Modern spacecraft instruments generate far more data than can be downlinked for analysis on the ground. Thus, in order to increase science return for any mission, automated onboard analysis and data selection must take place to return the most relevant data. For the NASA-ESA Europa Jupiter System Mission (EJSM) and particularly the Jupiter Europa Orbiter (JEO), autonomous science enhancement is crucial to finding evidence of current or recent geophysical activity on Europa. Algorithms for onboard detection of events and surface features that indicate activity, such as thermal anomalies and active plumes, can be matured from existing software for application to Europa. Those algorithms can be tested using currently available data sets and the test results can be analyzed in order to form recommendations for mission concepts. The objectives of this research are to (1) develop onboard decision-making software that will greatly enhance the Europa Flagship mission as well as other potential future planetary missions by (2) developing methods by which software can detect and identify a broad range of science events and phenomena that can be autonomously prioritized for data downlink and/or other spacecraft operations; development of this software and associated hardware and operations concepts will require (3) testing datasets with currently available platforms. This research will focus on finding methods of characterizing surface features and identifying sites of activity. Existing algorithms for autonomous science enhancement developed by Chien et al. at JPL will be adapted for use with the instruments planned for the JEO; they will be modified for characterization and classification of surface features, detection of thermal signatures, and identification of plumes. These algorithms will also include methods for change detection to enable efficient detection of science phenomena such as surface or near surface change on Europa. This will be completed by analyzing current methods of automated feature or change detection and testing similar methods on currently active platforms. Work will include enhancing existing onboard response capabilities such that the software can be applied directly to Europa mission conditions.
The power, distance, and memory capacity limitations suffered by outer planet spacecraft missions severely restrict the potential data volume returned for science analysis. In order to make effective use of limited observation time and to conserve the volume of data to be stored and transferred, thereby increasing science return, automated onboard analysis and data selection must take place to return the most relevant data. Autonomous science enhancement is crucial to finding evidence of current or recent geophysical activity on Europa; the uncertain nature of any activity necessitates an understanding of the limitations of physical characteristics that are detectable. Algorithms for onboard detection and classification of events and surface features that indicate activity, such as active volcanic plumes or outgassing, have been matured from existing software for application to Europa. This enables efficient planning of observation sequences, aids data prioritization and summarization, and allows potential onboard reactive execution. We have demonstrated the use of these algorithms on surrogate datasets where transient features are known in order to discern limiting physical characteristics (i.e., size, diffusivity, vertical extent, shape, etc.) of detectable features and computing constraints. This will allow us to make recommendations for the types of observations needed in order to discover or monitor active events at Europa and elsewhere.
|Effective start/end date||9/1/10 → 8/31/15|
- NASA: Goddard Space Flight Center: $89,355.00