Human Mission from Planet Earth: finding a rationale for exploration of the Moon and Mars

This paper advances scenarios for an evolutionary approach to the establishment of a Human Mission from Planet Earth involving exploration and utilization of the Moon and Mars. Of critical importance are the concepts of robotic–human and Moon–Mars synergies. The paper discusses the rationale variables that have an influence on types of space activities pursued and thus the policy that leads to particular scenarios. In this regard, the technological, scientific, and sociopolitical/socioeconomic impacts and consequences related to a Human Mission from Planet Earth are examined.     

Hybrid optimization for multiple-impulse reconfiguration trajectories of satellite formation flying

A hybrid optimization method is developed for fuel-optimal reconfigurations of a group of satellites flying in formation. The genetic algorithm performs a global search to find two-impulse trajectories, and primer vector analysis finds multiple-impulsive local optimal trajectories with the two-impulse trajectories as initial guesses. Hybrid optimization finds globally optimal trajectories for formation reconfigurations, including formation resizing, reassignment and reorientation maneuvers. Multiple-impulse trajectories reduce the fuel consumption from the two-impulse trajectories by up to 4.4% for those maneuvers. In real missions, satellites can follow two-impulse trajectories to gain the advantage of a smaller number of impulses, with the cost of slightly more propellant. The qualitative characteristics of the optimal trajectories are analyzed from the number of optimal trajectories found by hybrid optimization.     

Use of the ASTER satellite images for evaluation of structural changes in the Popocatépetl volcano related to microseismicity

Mexico is one of the most volcanically active regions in North America. Volcanic activity in central Mexico is associated with the subduction of the Cocos and Rivera plates beneath the North American plate. Periods of enhanced microseismic activity, associated with the volcanic activity of the Popocatépetl volcano are compared with periods, during which the microseismic activity was low. We detected systematical changes in the number of lineaments, associated with the microseismic activity due to lineament analysis of a temporal sequence of high resolution satellite images of the Popocatépetl volcano, provided by the ASTER/VNIR instrument. The Lineament Extraction and Stripes Statistic Analysis (LESSA) software package was used for the lineament extraction. In the future it would allow develop a methodology for detection of possible elevation of pressure in volcano edifice.     

The Scanning Sky Monitor (SSM) on ASTROSAT

The Scanning Sky Monitor is one of the experiments onboard the ASTROSAT, an Indian multiwavelength astronomy satellite mission. This experiment will detect and monitor X-ray transients in the energy band 2–10 keV. It is similar in design to the ASM on RXTE. It consists of position-sensitive proportional counters with one-dimensional mask. We describe the configuration of the experiment. We also discuss some of the results obtained using a detector which has already been fabricated and tested in our laboratory.     

卫星ATM网络中自适应FEC情况下的有效带宽估计

针对采用自适应前向差错控制（AFEC）的卫星异步传递模式（ATM）网络，研究了两种有效带宽估计方法。由于AFEC码率的动态特性使业务实际的传输速率具有不固定性，因此估计有效带宽时要考虑AFEC的影响。首先针对一般卫星时变信道和多码率AFEC情况下的卫星ATM，应用流体近似方法分析了有效带宽的计算，然而该方法要求的条件及计算复杂度均比较高，应用中有局限性。以此方法为基础，提出了采用修正因子的估计方法。数值结果表明采用修正因子的有效带宽估计方法比较简单可靠，适用面较广。     

卫星用半导体器件失效模式和机理分布

以中国空间技术研究院电子元器件可靠性中心1987～1990四个年度数百份失效分析报告为依据,得到卫星用半导体器件解剖前失效模式分布:逻辑失控占36.3%,开路占22.2%等;失效机理分布:铝腐蚀占1 6.3%,使用不当占14.6%等。该项研究以第一手数据首次全面、系统指出卫星用器件失效模式和机理。为卫星可靠性设计、优选器件厂及器件厂采取措施提供重要依据。     

First results from the LUCID-Timepix spacecraft payload onboard the TechDemoSat-1 satellite in Low Earth Orbit

The Langton Ultimate Cosmic ray Intensity Detector (LUCID) is a payload onboard the satellite TechDemoSat-1, used to study the radiation environment in Low Earth Orbit ($～$635?km). LUCID operated from 2014 to 2017, collecting over 2.1 million frames of radiation data from its five Timepix detectors on board. LUCID is one of the first uses of the Timepix detector technology in open space, with the data providing useful insight into the performance of this technology in new environments. It provides high-sensitivity imaging measurements of the mixed radiation field, with a wide dynamic range in terms of spectral response, particle type and direction. The data has been analysed using computing resources provided by GridPP, with a new machine learning algorithm that uses the Tensorflow framework. This algorithm provides a new approach to processing Medipix data, using a training set of human labelled tracks, providing greater particle classification accuracy than other algorithms. For managing the LUCID data, we have developed an online platform called Timepix Analysis Platform at School (TAPAS). This provides a swift and simple way for users to analyse data that they collect using Timepix detectors from both LUCID and other experiments. We also present some possible future uses of the LUCID data and Medipix detectors in space.     

A modern robust approach to remotely estimate chlorophyll in coastal and inland zones

The chlorophyll concentration of a water body is an important proxy for representing the phytoplankton biomass. Its estimation from multi or hyper-spectral remote sensing data in natural waters is generally achieved by using (i) the waveband ratioing in two or more bands in the blue-green or (ii) by using a combination of the radiance peak position and magnitude in the red-near-infrared (NIR) spectrum. The blue-green ratio algorithms have been extensively used with satellite ocean color data to investigate chlorophyll distributions in open ocean and clear waters and the application of red-NIR algorithms is often restricted to turbid productive water bodies. These issues present the greatest obstacles to our ability to formulate a modern robust method suitable for quantitative assessments of the chlorophyll concentration in a diverse range of water types. The present study is focused to investigate the normalized water-leaving radiance spectra in the visible and NIR region and propose a robust algorithm (Generalized ABI, GABI algorithm) for chlorophyll concentration retrieval based on Algal Bloom index (ABI) which separates phytoplankton signals from other constituents in the water column. The GABI algorithm is validated using independent in-situ data from various regional to global waters and its performance is further evaluated by comparison with the blue-green waveband ratios and red-NIR algorithms. The results revealed that GABI yields significantly more accurate chlorophyll concentrations (with uncertainties less than 13.5%) and remains more stable in different waters types when compared with the blue-green waveband ratios and red-NIR algorithms. The performance of GABI is further demonstrated using HICO images from nearshore turbid productive waters and MERIS and MODIS-Aqua images from coastal and offshore waters of the Arabian Sea, Bay of Bengal and East China Sea.     

低轨卫星缺失时序数据的模式识别方法

在航天应用中，低轨卫星经常会由于原始数据缺失而影响卫星时序数据模式识别结果，降低准确率。针对该问题提出了一种新型MR-GRU模型，可有效处理缺失时序数据，并获得较好的模式识别准确率。区别于传统模型的补全缺失数据的方法，MR-GRU模型直接在缺失时序数据上运用循环神经网络进行训练，对传统门控循环单元结构进行了改进，增加了两个新变量：掩蔽项和衰减项。掩蔽项作用于输入，衰减项作用于输入和隐层单元输出。MR-GRU模型不仅能够保持时序数据固有的时间特性，还能有效提高模式识别精度。在卫星时序数据上的模式识别试验表明，MR-GRU模型准确率优于传统模型。