏方案进行了论述。     

Analysis of the orbit lifetime of CubeSats in low Earth orbits including periodic variation in drag due to attitude motion

It is estimated that more than 22,300 human-made objects are in orbit around the Earth, with a total mass above 8,400,000 kg. Around 89% of these objects are non-operational and without control, which makes them to be considered orbital debris. These numbers consider only objects with dimensions larger than 10 cm. Besides those numbers, there are also about 2000 operational satellites in orbit nowadays. The space debris represents a hazard to operational satellites and to the space operations. A major concern is that this number is growing, due to new launches and particles generated by collisions. Another important point is that the development of CubeSats has increased exponentially in the last years, increasing the number of objects in space, mainly in the Low Earth Orbits (LEO). Due to the short operational time, CubeSats boost the debris population. One of the requirements for space debris mitigation in LEO is the limitation of the orbital lifetime of the satellites, which needs to be lower than 25 years. However, there are space debris with longer estimated decay time. In LEÓs, the influence of the atmospheric drag is the main orbital perturbation, and is used in maneuvers to increment the losses in the satellite orbital energy, to locate satellites in constellations and to accelerate the decay.The goal of the present research is to study the influence of aerodynamic rotational maneuver in the CubeSat?s orbital lifetime. The rotational axis is orthogonal to the orbital plane of the CubeSat, which generates variations in the ballistic coefficient along the trajectory. The maneuver is proposed to accelerate the decay and to mitigate orbital debris generated by non-operational CubeSats. The panel method is selected to determine the drag coefficient as a function of the flow incident angle and the spinning rate. The pressure distribution is integrated from the satellite faces at hypersonic rarefied flow to calculate the drag coefficient. The mathematical model considers the gravitational potential of the Earth and the deceleration due to drag. To analyze the effects of the rotation during the decay, multiple trajectories were propagated, comparing the results obtained assuming a constant drag coefficient with trajectories where the drag coefficient changes periodically. The initial perigees selected were lower than 400 km of altitude with eccentricities ranging from 0.00 to 0.02. Six values for the angular velocity were applied in the maneuver. The technique of rotating the spacecraft is an interesting solution to increase the orbit decay of a CubeSat without implementing additional de-orbit devices. Significant changes in the decay time are presented due to the increase of the mean drag coefficient calculated by the panel method, when the maneuver is applied, reducing the orbital lifetime, however the results are independent of the angular velocity of the satellite.     

基于ViBE与面向对象分类的视频卫星运动车辆检测

为了提高视频卫星对运动车辆的检测质量，在经典视觉背景提取器(ViBE)算法的基础上，结合遥感的面向对象分类技术，从提升正确检测运动目标数量和抑制虚假运动目标检测数量两个方面着手，提出了一种新的运动车辆检测方法（VOMVD）。首先通过优化ViBE模型参数，尽可能多地获取真实运动目标，但这在一定程度引入了许多的虚假目标。研究继而依据影像上地面小尺度运动目标和道路的依存关系，采用面向对象的分类方法，基于光谱、纹理、空间属性，构建了均值、标准差、卷积核内平均灰度值、卷积核内平均信息熵、面积、长度、紧密度、延伸度等8个特征，用于提取道路信息，以此掩膜ViBE提取的虚假运动目标和伪运动目标。结果表明，基于本研究提出的视频卫星运动目标检测方法较之三帧差分法、ViBE检测方法等，其精度有明显提升。在本研究中，三帧差分法、ViBE和VOMVD对运动目标的检测精度P分别为70.91%，61.49%和85.71%，召回率R分别为84.78%，98.91%和97.83%，F值分别为77.23%，75.83%和91.37%，有效提升了方法对运动目标的检测效果。     

Photon counting detector for space debris laser tracking and lunar laser ranging

We are reporting on a design, construction and performance of solid state photon counting detector package which has been designed for laser tracking of space debris. The detector has been optimized for top photon detection efficiency and detection delay stability. The active area of the commercially available avalanche photodiode manufactured on Si (SAP500 supplied by Laser Components, Inc.) is circular with a diameter of 500 μm. The newly designed control circuit enables to operate the detection sensor at a broad range of biases 5–50 V above its breakdown voltage of 125 V. This permits to select a right trade-off between photon detection efficiency, timing resolution and dark count rate. The photon detection efficiency exceeds 70% at the wavelength of 532 nm. This is the highest photon detection efficiency ever reported for such a device. The timing properties of the detector have been investigated in detail. The timing resolution is better than 80 ps r.m.s, the detection delay is stable within units of picoseconds over several hours of operation. The detection delay stability in a sense of time deviation of 800 fs has been achieved. The temperature change of the detection delay is 0.5 ps/K. The detector has been tested as an echo signal detector in laser tracking of space debris at the satellite laser station in Graz, Austria. Its application in lunar laser ranging is under consideration by several laser stations.     

Properties of the high area-to-mass ratio space debris population at high altitudes

In the framework of its space debris research activities ESA established an optical survey program to study the space debris environment at high altitudes, in particular in the geostationary ring and in the geostationary transfer orbit region. The Astronomical Institute of the University of Bern (AIUB) performs these surveys on behalf of ESA using ESA’s 1-m telescope in Tenerife. Regular observations were started in 1999 and are continued during about 120–140 nights per year. Results from these surveys revealed a substantial amount of space debris at high altitudes in the size range from 0.1 to 1 m. Several space debris populations with different dynamical properties were identified in the geostationary ring. During the searches for debris in the geostationary transfer orbit region a new population of objects in unexpected orbits, where no potential progenitors exist, was found. The orbital periods of these objects are clustered around one revolution per day; the eccentricities, however, are scattered between 0 and 0.6. By following-up some of these objects using the ESA telescope and AIUB’s 1-m telescope in Zimmerwald, Switzerland, it was possible to study the properties of this new population. One spectacular finding from monitoring the orbits over time spans of days to months is the fact that these objects must have extreme area-to-mass ratios, which are by several orders of magnitudes higher than for ‘normal-type’ debris. This in turn supports the hypothesis that the new population actually is debris generated in or near the geostationary ring and which is in orbits with periodically varying eccentricity and inclination due to perturbations by solar radiation pressure. In order to further study the nature of these debris, multi-color and temporal photometry (light curves) were acquired with the Zimmerwald telescope. The light curves show strong variations over short time intervals, including signals typical for specular reflections. Some objects exhibit distinct periodic variations with periods ranging from 10 to several 100 s. All this is indicative for objects with complicated shapes and some highly reflective surfaces.     

Small satellite characterization technologies applied to orbital debris

There are challenges associated with optical observations of Earth-orbiting objects that are at, or near, the limit of detection using terrestrial space surveillance sensors. These challenges include observing small objects not just for statistical purposes, but also with enough frequency and accuracy to move them into satellite catalogs, to provide the capability to routinely observe and characterize smaller objects, and to develop the capability to observe the satellite positions with increased accuracy. Until recently, ground-based observers could easily have mistaken such small objects as debris. Given the current pace of small satellite development, it may not be much longer before operational spacecraft of even smaller size are launched. AMOS is currently developing techniques to observe and characterize these small spacecraft, and applying those techniques to orbital debris.     

Orbital debris environment resulting from future activities in space

A long-term evolution of space debris environment has been simulated by a numerical model. Based on previously published results in many 50-year runs of the “dynamic model”, an “average model” is derived to reduce the computation time in order to effectively simulate a very-long-term evolution of space debris environment. The evolution of space debris environment is examined with two different future space activities in LEO: (1) Increase the yearly traffic input of new satellites by 2%, 5%, 10%, 20%, and 50%; and (2) place ten large space structures of 100 meters in diameter in the year 1995 at either 500 km or 1000 km altitude. The results indicate that in a 170-year span from 1983, every space activity listed above results in a rapid runaway of debris fluxes from objects of 4 mm or larger.     

家庭安全监控的实时异常检测与分类算法

同时具有好的实时性和稳健性是基于视频的安全监控系统异常检测算法的难点问题.在家庭安全监控系统中同时利用像素的亮度分量和色度分量检测变化像素,解决摄像镜头由于大尺寸对象闯入引起的图像背景变化造成运动对象检测失败的问题;提出一种实时运动对象分类算法,综合利用开关灯检测、运动距离分析和皮肤探测多种方法,区分是否出现影响家庭安全的事件;提出3关键值背景维护算法,用于消除背景振动像素,减少虚假报警.实验表明,本文异常探测算法对视频监控系统异常探测和消除虚假异常报警具有较好的实时性和稳健性.      

太阳质子事件中短期预报模型研究

太阳质子事件通量的预测对航天器抗辐射加固设计和航天员出舱活动具有非常重要的意义.针对一年以下的航天任务,利用经验统计方法,确认太阳活跃年和太阳平静年期间,1——365天不同时间段内 > 10MeV,> 30MeV和 > 60MeV的太阳质子事件积分通量符合对数正态分布,且通量对数的标准偏差σ和期望值μ随任务期时间的变化满足对数函数形式.以此为基础,构建太阳质子通量的中短期预报模型.该模型能够针对太阳活跃年和太阳平静年,给出一定置信度下1——365天不同时间内 > 10MeV,> 30MeV和 > 60MeV的质子事件通量分布,从而为执行中短期航天任务提供太阳质子事件通量的预测,以规避不必要的风险.      

Design and fabrication of robotic gripper for grasping in minimizing contact force

This paper presents a new method to improve the kinematics of robot gripper for grasping in unstructured environments, such as space operations. The robot gripper is inspired from the human hand and kept the hand design close to the structure of human fingers to provide successful grasping capabilities. The main goal is to improve kinematic structure of gripper to increase the grasping capability of large objects, decrease the contact forces and makes a successful grasp of various objects in unstructured environments. This research will describe the development of a self-adaptive and reconfigurable robotic hand for space operations through mechanical compliance which is versatile, robust and easy to control. Our model contains two fingers, two-link and three-link, with combining a kinematic model of thumb index. Moreover, some experimental tests are performed to examine the effectiveness of the hand-made in real, unstructured tasks. The results represent that the successful grasp range is improved about 30% and the contact forces is reduced approximately 10% for a wide range of target object size. According to the obtained results, the proposed approach provides an accommodative kinematic model which makes the better grasping capability by fingers geometries for a robot gripper.     

Autonomous space target tracking through state estimation techniques via ground-based passive optical telescope

The presence of operational satellites or small-body space debris is a challenge for autonomous ground-based space object observation. Although most space objects exceeding 10?cm in diameter have been cataloged, the position of each space object (based on six orbital parameters) remains important and should be updated periodically, as the Earth’s orbital perturbations cause disturbances. Modern ground-based passive optical telescopes equipped with complementary metal-oxide semiconductors have become widely used in astrometry engineering, being combined with image processing techniques for target signal enhancement. However, the detection and tracking performance of this equipment when employed with image processing techniques primarily depends on the size and brightness of the space target, which appears on the monitor screen under variable background interference conditions. A small and dim target has a highly sensitive tracking error compared to a bright target. Moreover, most image processing techniques for target signal enhancement require large computational power and memory; therefore, automatic tracking of a space target is difficult. The present work investigates autonomous space target detection and tracking to achieve high-sensitivity detection and improved tracking ability for non-Gaussian and dynamic backgrounds with a simple system mechanism and computational efficiency. We develop an improved particle filter (PF) using the ensemble Kalman filter (KF) for track-before-detect (TBD) frameworks, by modifying and optimizing the computational formula for our non-linear measurement function. We call this extended version the “ensemble Kalman PF-TBD (EnKPF-TBD).” Three sequential astronomical image datasets taken by the Asia-Pacific Ground-Based Optical Space Objects Observation System (APOSOS) telescope under different conditions are used to evaluate three proposed TBD baseline frameworks. Given an optimal random sample size, the EnKPF-TBD exhibits superior performance to PF-TBD and threshold-based unscented KF with two-dimensional peak search (2dPS). The EnKPF-TBD scheme achieves satisfactory performance for all variable background interference conditions, especially for a small and dim space target, in terms of tracking accuracy and computational efficiency.     

A Partially Orthogonal EnKF approach to atmospheric density estimation using orbital debris

A key requirement for accurate trajectory prediction and space situational awareness is knowledge of how non-conservative forces affect space object motion. These forces vary temporally and spatially, and are driven by the underlying behavior of space weather particularly in Low Earth Orbit (LEO). Existing trajectory prediction algorithms adjust space weather models based on calibration satellite observations. However, lack of sufficient data and mismodeling of non-conservative forces cause inaccuracies in space object motion prediction, especially for uncontrolled debris objects. The uncontrolled nature of debris objects makes them particularly sensitive to the variations in space weather. Our research takes advantage of this behavior by utilizing observations of debris objects to infer the space environment parameters influencing their motion.The hypothesis of this research is that it is possible to utilize debris objects as passive, indirect sensors of the space environment. We focus on estimating atmospheric density and its spatial variability to allow for more precise prediction of LEO object motion. The estimated density is parameterized as a grid of values, distributed by latitude and local sidereal time over a spherical shell encompassing Earth at a fixed altitude of 400 km. The position and velocity of each debris object are also estimated. A Partially Orthogonal Ensemble Kalman Filter (POEnKF) is used for assimilation of space object measurements to estimate density.For performance comparison, the scenario characteristics (number of objects, measurement cadence, etc.) are based on a sensor tasking campaign executed for the High Accuracy Satellite Drag Model project. The POEnKF analysis details spatial comparisons between the true and estimated density fields, and quantifies the improved accuracy in debris object motion predictions due to more accurate drag force models from density estimates. It is shown that there is an advantage to utilizing multiple debris objects instead of just one object. Although the work presented here explores the POEnKF performance when using information from only 16 debris objects, the research vision is to utilize information from all routinely observed debris objects. Overall, the filter demonstrates the ability to estimate density to within a threshold of accuracy dependent on measurement/sensor error. In the case of a geomagnetic storm, the filter is able to track the storm and provide more accurate density estimates than would be achieved using a simple exponential atmospheric density model or MSIS Atmospheric Model (when calm conditions are assumed).     

星用SRAM型FPGA的故障模式分析和容错方法研究

静态存储器（SRAM,static random access memory）型现场可编程门阵列（FPGA,field programmable gate array）是一种对空间辐射效应较为敏感的航天器电子元器件。由于其特有的构造和工作方式,单粒子辐射效应对SRAM型FPGA造成的影响及其引起的故障模式有着区别于一般电子元器件的特征。为了提高SRAM型FPGA在空间应用中的可靠性,以该类型FPGA的主流器件作为研究对象,深入分析了FPGA在空间应用中的各种故障模式,研究了相应的各种容错方法。研究表明,通过采取适当的FPGA容错方法,能够有效降低SRAM型FPGA因空间辐射而发生故障的可能性。