Load balancing strategy and its lookup-table enhancement in deterministic space delay/disruption tolerant networks

Space networks, in which connectivity is deterministic and intermittent, can be modeled by delay/disruption tolerant networks. In space delay/disruption tolerant networks, a packet is usually transmitted from the source node to the destination node indirectly via a series of relay nodes. If anyone of the nodes in the path becomes congested, the packet will be dropped due to buffer overflow. One of the main reasons behind congestion is the unbalanced network traffic distribution. We propose a load balancing strategy which takes the congestion status of both the local node and relay nodes into account. The congestion status, together with the end-to-end delay, is used in the routing selection. A lookup-table enhancement is also proposed. The off-line computation and the on-line adjustment are combined together to make a more precise estimate of the end-to-end delay while at the same time reducing the onboard computation. Simulation results show that the proposed strategy helps to distribute network traffic more evenly and therefore reduces the packet drop ratio. In addition, the average delay is also decreased in most cases. The lookup-table enhancement provides a compromise between the need for better communication performance and the desire for less onboard computation.     

Ionospheric parameters in the European sector during the magnetic storm of August 25–26, 2018

Variations of ionospheric parameters Total Electron Content (TEC) by GNSS, critical frequency (foF2) by vertical sounding and electron density (Ne) by low-altitude satellite were studied at high, mid and low latitudes of the European sector during the magnetic storm of August 25–26, 2018. During the main phase of the storm the ionospheric F2-layer was under the positive disturbance at mid and low latitudes. Then the transition from the positive to negative ΔfoF2 values occurred at all latitudes. The recovery phase was characterized by negative ionospheric disturbance at all latitudes. This is due to the decrease of thermospheric O/N2 ratio during the recovery phase of the storm. The intense Es layers screened the reflections from the F2-layer on August 26th at high and at low latitudes but at different times. Some blackouts occurred due to the high absorption level at high latitudes. In general, foF2 and TEC data were highly correlated. The major Ne changes were at the low latitudes. In general, Ne data confirmed the ionospheric dynamics revealed with foF2 and TEC.     

Estimating sea level rise around Australia using a new approach to account for low frequency climate signals

Regional sea level studies help to identify the vulnerable areas to the sea level rise. This study investigates the impact of climate modes on sea level variations and trends around Australia using altimetry data, climate indices, and sea level records from tide gauge stations. Here, we show that the sea level variations are negatively correlated with climate indices to the north and west of Australia. The spectral analyses of the climate indices and tide gauge data suggest that a low frequency signal with a period of 11 years emerges during the mid 1980s. Since the 25-year length of the satellite altimetry record is yet too short to detect low frequency signals, their effect on the estimation of regional sea level trend is unknown. Therefore, we estimate the sea level trend with consideration of this signal and using a two-step method. All signals with periods shorter than 7.5 years are first removed from sea level time series and then the trend is estimated using the parametric model that includes the 11-year signal. The skill of the parametric model in explaining the variations in sea level anomaly validates the presence of the 11-year signal detected in the spectrograms of the tide gauge data and climate indices. The average sea level trend for the study area is estimated as 3.85 ± 0.15 mm/year.     

Virtual sensing method for monitoring vibration of continuously variable configuration structures using long short-term memory networks

Vibration monitoring by virtual sensing methods has been well developed for linear time-invariant structures with limited sensors. However, few methods are proposed for Time-Varying (TV) structures which are inevitable in aerospace engineering. The core of vibration monitoring for TV structures is to describe the TV structural dynamic characteristics with accuracy and efficiency. This paper propose a new method using the Long Short-Term Memory (LSTM) networks for Continuously Variable Configuration Structures (CVCSs), which is an important subclass of TV structures. The configuration parameters are used to represent the time-varying dynamic characteristics by the “freezing” method. The relationship between TV dynamic characteristics and vibration responses is established by LSTM, and can be generalized to estimate the responses with unknown TV processes benefiting from the time translation invariance of LSTM. A numerical example and a liquid-filled pipe experiment are used to test the performance of the proposed method. The results demonstrate that the proposed method can accurately estimate the unmeasured responses for CVCSs to reveal the actual characteristics in time-domain and modal-domain. Besides, the average one-step estimation time of responses is less than the sampling interval. Thus, the proposed method is promising to on-line estimate the important responses of TV structures.     

Satellite selection methods for multi-constellation advanced RAIM

The increased number of potential threat modes under multi-constellation advanced receiver autonomy integrity monitoring (ARAIM) requires an increase in the number of subsets and a correspondingly high computational load. A new satellite selection method based on integrity support message (ISM) parameters is proposed and compared with GDOP-based selection. The performance was tested on five days of data measurements from 21 multi-global navigation satellite system experiment (MGEX) stations distributed around the world, as well as simulation using the broadcast ephemeris. The results show that the proposed ISM-based satellite selection method is highly compatible with the baseline ARAIM. This method could reduce the computational times by about 60–70% quickly, with minimising vertical protection level (VPL) loss, which was consistently within 1 m, even a reduced VPL value in some epochs, and resulting in an improved availability. The simulation results were similar to the MGEX data. It appears that the application of ISM-based satellite selection can effectively reduce computational burden with a minimal impact on availability.     

Fast cooperative trajectory optimization and test verification for close-range satellite formation using Finite Fourier Series method

The process of formation reconfiguration for close-range satellite formation should take into account the risk of collisions between satellites. To this end, this paper presents a method to rapidly generate low-thrust collision-avoidance trajectories in the formation reconfiguration using Finite Fourier Series (FFS). The FFS method can rapidly generate the collision-avoidance three-dimensional trajectory. The results obtained by the FFS method are used as an initial guess in the Gauss Pseudospectral Method (GPM) solver to verify the applicability of the results. Compared with the GPM method, the FFS method needs very little computing time to obtain the results with very little difference in performance index. To verify the effectiveness, the proposed method is tested and validated by a formation control testbed. Three satellite simulators in the testbed are used to simulate two-dimensional satellite formation reconfiguration. The simulation and experimental results show that the FFS method can rapidly generate trajectories and effectively reduce the risk of collision between satellites. This fast trajectory generation method has great significance for on-line, constantly satellite formation reconfiguration.     

基于模拟退火算法预测储层参数

讨论了如何将地震资料、测井信息和先验地质知识有机地结合起来预测储层参数，以便揭示储层内部细节和纵横向变化特征。通过将模拟退火算法与人工神经网络相结合，能够解决非线性全局优化问题，勾画出地震信息和储层参数之间的复杂关系，为储层特征描述和储层横向预测提供提供直观、可靠的地层参数剖面一孔隙度、砂泥质百分含量、含水饱和度及渗透率等剖面。     

卫星指令控制系统中的信息反馈校验监督

本文讨论采用信息反馈校验方式的卫星指令控制系统的信息反馈校验监督能力问题。提出了关于信息反馈校验指令控制系统的最佳监督概念和校验监督能力的概率表示。还讨论了改善系统校验监督能力的途径。利用本文给出的概率分析方法,可以完成系统性能的评价。     

分布交互仿真的一个原型系统—DIFTS

介绍了分布交互仿真的概念及其背景，分析了它的特点及涉及的关键技术，然后，设计了分布交互仿真的一个原型系统－ＤＩＦＴＳ，分析了ＤＩＦＴＳ的功能模型，并对其进行了功能分解，给出了各模块的功能，最后，介绍了系统的硬件组成及支持工具。     

基于神经网络的多模态故障检测

研究了使用RBF网络进行多模态辨识的结构和其在多模态故障检测中的应用。在信号满足持续激励的条件下 ,状态估计误差渐进趋向于零 ,辨识器的参数估计能够达到满意的效果。使用多个神经网络辨识器 ,对一非线性系统的多模态故障检测进行了仿真研究