新一代GNSS接收机的智能跟踪状态评估技术

新一代全球导航卫星系统的接收机需要根据用户所处环境,自适应地调整接收机内部参数以达到最稳健的导航效果。这就要求接收机在运行过程中通过评估跟踪状态去检测和分析用户场景。基于对传统接收机控制系统缺陷的分析,提出了智能接收机的概念、特点及系统框架;在此基础上设计、分析接收机的智能跟踪状态评估算法;最后通过仿真验证了所设计的算法可以有效地识别场景及场景间的切换。     

Automatic detection of geomagnetic sudden commencement via time–frequency clusters

One of global processes in ionosphere–thermosphere–magnetosphere system is the geomagnetic storms. It is of great importance to develop an algorithm that auto-detects sudden commencement because it could be an indicator of onset of the geomagnetic storm. Automatic detection of geomagnetic sudden commencement is based on time–frequency clusters generated by spectrogram. Proposed algorithm is tested on data set collected from stations belong to the international real-time magnetic observatory network (INTERMAGNET). Maximum standard deviation of algorithm detection times is observed to be one minute of the corresponding arrival times published by National Geophysical Data Center (NGDC).     

A feasibility study for the detection of the diurnal variation of tropospheric NO2 over Tokyo from a geostationary orbit

We have conducted a feasibility study for the geostationary monitoring of the diurnal variation of tropospheric NO₂ over Tokyo. Using NO₂ fields from a chemical transport model, synthetic spectra were created by a radiative transfer model, SCIATRAN, for summer and winter cases. We then performed a Differential Optical Absorption Spectroscopy (DOAS) analysis to retrieve NO₂ slant column densities (SCDs), and after converting SCDs into vertical column densities (VCDs), we estimated the precision of the retrieved VCDs. The simulation showed that signal-to-noise ratio (SNR) ? 500 is needed to detect the diurnal variation and that SNR ? 1000 is needed to observe the local minimum occurring in the early afternoon (LT13–14) in summer. In winter, the detection of the diurnal variation during LT08–15 needs SNR ? 500, and SNR ? 1000 is needed if early morning (LT07) and early evening (LT16) are included. The currently discussed sensor specification for the Japanese geostationary satellite project, GMAP-Asia, which has a horizontal resolution of 10 km and a temporal resolution of 1hr, has demonstrated the performance of a precision of several percent, which is approximately corresponding to SNR = 1000–2000 during daytime and SNR ? 500 in the morning and evening. We also discuss possible biases caused by the temperature dependence of the absorption cross section utilized in the DOAS retrieval, and the effect of uncertainties of surface albedo and clouds on the estimation of precisions.     

A holistic approach to SIM platform and its application to early-warning satellite system

This study proposes a new simulation platform named Simulation Integrated Management (SIM) for the analysis of parallel and distributed systems. The platform eases the process of designing and testing both applications and architectures. The main characteristics of SIM are flexibility, scalability, and expandability. To improve the efficiency of project development, new models of early-warning satellite system were designed based on the SIM platform. Finally, through a series of experiments, the correctness of SIM platform and the aforementioned early-warning satellite models was validated, and the systematical analyses for the orbital determination precision of the ballistic missile during its entire flight process were presented, as well as the deviation of the launch/landing point. Furthermore, the causes of deviation and prevention methods will be fully explained. The simulation platform and the models will lay the foundations for further validations of autonomy technology in space attack-defense architecture research.     

Predictive fault-tolerant control of an all-thruster satellite in 6-DOF motion via neural network model updating

The problem of controlling an all-thruster spacecraft in the coupled translational-rotational motion in presence of actuators fault and/or failure is investigated in this paper. The nonlinear model predictive control approach is used because of its ability to predict the future behavior of the system. The fault/failure of the thrusters changes the mapping between the commanded forces to the thrusters and actual force/torque generated by the thruster system. Thus, the basic six degree-of-freedom kinetic equations are separated from this mapping and a set of neural networks are trained off-line to learn the kinetic equations. Then, two neural networks are attached to these trained networks in order to learn the thruster commands to force/torque mappings on-line. Different off-nominal conditions are modeled so that neural networks can detect any failure and fault, including scale factor and misalignment of thrusters. A simple model of the spacecraft relative motion is used in MPC to decrease the computational burden. However, a precise model by the means of orbit propagation including different types of perturbation is utilized to evaluate the usefulness of the proposed approach in actual conditions. The numerical simulation shows that this method can successfully control the all-thruster spacecraft with ON-OFF thrusters in different combinations of thruster fault and/or failure.     

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.