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Automated Mission Planning System for Ocean Observation of Micro-satellite RISESAT

机译:微型卫星上涨的海洋观测自动化任务规划系统

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In this paper, we evaluate the performance of the automated mission planning system which we developed for ocean observation of microsatellite RISESAT. RISESAT is equipped with multiple scientific instruments including Ocean Observation Camera (OOC). OOC is a wide field of view camera system and sweeps the ocean surface to evaluate the amount of Colored Dissolved Organic Matter (CDOM), which influences the carbon cycle in this planet, which is closely related to climate change. Constraint conditions exist mainly in terms of cloud coverage and the elevation angle of the satellite at a targeted point because OOC observation is conducted in the range of the visible light spectrum. Therefore, we developed an automatic mission planning system based on cloud forecasts for efficient ocean observation. In this system, we use Open Weather Map (OWM) to create cloud forecasts, and Two Line Element (TLE) and Simplified General Perturbations Satellite Orbit Model (SGP4) for orbit prediction of the satellite. Then, we propose an algorithm to output an optimised mission plan maximising the total profit. Furthermore, the performance of the system was evaluated by actual images taken by OOC and we confirmed that this system captured targeted regions properly.
机译:在本文中,我们评估了我们开发用于海洋观察微卫星上篮的自动化任务规划系统的表现。 Risesat配备多种科学仪器,包括海洋观察相机(OOC)。 OOC是一系列宽视野,并扫过海洋表面以评估彩色溶解有机物(CDOM)的量,这影响了该行星中的碳循环,这与气候变化密切相关。约束条件主要以云覆盖率和卫星在目标点处的仰角存在,因为在可见光谱的范围内进行OOC观察。因此,我们开发了基于云预测的自动任务规划系统,以获得高效的海洋观察。在该系统中,我们使用开放气象图(OWM)来创建云预测和两个线元素(TLE)和简化的一般扰动卫星轨道模型(SGP4),用于卫星预测。然后,我们提出了一种算法来输出优化的任务计划,最大化总利润。此外,通过OOC拍摄的实际图像来评估系统的性能,我们确认该系统适当地捕获了目标区域。

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