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Global science coverage of a 5-spacecraft constellation evaluated in the SDC study. The color of each 1x1 degree bin tells how many times the science targets have been observed during the 10-day planning horizon.

Background

The National Academies of Science, Engineering and Medicine 2017 Decadal Survey of Earth Science and Applications identified geodetic measurements of surface deformation and related change as one of the top five “observables” to be prioritized in NASA's future program. In response, NASA commissioned a multi-center Surface Deformation and Change (SDC) team to perform a five year study of mission architectures that would support SDC observables and provide the most value to the diverse science and applications communities it serves. As synthetic aperture radar (SAR) was identified as the prime sensor technology to satisfy SDC observational needs, a key component of the SDC study is to assess the current state of the art in SAR sensor and supporting technology. The mechanism for assessment involves development of an end-to-end science performance evaluation tool for multi-satellite constellations, which feeds into a science value framework that considers science performance, technological programmatic risks, and cost.

Problem

The observational capabilities of many candidate constellations with various capabilities have to be simulated and evaluated over a long planning horizon before being compared to each other.

The Science team express their intent in terms of campaigns, which are sets of polygons to observe associated with observational constraints (illumination, temporal constraints…). All campaigns are assigned a priority. Designing the campaigns and assigning priorities is a tedious exercise that can affect the satisfaction of these campaigns as resources, time, power and memory also play a role in decision-making. With this in consideration, and as the resulting plans comprises hundreds of observations, explainability is a focus to improve the communication between the science team and the AI group and being able to answer questions about the plans.

Technology

CLASP serves as the core tool. Developed by the AIG and used in several flight missions, it ingests spacecraft trajectories, science campaigns with their observational constraints, and spacecraft models (including instrument modes, power model, and memory constraints), and outputs observation schedules for a given planning horizon.

A software suite has been developed to generate input constellation configurations and scenarios.

We use various newly developed output data visualization products for analysis and communication with the science team such as coverage maps and resource graphs.

New scheduling algorithms have been developed to address specific constraints or desired behaviors of some of the constellations. Some of this work builds upon the work done for the mission design of NISAR [reference]. Here are a few examples:
- Approaches to limit how spacecraft can slew (vs a default opportunistic slewing over a predefined range)
- Scheduling interferometry pairs over a region, two observations that can be made by different spacecraft but have to be made at the same slewing angle.
- Scheduling simultaneous observations from formation-flying sub-constellation (vs considering each spacecraft separately), either focused on the same point on the ground or extending each other swath to cover more ground.

Impact

The study is being conducted in phases, in which the science and applications capabilities identified in the Decadal Survey are refined, candidate architectures and associated technologies to support these needs are identified, architectures are assessed against a science value framework specific to SDC, and recommendations to NASA are made. Ultimately, NASA will decide which amongst these recommendations will proceed to mission formulation.

Status

In September 2022, about 15 architectures (ranging from 1 to 12 spacecraft) have been defined, implemented, and simulated. A subset of these have been selected and will undergo further studies.

References

[1] https://science.nasa.gov/earth-science/decadal-sdc

Publications

Team

Adrien Maillard
Christopher Wells

Sponsors

NASA Earth Science Division of the Science Mission Directorate