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Space Technology 6: Testing Tomorrow's Technology Today!
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The onboard science algorithm module analyzes image data captured by the image formation module. These algorithms identify unchanged features and find changes that have occurred since previous observations. They then tell the processor to downlink (send the signal) to those regions where changes such as flooding, ice melt, new forest growth, or lava flows have occurred. They also tell the image formation module where to search or look again.

The algorithms command the radar aim-point (direction pointed) to shift on the next orbit so that, for example, a new lava flow or the full extent of a flood can be detected and captured. To detect change, the module software tests for statistically significant differences in region sizes, locations, boundaries, using histograms (bar-chart-like plots of amounts) of raw data.

This module also develops science products from raw data. Such onboard conversion of raw data is a form of intelligent data compression. Examples of the science products are:

  • descriptions of terrain boundaries (the outline of a flooded region or a fresh lava flow)
  • histograms of heights, slopes, or reflectivities (how much light is returned and from where), such as of volcano hypsometry (distribution of slopes on a side of a volcano: how many are steep and how many shallow)
  • vector field (the quantity of magnitude and direction) descriptions of flows of ice migration or lava and of wind
  • catalogs of the features——including type, location, and size information——of such regions as lakes and sand dunes
  • image data of regions of interest, particularly regions where change has occurred or which stand out from the local surroundings

On deep space missions, this module will enable capture of short-term science phenomena at very short intervals of time. Examples of these are volcanic eruptions on Jupiter's moon, Io, or formation of jets on comets, and phase transitions in ring systems. Additionally, the module's capability of capturing data on region changes and then converting the raw data will also reduce the total amount of data to a manageable level. This is important for long missions that study long-term phenomenom, such as atmospheric changes at Jupiter or the flexing and cracking of the ice crust on Europa. Short and long-term phenomena will be captured without overwhelming onboard caching (quick operations performed by computer memory) or downlink capacities.



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