Imaging of target with complicated motion using ISAR system based on IPHAF-TVA

The technique of imaging a target with a complicated motion using an Inverse Synthetic Aperture Radar (ISAR) system is an effective tool in the field of radar signal processing. After the translational compensation, the received signal reflected from the target can take the form of a multi-component Polynomial Phase Signal (m-PPS), and the high quality ISAR image can be provided via the combination between the estimated parameters of the m-PPS and the Range Instantaneous-Doppler technique (RID). For a target with a high maneuvrability, the occurrence of scatterers Migration Through Resolution Cell (MTRC), caused by the rotational movement could be appearing. That is why the variation in the amplitude of the echo during the time of observation cannot be neglected. The purpose of this study is the parameters estimation of the m-PPS signal with order three in the case of the Time Varying Amplitude (TVA). The Improved-version of the Product High-order Ambiguity Function (IPHAF) with TVA is proposed to improve the quality of the ISAR image compared with traditional techniques based on a constant amplitude; the experimental outcomes confirm that the new IPHAF-TVA method presented in this study is an effective technique to make the ISAR image very clear.     

球铰接杆式支撑臂展开过程中横向振动分析

针对展开过程中球铰接杆式支撑臂时变构型的横向振动问题,推导了支撑臂等效连续体模型的各向等效刚度,基于Hamilton原理推导了支撑臂展开过程的控制方程,采用加权余量法将偏微分控制方程转化为常微分方程,利用Runge Kutta法对方程进行了数值求解。计算结果表明：在收拢过程中,支撑臂末端的横向振幅越来越小,收拢过程是安全可靠的;而在展开过程中,末端的横向振幅随展开进程而增加,且振幅随末端负载质量增加而增加;若不考虑锁定冲击,展开速度对支撑臂横向振动的振幅影响可忽略,若考虑锁定带来的周期性冲击时,支撑臂的横向振幅将显著增大。为减小支撑臂的横向振动,必须对支撑臂展开速度加以限制。研究结果为航天器支撑臂在轨展开的控制提供了参考。     

The Big Pine Creek watershed and climate change: A trend analysis of Landsat surface reflectance and PRISM datasets over the last 3 decades

Recent variations in normal meteorological conditions indicate the earth’s climate is changing in ways that may impact delicate ecological balances in sensitive regions. Identifying how those changes are affecting the biosphere is essential if we are going to be able to adapt to those changes and to potentially mitigate their harmful consequences. This paper presents a time series study of an alpine ecosystem in the Big Pine Creek watershed in California’s Eastern Sierra Nevada Mountain’s. Raw Landsat data covering the years 1984 through 2011 is converted to observed surface reflectance and analyzed for trends that would indicate a change in the ecosystem. We found that over the time period of the study, observed surface reflectance shows a general decline across the spectrum while our analysis of environmental data demonstrates statistically significant increases in temperatures. While declining reflectance in the visible and short wave bands are indicators of increased surface cover, the fact that the IR band also shows declines is consistent with a decline in tree density. This study provides a useful insight into the ecological response of the Big Pine Creek watershed to recent climate change. These findings suggest that alpine ecosystems are particularly sensitive to increasing temperatures. If these results are replicated in other alpine watersheds it will demonstrate that the biosphere is already showing the effects of a warmer environment.     

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.      

LEVEL DECISION-MAKING FOR AERO-ENGINE MODULES BASED ON INCREMENTAL KNOWLEDGE LEARNING

The maintenance of an aero-engine usually includes three levels, and the maintenance cost and period greatly differ depending on the different maintenance levels. To plan a reasonable maintenance budget program, airlines would like to predict the maintenance level of aero-engine before repairing in terms of performance parame- ters, which can provide more economic benefits. The maintenance level decision rules are mined using the histori- cal maintenance data of a civil aero-engine based on the rough set theory, and a variety of possible models of upda- ting rules produced by newly increased maintenance cases added to the historical maintenance case database are in- vestigated by the means of incremental machine learning. The continuously updated rules can provide reasonable guidance suggestions for engineers and decision support for planning a maintenance budget program before repai- ring. The results of an example show that the decision rules become more typical and robust, and they are more accurate to predict the maintenance level of an aero-engine module as the maintenance data increase, which illus- trates the feasibility of the represented method.     

基于预测扭矩前馈的涡轴发动机内模控制方法

基于内模原理设计了涡轴发动机功率涡轮转速控制器.针对主旋翼扭矩变化对功率涡轮转速的干扰,提出了一种基于极端学习机的扭矩预测方法.极端学习机训练基于动态仿真数据,其输入通过相关分析获得.基于内模原理的功率涡轮转速控制器采用极点配置的设计方法,将输入信号的内模直接加入控制器,实现鲁棒跟踪.扭矩前馈采用比例微分(PD)控制策略,实现对发动机负载变化干扰的有效补偿.数字仿真结果表明:极端学习机扭矩预测精度高,扭矩相对误差小于1.5‰,与不加前馈控制相比,所提出的控制方法减小了机动飞行过程中功率涡轮转速的超调或下垂30%以上.      

应用双向时间传递的重力卫星时标误差自主测量

星间时标误差的自主测量对于中国自主研发地球重力卫星具有重要意义. 提出利用双向时间传递法实现重力卫星时标误差的自主测量, 设计了测量方案, 建立了包含卫星运动导致的链路非对称、电离层效应、设备零值以及随机测时误差在内的测量模型. 结合地球重力卫星相关特性, 分析了时标误差测量中各误差源的影响及相应的误差校正方法. 以GRACE重力卫星为例, 利用提出的方法和校正措施, 星间时标误差自主测量精度可以达到0.62ns, 其中误差主要来自系统零值标定误差和随机测时误差.      

Soybean cultivar selection for Bioregenerative Life Support Systems (BLSSs) – Hydroponic cultivation

Four soybean cultivars (‘Atlantic’, ‘Cresir’, ‘Pr91m10’ and ‘Regir’), selected through a theoretical procedure as suitable for cultivation in BLSS, were evaluated in terms of growth and production. Germination percentage and Mean Germination Time (MGT) were measured. Plants were cultivated in a growth chamber equipped with a recirculating hydroponic system (Nutrient Film Technique). Cultivation was performed under controlled environmental conditions (12 h photoperiod, light intensity 350 μmol m⁻² s⁻¹, temperature regime 26/20 °C light/dark, relative humidity 65–75%). Fertigation was performed with a standard Hoagland solution, modified for soybean specific requirements, and EC and pH were kept at 2.0 dS m⁻¹ and 5.5 respectively.     

声表面波色散延时线激励的高精度时间间隔测量方法

高精度时间间隔测量技术对国民经济与国防建设意义重大,论述了一种新的高精度时间间隔测量方法,可以达到1ps量级甚至更高的测量精度。该方法利用声表面波色散延迟线作为时间内插器,时间内插器起到时间拉伸的作用,从而可以获得多个观测值,由于平均的效果,总的测量误差将被大大降低。理论分析与仿真实验均表明该方法可以达到很高的时间测量精度,是切实可行的。