动态瞄准改进地球科学任务

IF 1.3 4区工程技术 Q2 ENGINEERING, AEROSPACE

Journal of Aerospace Information Systems Pub Date : 2023-11-01 DOI:10.2514/1.i011233

Alberto Candela, Jason Swope, Steve A. Chien

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引用次数: 0

摘要

动态定位(DT)是一个新兴的概念，它使用前瞻性仪器的数据来智能地重新配置和指向主要仪器，以提高科学回报。例如，在智能寻冰雷达(智能冰云传感项目)中，使用前视辐射计探测深层对流冰暴，然后使用雷达定位。在其他概念中，前视传感器用于探测云，以便主传感器可以避开它们。为此，我们从运筹学和人工智能/启发式搜索中开发了几种算法来指向/重新配置动态仪器。我们对这些概念进行了DT的模拟研究，并对这些算法进行了基准测试，以表明DT是一个强大的工具，具有显着提高仪器科学产量的潜力。

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Dynamic Targeting to Improve Earth Science Missions

Dynamic targeting (DT) is an emerging concept in which data from a lookahead instrument are used to intelligently reconfigure and point a primary instrument to enhance science return. For example, in the smart ice hunting radar (Smart Ice Cloud Sensing project), a forward-looking radiometer is used to detect deep convective ice storms, which are then targeted using a radar. In other concepts, forward-looking sensors are used to detect clouds so that a primary sensor can avoid them. To this end, we have developed several algorithms from operations research and an artificial intelligence/heuristic search to point/reconfigure the dynamic instrument. We present simulation studies of DT for these concepts and benchmark these algorithms to show that DT is a powerful tool with the potential to significantly improve instrument science yield.

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来源期刊

Journal of Aerospace Information Systems ENGINEERING, AEROSPACE-

CiteScore

3.70

自引率

13.30%

发文量

审稿时长

>12 weeks

期刊介绍： This Journal is devoted to the dissemination of original archival research papers describing new theoretical developments, novel applications, and case studies regarding advances in aerospace computing, information, and networks and communication systems that address aerospace-specific issues. Issues related to signal processing, electromagnetics, antenna theory, and the basic networking hardware transmission technologies of a network are not within the scope of this journal. Topics include aerospace systems and software engineering; verification and validation of embedded systems; the field known as ‘big data,’ data analytics, machine learning, and knowledge management for aerospace systems; human-automation interaction and systems health management for aerospace systems. Applications of autonomous systems, systems engineering principles, and safety and mission assurance are of particular interest. The Journal also features Technical Notes that discuss particular technical innovations or applications in the topics described above. Papers are also sought that rigorously review the results of recent research developments. In addition to original research papers and reviews, the journal publishes articles that review books, conferences, social media, and new educational modes applicable to the scope of the Journal.