Assessment of the close approach frequency and collision probability for satellites in different configurations of large constellations

The Earth orbital environment is drastically changing due to an intensification of the space activities. In particular, several projects of large constellations, proposed for the next years for communications purpose like global internet access, Internet of Things, or for Earth observations, will lead to the deployment of several thousands of new satellites at an unprecedented rate. It is a crucial challenge for space traffic management, which will deal with a great number of satellite conjunctions, potentially causing a collision with damaging consequences for the constellation itself and the space environment sustainability.In this paper, we investigate the close approach frequency and the cumulative collision probability for each referenced constellation. For this purpose, we compute the orbital evolution of satellites in different constellations during the lifecycle, from the deployment to the decommissioning, and we apply the CUBE algorithm and the Foster method to assess the collision probability with the background space debris population assuming a constant uncertainty in position. We show the variation of risk defined by the close approach frequency and the cumulative collision probability as a function of the proposed configuration. In particular, satellites of the Iridium and Kuiper constellation, but also satellite of the Telesat constellation on polar orbits are the most exposed at a collision. Moreover, the decommissioning phase contribute for a major part to the final cumulative collision probability.     

Semi-supervised gear fault diagnosis using raw vibration signal based on deep learning

In aerospace industry, gears are the most common parts of a mechanical transmission system. Gear pitting faults could cause the transmission system to crash and give rise to safety disaster. It is always a challenging problem to diagnose the gear pitting condition directly through the raw signal of vibration. In this paper, a novel method named augmented deep sparse autoencoder (ADSAE) is proposed. The method can be used to diagnose the gear pitting fault with relatively few raw vibration signal data. This method is mainly based on the theory of pitting fault diagnosis and creatively combines with both data augmentation ideology and the deep sparse autoencoder algorithm for the fault diagnosis of gear wear. The effectiveness of the proposed method is validated by experiments of six types of gear pitting conditions. The results show that the ADSAE method can effectively increase the network generalization ability and robustness with very high accuracy. This method can effectively diagnose different gear pitting conditions and show the obvious trend according to the severity of gear wear faults. The results obtained by the ADSAE method proposed in this paper are compared with those obtained by other common deep learning methods. This paper provides an important insight into the field of gear fault diagnosis based on deep learning and has a potential practical application value.     

Orbit-attitude-vibration coupled dynamics of tethered solar power satellite

A new orbit-attitude-vibration coupled dynamic model of the tethered solar power satellite (Tethered SPS) is established based on absolute nodal coordinate formulation. The Hamilton’s equation of the system is derived by introducing generalized momentum through Legendre transformation. The correctness of the proposed model is verified by an example. The dynamic characteristics of the Tethered SPS are studied using the symplectic Runge-Kutta method. Simulation results show that the orbital radius and the total energy of the system are well preserved. The attitude of the system is unstable when the mass of the bus system is small. However, the attitude stability is dependent on some other parameters of the system, which requires further studies. It is also found that the average tether force/deformation can be roughly estimated by simplifying the solar panel as a particle. The proposed model can be used to study the orbit-attitude-vibration coupled dynamics and control problems.     

Substitution of satellite-based land surface temperature defective data using GSP method

Land surface temperature (LST) as an important environmental variable provides valuable information for earth environmental system modelling. Currently, LST is obtained through satellite thermal sensors at various spatial and temporal resolutions. Although spatially continuous satellite-based LST measurements are intended to overcome the shortcomings of sparse ground-based LST measurements, LST images often contain anomalous values due to the existence of clouds or sensor malfunctioning. The problem becomes more serious where the users deal with high spatial resolution characterized by low temporal resolution. This study examines the capability of a newly developed graph signal processing (GSP) method using two-dimensional single-date thermal data. For this purpose, four Landsat/TIRS datasets are analyzed. The data of five elliptical regions on thermal images are eliminated and then reconstructed through the GSP method and using the LST values of the enclosing rectangles containing the ellipsoids. The results indicate that the temperature variation determined by the GSP method generally conforms to the original image LST values. According to a correlation test conducted on the original image LST and those obtained through the GSP method, the values vary from 58% to 95%, which is an above-the-average rate (RMSE from 0.69 to 2.27). The statistical analysis of the original image LST in both the elliptical regions and the enclosing rectangles containing the ellipsoids indicates that an increase in the variance of LST data causes an increased error in the calculation of temperature by the GSP method, and vice versa. The results of the analysis of variance (ANOVA) and Duncan test indicated that an increase in the number of the non-zero spectral bins would result in increased RMSE values for all the dates and the regions. Moreover, the model errors were significant at the 0.05 level across all the image date and five elliptical study regions. Based on the results, the use of this method is recommended for the reconstruction of LST missing values, where dissimilarity of atmospheric conditions limits the use of other methods that depend on the time series data of various dates and a great deal of data calculation.     

A robust object-based shadow detection method for cloud-free high resolution satellite images over urban areas and water bodies

Unwanted contrast in high resolution satellite images such as shadow areas directly affects the result of further processing in urban remote sensing images. Detecting and finding the precise position of shadows is critical in different remote sensing processing chains such as change detection, image classification and digital elevation model generation from stereo images. The spectral similarity between shadow areas, water bodies, and some dark asphalt roads makes the development of robust shadow detection algorithms challenging. In addition, most of the existing methods work on pixel-level and neglect the contextual information contained in neighboring pixels. In this paper, a new object-based shadow detection framework is introduced. In the proposed method a pixel-level shadow mask is built by extending established thresholding methods with a new C₄ index which enables to solve the ambiguity of shadow and water bodies. Then the pixel-based results are further processed in an object-based majority analysis to detect the final shadow objects. Four different high resolution satellite images are used to validate this new approach. The result shows the superiority of the proposed method over some state-of-the-art shadow detection method with an average of 96% in F-measure.     

高速低压差分信号（LVDS）器件应用设计方法研究

随着高速LVDS器件得到广泛应用，在高速信号使用LVDS传输时，信号传输线路问题、信号传输波形的最佳化成为非常重要的课题之一。由于印制电路板的布局布线直接影响信号传输质量，因此利用仿真对印制板分析成为设计上不可缺少的手段。有鉴于此，文章深入探讨了高速电路的设计，总结出设计技巧。     

CBERS-1卫星IRMSS数据在城市绿地系统规划的应用

文章以CBERS -1卫星长沙幅IRMSS数据作为基础资料 ,利用PCI遥感图像处理软件对数据进行了预处理和应用实验。实验证明CBERS -1卫星的IRMSS数据图像信息丰富 ,可解译程度较高 ,能满足大中城市中等比例尺城市绿地系统规划遥感调查的要求     

对“ZY-1”FM1整星热平衡、热真空试验中有效载荷被污染情况的分析

介绍了卫星在热平衡试验后所发现的有效载荷的污染情况,通过对污染提取物的分析和试验设备的再次污染监测,找出了污染源,并对以后的防污染工作提供了借鉴.     

CBERS-1卫星红外多光谱扫描仪扫描子系统

文章介绍了CBERS -1卫星红外多光谱扫描仪(IRMSS)关键部件扫描子系统研制与应用情况。     

高速低压差分信号(LVDS)器件应用设计方法研究

随着高速LVDS器件得到广泛应用,在高速信号使用LVDS传输时,信号传输线路问题、信号传输波形的最佳化成为非常重要的课题之一。由于印制电路板的布局布线直接影响信号传输质量,因此利用仿真对印制板分析成为设计上不可缺少的手段。有鉴于此,文章深入探讨了高速电路的设计,总结出设计技巧。