Search

Satellite area coverage analysis is complex, especially when the satellite operating state changes. Traditional algorithms cannot quickly and efficiently obtain the satellite area coverage analysis results, and are incapable of providing efficient online services. To overcome these shortcomings and meet the needs of 21st century geospatial science and applications for real-time response and online services for handling high concurrent requests, a data-driven real-time analysis service for satellite area coverage is proposed. Firstly, to optimize traditional algorithms, an extended bounding rectangle of the ground area is constructed, and the spatial relationship with the central point of satellite ground coverage area is determined to avoid large number of calculations of satellite ground coverage areas, thus, improving efficiency. Secondly, the data-driven real-time analysis model is constructed, and is used to further improve the efficiency of satellite area coverage analysis. Finally, a simulation analysis scenario is developed, the service proposed in this study is verified, and the results are visualized. The experimental results show that the proposed data-driven real-time analysis service can cope well with the requests from users for online service of satellite area coverage, improve the cognitive capability of users and operators, and help in completely utilizing the application performance of observation satellites.

Due to the ability of flexible, accurate, and fast obtaining abundant information, airborne SAR is significant in the field of Earth Observation and many other applications. Optimally the flight paths are straight lines, but in reality it is not the case since some portion of deviation from the ideal path is impossible to avoid. A small disturbance from the ideal line will have a major effect on the signal phase, dramatically deteriorating the quality of SAR images and data. Therefore, to get accurate echo information and radar images, it is essential to measure and compensate for nonlinear motion of antenna trajectories. By means of compensating each flying trajectory to its reference track, MOCO method corrects linear phase error and quadratic phase error caused by nonlinear antenna trajectories. Position and Orientation System (POS) data is applied to acquiring accuracy motion attitudes and spatial positions of antenna phase centre (APC). In this paper, extend chirp scaling algorithm (ECS) is used to deal with echo data of airborne SAR. An experiment is done using VV-Polarization raw data of C-band airborne SAR. The quality evaluations of compensated SAR images and uncompensated SAR images are done in the experiment. The former always performs better than the latter. After MOCO processing, azimuth ambiguity is declined, peak side lobe ratio (PSLR) effectively improves and the resolution of images is improved obviously. The result shows the validity and operability of the imaging process for airborne SAR.