Described is a method and apparatus for obtaining accurate, timely information
for event detection and prediction based on autonomous opportunism. The objective
is to make the best possible use of all available resources at the time of acquisition,
including historical data, multiple sensors, and multiresolution acquisition capabilities,
under a given set of processing and communication bandwidth constraints. This method
(and the corresponding apparatus) fuses multiple adaptively acquired data sources
to prepare information for use by decision support models. The onboard data acquisition
schedule is constructed to maximize the prediction accuracy of the decision models,
which are designed to operate progressively, utilizing data representations consisting
of multiple abstraction levels and multiple resolutions. Due to the progressive
nature of these models, they can be executed onboard even with the use of substantially
summarized (or compressed) datasets delivered from the ground or from other satellite
platforms. Models are formulated to accept data with less than complete certainty,
thus allowing real-time decisions to be made on locations where additional data
is to be acquired based on predicted likelihood of the event of interest and uncertainties.
Multi-abstraction-level multi-resolution data is expressed using standard-compliant
representations, and progressively transmitted to the ground or other platforms.
More detailed calculations can then be performed on the ground using all of the
available real time and historical data.
