Impact of rain on wave retrieval from Sentinel-1 synthetic aperture radar images in tropical cyclones

The main objective of our work was to investigate the impact of rain on wave observations from C-band (~5.3 GHz) synthetic aperture radar (SAR) in tropical cyclones. In this study, 10 Sentinel-1 SAR images were available from the Satellite Hurricane Observation Campaign, which were taken under cyclonic conditions during the 2016 hurricane season. The third-generation wave model, known as Simulating WAves Nearshore (SWAN) (version 41.31), was used to simulate the wave fields corresponding to these Sentinel-1 SAR images. In addition, rainfall data from the Tropical Rainfall Measuring Mission satellite passing over the spatial coverage of the Sentinel-1 SAR images were collected. The simulated results were validated against significant wave heights (SWHs) from the Jason-2 altimeter and European Centre for Medium-Range Weather Forecasts data, revealing a root mean square error (RMSE) of ~0.5 m with a 0.25 scatter index. Winds retrieved from the VH-polarized Sentinel-1 SAR images using the Sentinel-1 Extra Wide-swath Mode Wind Speed Retrieval Model after Noise Removal were taken as prior information for wave retrieval. It was discovered that rain did indeed affect the SAR wave retrieval, as evidenced by the 3.21-m RMSE of SWHs between the SAR images and the SWAN model, which was obtained for the ~1000 match-ups with raindrops. The raindrops dampened the wave retrieval when the rain rate was < ~5 mm/hr; however, they enhanced wave retrieval for higher rain rates. It was also found that the portion of the rain-induced ring wave with a wave number > 0.05 rad/m (~125 m wavelength) was clearly observed in the SAR-derived wave spectra.     

基于梯度提升决策树的量子科学实验卫星光学实验预测

量子科学实验卫星在轨运行期间完成4种光学实验，地面监测人员通过遥测参数阈值判断卫星是否进行光学实验、实验类型及实验结果.这种方法需要预先设定大量阈值，并且这些阈值需要根据在轨卫星重新设定，可扩展性较差.针对以上问题，提出一种基于机器学习的光学实验判别方法，将量子科学实验卫星的光学实验监测任务抽象为机器学习中的多元分类问题，构建分类模型，利用量子科学实验卫星的真实历史遥测数据对模型进行训练，并通过真实实验计划对训练得到的模型进行验证.实验结果表明，本文提出的方法在没有专家先验知识的前提下，判别准确率达到99%，可用于量子科学实验卫星光学实验的实时监测任务.提出的基于机器学习的判别方法具有较强的可扩展性，可应用于卫星在轨运行的其他监测任务.      

Research on navigation of satellite constellation based on an asynchronous observation model using X-ray pulsar

Pulsar navigation is a promising navigation method for high-altitude orbit space tasks or deep space exploration. At present, an important reason for restricting the development of pulsar navigation is that navigation accuracy is not high due to the slow update of the measurements. In order to improve the accuracy of pulsar navigation, an asynchronous observation model which can improve the update rate of the measurements is proposed on the basis of satellite constellation which has a broad space for development because of its visibility and reliability. The simulation results show that the asynchronous observation model improves the positioning accuracy by 31.48% and velocity accuracy by 24.75% than that of the synchronous observation model. With the new Doppler effects compensation method in the asynchronous observation model proposed in this paper, the positioning accuracy is improved by 32.27%, and the velocity accuracy is improved by 34.07% than that of the traditional method. The simulation results show that without considering the clock error will result in a filtering divergence.     

刹车装置性能试验台系统设计

主要介绍了刹车装置性能试验台的实现机理、采用的方案,有助于增进对液压试验台设计和可编程控制器PLC应用方面的了解。     

关于CCSDS体制数据安全保护实施位置的探讨

主要阐述CCSDS（空间数据系统咨询委员会）标准的信息安全问题，重点是航天器安全，从分析空间数据面临的安全威胁出发，讨论了CCSDS不同安全实施位置的特点；并在此基础上，通过对CCSDS业务及数据结构的影响对比，总结出不同安全实施方法的优缺点，该结合对于采用CCSDS标准的空间数据系统如何解决信息安全问题，具有一定的参考价值。     

FET振荡器注入锁相伏特拉级数分析

应用伏特拉级数法分析了电容耦合ＦＥＴ振荡系统在外加信号下的注入锁定现象，推导出输出信号和注入锁定带宽表达式。与一般非线性系统分析方法相比，伏特拉级数法在建立好系统模型后只需进行代数运算，从而避开了求解非线性，非齐次高阶微分方程的复杂过程。     

准各向同性基层上椭圆形子层的屈曲

通过改进文献[1]中假设的挠度函数,使Rayleigh-Ritz法能用于计算准各向同性基层上任意对称椭圆形子层的临界应变,然后以单向层板为主,探讨了临界应变随基层泊桑比ν,椭圆半轴之比λ,子层角θ和单层铺设角α的变化规律。     

最坏风模型及对飞机突防航迹跟踪的影响

针对一类非线性动力学系统,本文推导出二次型性能指标下的微分对策解,由此得到一组含有非线性因素的最环风模型,这一模型特别适用于研究作空间机动飞行的飞机受外界环境扰动的灵敏性问题。最后考察了这一变化风场对飞机突防航迹非线性解耦跟踪的影响。     

减压活门性能试验台系统方案设计

主要介绍了减压活门性能试验台的实现机理、采用的方案。     

Application of Gram-Schmidt algorithm to fully adaptive arrays

The Gram-Schmidt orthogonalization (GSO) algorithm has excellent numerical performance and is readily applicable to systolic implementations such as in a field of adaptive cancellation systems. A modified GSO algorithm for a fully adaptive array is proposed and computer simulations show that the proposed algorithm gives superior performance. A systolic implementation of the proposed GSO algorithm for fully adaptive array is presented. A feedback mode GSO algorithm for use with analog weights is also presented and has been shown to have excellent performance in the presence of weight errors