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Smart Satellite Sets Its Own Priorities
Roland Piquepaille writes "Currently, satellites take pictures of whatever is in front of their cameras. But hydrologists from the University of Arizona (UA), working with the Jet Propulsion Laboratory (JPL) are creating spacecraft that think for themselves. Their smart software, which is tested on NASA's EO-1 satellite, can be used on all kinds of spacecraft. This software has three components: an image formation module, a science algorithm module, and a continuous planning module. This onboard planner reschedules what to film in conjunction with what the scientific algorithms have detected. This software has already detected floods in Australia and will be adapted to also detect volcano eruptions and changes in ice fields. More details and references are available in this overview, including images of the flood detected by this smart software."
This article reminds of the optical systems of mantis shrimp as a supreme example of controlled visual integration of optical information.
With up to 10 color bands and 2 to 4 polarizations in a multi-band linear array across each eye, the little beastie is the champion for color vision . Because the eye bands of the left and right eyes are at an angle to each other, the shrimp can sweep the two linear arrays across an area to create binocular polychromatic vision (more remarkable is that each eye has a central trinocular field of vision so each eye has independent depth perception). The entire system is controlled by X-Y scanning of the two eyes (either independently or in sync) to sweep across an area to to create a 2-D high resolution multi-spectral image from 1-D linear arrays.
The point, for satellite sensors, is that more dynamic control of a multi-spectral sensor Earth-observing system can adaptively gather data at multiple resolutions -- gathering super-resolution scans on interesting regions such as a flash floods, forest fires - while retaining a low resolution full-image situation awareness. This intelligence needs to be local because, in the mantis shrimp at least, the control loop operates on millisecond timescales. Satellite-local processing would also reduce the downlink bandwidth requirements as the raw sensor output could easily exceed 10 gigabits/sec.
Two wrongs don't make a right, but three lefts do.
You do not want the satellite to send all the data it collects. I went to a seminar on on-board realtime data mining last year and the lecturer said they can download about 11% of the data. So the big problem is to filter out all the extra and send the useful information.
Example: You don't want to download thousands of nearly identical pictures of the South Pole from 5 different instruments when all you want to know is how big the ozone hole is. Solution is to use data mining filters to detect the edges of the ozone hole and send back this information.
It all comes down to a lack of bandwidth and using as much intelligent processing on-satellite as possible to extract information rather than just collecting data.
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