We introduce what is believed to be a novel concept by which several sensors with automatic target
recognition (ATR) capability collaborate to recognize objects. Such an approach would
be suitable for netted systems in which the sensors and platforms can coordinate to optimize
end-to-end performance. We use correlation filtering techniques to facilitate the
development of the concept, although other ATR algorithms may be easily substituted.
Essentially, a self-configuring geometry of netted platforms is proposed that positions the
sensors optimally with respect to each other, and takes into account the interactions
among the sensor, the recognition algorithms, and the classes of the objects to be
recognized. We show how such a paradigm optimizes overall performance, and illustrate
the collaborative ATR scheme for recognizing targets in synthetic aperture radar imagery by using viewing
position as a sensor parameter.
© 2006 Optical Society of America
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