{"project":{"acronym":"","projectId":18665,"title":"Tradespace Analysis Tool for Designing Earth Science Distributed Missions","primaryTaxonomyNodes":[{"taxonomyNodeId":10833,"taxonomyRootId":8816,"parentNodeId":10831,"level":3,"code":"TX11.4.2","title":"Intelligent Data Understanding","definition":"Intelligent data understanding technologies provide the ability to automatically mine and analyze datasets that are large, noisy, and of varying modalities, including discrete, continuous, text, and graphics, and extract or discover information that can be used for further analysis or decision making.","exampleTechnologies":"Intelligent data collection and prioritization toolset, event detection and intelligent action toolset, data on demand toolset, intelligent data search and mining toolset, data fusion toolset, information representation standards for persistent data, artificial intelligence (AI), robot-automated cross-program standardization","hasChildren":false,"hasInteriorContent":true}],"startTrl":2,"currentTrl":3,"description":"The ESTO 2030 Science Vision envisions the future of Earth Science to be characterized by 'many more distributed observations,' and 'formation-flying [missions that] will have the ability to reconfigure on the fly and constellations of complementary satellites with different capabilities will work together autonomously.' All these concepts refer to 'Distributed Spacecraft Missions (DSMs)', i.e., missions that involve multiple spacecraft to achieve one or more common goals, and more particularly to 'constellations' or 'formations', i.e., missions designed as distributed missions with specific orbits from inception (in contrast to virtual or ad-hoc DSMs being formed after launch). DSMs include multiple configurations such as homogenous and heterogeneous constellations, formation flying clusters and fractionated spacecraft. They are gaining momentum in all science domains, because of their ability to optimize the return on investment in terms of science benefits, aided by the increasing prevalence of small satellites. In Earth science, DSMs have the unique ability to increase observation sampling in spatial, spectral and temporal dimensions simultaneously. Many future missions have been studying the possibility of using constellations to satisfy their science goals. However, since DSM architectures are defined by monolithic architecture variables and variables associated with the distributed framework, designing an optimal DSM requires handling a very large number of variables, which increases further in heterogeneous cases. Additionally, DSMs are expected to increase mission flexibility, scalability, evolvability and robustness and to minimize cost risks associated with launch and operations. As a result, DSM design is a complex problem with many design variables and multiple conflicting objectives. There are very few open-access tools available to explore the tradespace of variables, minimize cost and maximize performance for pre-defined science goals, and therefore select the most optimal design. Over the last year, our team developed a prototype tool using the MATLAB engine and interfacing with AGI's Systems Tool Kit. The prototype tool is capable of generating hundreds of DSM architectures using a few pre-defined design variables, e.g., number of spacecraft, number of orbital planes, altitudes, swath widths, etc. and sizing the architectures' performance using the limited metrics available in the off-the-shelf components. Currently, only Walker constellations are being considered. We have found off-the-shelf components do not support the necessary functionality to explore and optimize DSMs based on specific science objectives and architecture requirements. In the proposed work, the tool will be generalized to consider a larger number of parameters and metrics and different types of constellations, to enable analysis and design of architectures in terms of pre-defined science, cost, and risk metrics. The product will leverage existing modeling and analysis capabilities available in the General Mission Analysis Tool (GMAT), developed at NASA Goddard. GMAT is an open source, trajectory optimization and design system, designed to model and optimize spacecraft trajectories in flight regimes ranging from low Earth orbit to lunar applications, interplanetary trajectories, and other deep space missions. The tool will include a user-friendly interface that will enable Earth Scientists to easily perform tradespace analyses and to interface with this tool when performing trades on planned instruments and when conducting Observing System Simulation Experiments (OSSEs) for mission design. The software developed under this proposal will enable: (1) better science through distributed missions, (2) better communication between mission designers and scientists, (3) more rapid trade studies, (4) better understanding of the trade space as it relates to science return. The final tool will be offered open source to the Earth Science community.","destinations":[{"lkuCodeId":1543,"code":"EARTH","description":"Earth","lkuCodeTypeId":526,"lkuCodeType":{"codeType":"DESTINATION_TYPE","description":"Destination Type"}}],"startYear":2015,"startMonth":4,"endYear":2017,"endMonth":3,"statusDescription":"Completed","principalInvestigators":[{"contactId":190272,"canUserEdit":false,"firstName":"Jacqueline","lastName":"Le Moigne","fullName":"Jacqueline J Le Moigne","fullNameInverted":"Le Moigne, Jacqueline J","middleInitial":"J","primaryEmail":"Jacqueline.J.LeMoigne-Stewart@nasa.gov","publicEmail":true,"nacontact":false}],"programDirectors":[{"contactId":363458,"canUserEdit":false,"firstName":"Pamela","lastName":"Millar","fullName":"Pamela S Millar","fullNameInverted":"Millar, Pamela S","middleInitial":"S","primaryEmail":"pamela.s.millar@nasa.gov","publicEmail":true,"nacontact":false}],"programManagers":[{"contactId":190272,"canUserEdit":false,"firstName":"Jacqueline","lastName":"Le Moigne","fullName":"Jacqueline J Le Moigne","fullNameInverted":"Le Moigne, Jacqueline J","middleInitial":"J","primaryEmail":"Jacqueline.J.LeMoigne-Stewart@nasa.gov","publicEmail":true,"nacontact":false}],"coInvestigators":[{"contactId":375348,"canUserEdit":false,"firstName":"Philip","lastName":"Dabney","fullName":"Philip Dabney","fullNameInverted":"Dabney, Philip","primaryEmail":"philip.w.dabney@nasa.gov","publicEmail":true,"nacontact":false},{"contactId":360572,"canUserEdit":false,"firstName":"Oliver","lastName":"De Weck","fullName":"Oliver L De Weck","fullNameInverted":"De Weck, Oliver L","middleInitial":"L","primaryEmail":"deweck@mit.edu","publicEmail":false,"nacontact":false},{"contactId":506184,"canUserEdit":false,"firstName":"Steven","lastName":"Hughes","fullName":"Steven P Hughes","fullNameInverted":"Hughes, Steven P","middleInitial":"P","primaryEmail":"steven.p.hughes@nasa.gov","publicEmail":true,"nacontact":false},{"contactId":225738,"canUserEdit":false,"firstName":"Joel","lastName":"Parker","fullName":"Joel J Parker","fullNameInverted":"Parker, Joel J","middleInitial":"J","primaryEmail":"joel.j.k.parker@nasa.gov","publicEmail":true,"nacontact":false},{"contactId":440401,"canUserEdit":false,"firstName":"Sreeja","lastName":"Nag","fullName":"Sreeja Nag","fullNameInverted":"Nag, Sreeja","primaryEmail":"sreejanag@gmail.com","publicEmail":false,"nacontact":false},{"contactId":506527,"canUserEdit":false,"firstName":"Michael","lastName":"Johnson","fullName":"Michael A Johnson","fullNameInverted":"Johnson, Michael A","middleInitial":"A","primaryEmail":"michael.a.johnson@nasa.gov","publicEmail":true,"nacontact":false}],"website":"","libraryItems":[],"transitions":[],"responsibleMd":{"acronym":"SMD","canUserEdit":false,"city":"","external":false,"linkCount":0,"organizationId":4909,"organizationName":"Science Mission Directorate","organizationType":"NASA_Mission_Directorate","naorganization":false,"organizationTypePretty":"NASA Mission Directorate"},"program":{"acronym":"AIST","active":true,"description":"
Advanced Information Systems Technology:
Facilitating the transformation of Earth observation concepts into data, information, and knowledge to benefit society
Information technology plays a critical role in collecting, managing and analyzing very large amounts of Earth observation data and information. ESTO’s Advanced Information Systems Technology (AIST) program serves the NASA research community by providing tools and techniques to acquire, process, access, visualize and otherwise communicate Earth science data.
Individual projects address the research community’s need for tools to simulate and develop sensor measurement concepts, as well as operations concepts and software systems to acquire and manage data for research and applications. The AIST program enables computer scientists to apply best practices from the rapidly evolving information technology fields to NASA’s unique interdisciplinary science challenges, to help the Earth science community to produce groundbreaking science and fully exploit the unique vantage point of space-based Earth observations.
","parentProgram":{"acronym":"ESD","active":true,"description":"ESTO's technology development approach is end-to-end: