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首页> 外文会议>Sensors, systems, and next-generation satellites XX >CASE STUDIES FOR OBSERVATION PLANNING ALGORITHM OF A JAPANESE SPACEBORNE SENSOR: HYPERSPECTRAL IMAGER SUITE (HISUI)
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CASE STUDIES FOR OBSERVATION PLANNING ALGORITHM OF A JAPANESE SPACEBORNE SENSOR: HYPERSPECTRAL IMAGER SUITE (HISUI)

机译：日本空间发射传感器观测计划算法的案例研究：超光谱IMAGER SUITE（HISUI）

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摘要

Hyperspectral Imager Suite (HISUI)[1] is a Japanese future spaceborne hyperspectral instrument being developed by Ministry of Economy, Trade, and Industry (METI) and will be delivered to ISS in 2018. In HISUI project, observation strategy is important especially for hyperspectral sensor, and relationship between the limitations of sensor operation and the planned observation scenarios have to be studied. We have developed concept of multiple algorithms approach. The concept is to use two (or more) algorithm models (Long Strip Model and Score Downfall Model) for selecting observing scenes from complex data acquisition requests with satisfactory of sensor constrains. We have tested the algorithm, and found that the performance of two models depends on remaining data acquisition requests, i.e. distribution score along with orbits. We conclude that the multiple algorithms approach will be make better collection plans for HISUI comparing with single fixed approach.
机译：高光谱成像仪套件（HISUI）[1]是日本经济产业省（METI）开发的日本未来星载高光谱仪器，将于2018年交付给ISS。在HISUI项目中，观察策略对高光谱尤为重要传感器，以及传感器操作的局限性与计划的观察方案之间的关系，必须进行研究。我们已经开发了多种算法方法的概念。该概念是使用两个（或多个）算法模型（长条带模型和得分下降模型）从传感器满意的复杂数据采集请求中选择观察场景。我们测试了该算法，发现两个模型的性能取决于剩余的数据采集请求，即分布分数和轨道。我们得出结论，与单一固定方法相比，多种算法方法将是针对HISUI的更好的收集计划。

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