A Technical Seminar presented by the
Washington/Northern Virginia Chapter
of the
IEEE Geoscience and Remote Sensing Society
Novel Self-Adpative Application Strategies
using Smart
Satellites
Dr. Richard B. Gomez
School of Computational Sciences
Abstract:
This talk
presents self-adaptive application strategies to operationally process
and
exploit spectral information on-board smart remote sensing satellites
in real
time. The goal is to greatly increase onboard processing
capabilities and
reduce data volumes for hyperspectral systems by incorporating this
intelligent-based approach. The approach focuses on the future
development of hardware and software methods using an architecture
based on
Reconfigurable Computers that work more like the human brain and body.
These smart satellites will be self-sensing, self-repairing, and
self-adaptive. If something is not exactly right, the smart
satellite will
not need a signal from ground control. The spacecraft itself
decides
what's best and then take the necessary action to address the
problem.
It’s a revolutionary means to process and exploit on board, huge
amounts of
hyperspectral data without the need to have an expert spectral analyst
in the
loop. Special attention will be paid to spectral libraries and
novel
usage of exemplar spectra. This involves techniques that are
beyond the
forefront of current database research. NASA has recognized the
value of
using a hyperspectral sensor flying with or slightly behind of the
imaging
sensor platform to identify features of interest to be processed.
The
hyperspectral sensor is used to identify the presence of a feature and
verify
its composition. The employment of a near real time feature
recognition
system on the hyperspectral sensing satellite is invaluable. We
envision
that a reconfigurable architecture incorporating evolutionary
algorithms will
be developed knowing that self-adaptive satellites may be the key to
success.