Page:Advanced Automation for Space Missions.djvu/22



DATA ON DEMAND USER I LOGON I SYSTEM/USER INTERFACE - NATURAL LANGUAGE QUERY-RESPONSE ON GROUND PROCESSING - KNOWS ALL SATELLITES - KNOWS ALL USER REQUESTS - KNOWS ALL PRIORITIES - BUILDS PLAN FOR IMPLEMENTATION - GENERATES COST ESTIMATE PRIOR TO EXECUTION OF PLAN UPLINK I SATELLITE SENSING & PROCESSING - RAW DATA COLLECTION - MAKES DECISION ON DATA COLLECTION - ON BOARD PROCESSING - DOWNLINK - IMAGE DOWNLINK ON GROUND PROCESSING - PICTURE PROCESSING - UPDATE WORLD MODEL - ARCHIVE - DELIVER RESPONSE TO USER USER

Figure 2.5. - Typical data processing steps in any user/IESIS interaction.

their signatures. Observations of these anomalies may produce a sample count of the observation type, trigger an alarm, or generate a report of the incident automatically sent to persons who should be apprised of the situation. The second class of anomaly consists of unexpected, wholly novel events. Upon observation of such an anomaly (e.g., the eruption of Mount Saint Helens' volcano), all sensor data are returned to Earth for analysis, identification, and possibly, action. The expected anomaly file is updated to include the identity of the phenomenon together with directions on actions to take upon re-observation, if any.

Processed sensor readings for features encountered during an observation are archived. Archival data collected on the basis of features and their properties then may be used to improve world model accuracy or to build detailed models of particular features (e.g., Lake Erie) or types of features (e.g., fresh water lakes). Individually observed data points lose informational value over time and can be reduced to models such as a Fourier time series to retain more valuable long-term trends once sufficiently detailed surveys accumulate. While the importance of this aspect of data reduction will grow over time, the majority of data reduction is associated with the world model in the process of eliminating the storage of redundant data. The world model will enable individual features as well as groups of features to be studied and summarized easily.

2.2.2 Foreground Mode

The IESIS foreground mode allows individual users to make natural language requests for particular data to be collected and processed for their own purposes. The fulfillment of this request becomes a goal of the system. IESIS determines the appropriate sensor algorithms and requested data are acquired the next time the requisite sensors are within view of the feature or area to be observed. The system must ascertain that conditions specified by the requester are satisfied during observation (e.g., absence of cloud cover, proper sun angle). If they are not, IESIS informs the user and reschedules the run. Nonstandard data processing may be performed on sensor data with output in any user-specified format including terminal printout, photograph/hard copy, and so forth. IESIS must have default processing/output modes as well as a choice of several optimal preprogrammed methodologies. An unsupported user-written software library similar to that maintained by IBM also could be provided.