On the detection of anomalous seismo-ionospheric behavior in the presence of space weather stimuli for large earthquakes

Anomalous behavior of ionospheric total electron content (TEC) prior to earthquake has been observed in many studies. Evidence of such seismo-ionospheric coupling effects suggests that it is plausible to rely on TEC signatures for early earthquake warning. However, the detection of pre-earthquake TEC anomalies (PETA) has not been adopted in practice due to two pertinent issues. Firstly, the effects of space weather activity can affect TEC levels and cause anomalous behavior in the TEC. Usually arbitrary thresholds are set for space weather indices to eliminate TEC anomaly due to space weather effects. Secondly, the choice regarding moving time-window length used to characterise background variation of TEC within the statistical envelope approach has an effect on detection of PETA. While the rule-of-thumb in selecting the moving window length is to have a time window capable of capturing background variability and short-term fluctuations, the length of the time window used in the literature varies with little justification. In this study, a critical examination is conducted on the statistical envelope approach and in particular, to eliminate the effect of space weather activity without the use of arbitrary space indices to detect PETA. A two-part PETA identification procedure is proposed, consisting of wavelet analyses isolating non-earthquake TEC contributions, followed by the statistical envelope method using a moving window length standardized based on observed periodicities and statistical implications is suggested. The approach is tested on a database of 30 large earthquakes (M?≥?7.0). The proposed procedure shows that PETA can be detected prior to earthquakes at higher confidence levels without the need to separately check for space weather activity. More importantly, the procedure was able to detect PETA for studies where it was previously reported that PETA could not be detected or detected convincingly.     

An optimal beam alignment method for large-scale distributed space surveillance radar system

Large-scale distributed space surveillance radar is a very important ground-based equipment to maintain a complete catalogue for Low Earth Orbit (LEO) space debris. However, due to the thousands of kilometers distance between each sites of the distributed radar system, how to optimally implement the Transmitting/Receiving (T/R) beams alignment in a great space using the narrow beam, which proposed a special and considerable technical challenge in the space surveillance area. According to the common coordinate transformation model and the radar beam space model, we presented a two dimensional projection algorithm for T/R beam using the direction angles, which could visually describe and assess the beam alignment performance. Subsequently, the optimal mathematical models for the orientation angle of the antenna array, the site location and the T/R beam coverage are constructed, and also the beam alignment parameters are precisely solved. At last, we conducted the optimal beam alignment experiments base on the site parameters of Air Force Space Surveillance System (AFSSS). The simulation results demonstrate the correctness and effectiveness of our novel method, which can significantly stimulate the construction for the LEO space debris surveillance equipment.     

Predicting the vulnerability of spacecraft components: Modelling debris impact effects through vulnerable-zones

The space environment around the Earth is populated by more than 130 million objects of 1 mm in size and larger, and future predictions shows that this amount is destined to increase, even if mitigation measures are implemented at a far better rate than today. These objects can hit and damage a spacecraft or its components. It is thus necessary to assess the risk level for a satellite during its mission lifetime. Few software packages perform this analysis, and most of them employ time-consuming ray-tracing methodology, where particles are randomly sampled from relevant distributions. In addition, they tend not to consider the risk associated with the secondary debris clouds. The paper presents the development of a vulnerability assessment model, which relies on a fully statistical procedure: the debris fluxes are directly used combining them with the concept of vulnerable zone, avoiding the random sampling the debris fluxes. A novel methodology is presented to predict damage on internal components. It models the interaction between the components and the secondary debris cloud through basic geometrical operations, considering mutual shielding and shadowing between internal components. The methodologies are tested against state-of-the-art software for relevant test cases, comparing results on external structures and internal components.     

Survey of orbital dynamics and control of space rendezvous

Rendezvous orbital dynamics and control （RODC） is a key technology for operating space rendezvous and docking missions. This paper surveys the studies on RODC. Firstly, the basic relative dynamics equation set is introduced and its improved versions are evaluated. Secondly, studies on rendezvous trajectory optimization are commented from three aspects： the linear rendez- vous, the nonlinear two-body rendezvous, and the perturbed and constrained rendezvous. Thirdly, studies on relative navigation are briefly reviewed, and then close-range control methods including automated control, manual control, and telecontrol are analyzed. Fourthly, advances in rendezvous trajectory safety and robust analysis are surveyed, and their applications in trajectory optimization are discussed. Finally, conclusions are drawn and prospects of studies on RODC are presented.     

Multi-view space object recognition and pose estimation based on kernel regression

The application of high-performance imaging sensors in space-based space surveillance systems makes it possible to recognize space objects and estimate their poses using vision-based methods. In this paper, we proposed a kernel regression-based method for joint multi-view space object recognition and pose estimation. We built a new simulated satellite image dataset named BUAA-SID 1.5 to test our method using different image representations. We evaluated our method for recognition-only tasks, pose estimation-only tasks, and joint recognition and pose estimation tasks. Experimental results show that our method outperforms the state-of-the-arts in space object recognition, and can recognize space objects and estimate their poses effectively and robustly against noise and lighting conditions.     

一种光学遥感成像系统优化设计新方法研究

针对空间光学高分辨率遥感器,既要实现轻小型化,又要获得高品质遥感图像的要求,文章提出一种空间光学遥感成像系统优化设计新方法;综合考虑成像链路各环节因素,采用全面的指标设计和合理的优化设计流程来改进空间光学遥感成像系统的总体指标和成像品质,并显著降低遥感器的研制难度.通过比较全链路优化设计方法和传统设计方法的仿真结果及其...     

大气对遥感卫星图像品质的影响分析

影响遥感卫星图像品质的因素很多,其中包括成像条件中的大气辐射.文章根据遥感成像理论分析了大气辐射对遥感卫星图像品质的影响,计算了大气背景及大气对图像层次和图像对比度的影响.最后,结合遥感相机的特点,给出了减少大气影响、提高图像品质的建议.     

采用波前编码降低MWIR成像系统的温度敏感度

波前编码成像由于可以大大扩展非相干成像系统的景深而不降低像质,成为近年来的研究热点.文章首先介绍了波前编码原理,然后基于波前编码原理对现有空间中波红外光学系统进行了优化改进,比较了原光学系统和改进系统在不同温度环境下的点扩散函数(PSF)、调制传递函数(MTF),结果表明,新系统在更大的温度范围内具有稳定的成像性能.     

自适应双平面信息无缝传输实现方法研究

航天测控事业的发展对测控网信息传输的要求越来越高。为保证信息的可靠传输,在通信传输上采用了独立双路由的双平面设计。本文在分析传统测控信息传输模型优缺点的基础上,提出了双平面通信方式下信息传输的改进模型,通过信息选用策略,实现了信息的自适应无缝传输,并进行了仿真测试验证。     

空间机器人主从遥操作的自抗扰控制

目前基于模型的控制方法是空间机器人遥操作控制的主流方法,但该方法不可避免地会引入运动的累积误差,甚至造成控制失稳。针对这一问题,基于自抗扰控制方法为空间机器人主从遥操作设计了一类单关节控制器,并采用计算机仿真方法研究了其基本性能,结果表明所设计的自抗扰控制器能够实现稳定的遥操作控制,且具有良好的抗扰性和鲁棒性。特别是由于自抗扰控制方法不依赖于机器人的数学模型,因此十分适合作为现行基于模型控制的有益补充。