Neural network point detection using a coning scan imager

Details Neural network point detection using a coning scan imager Neural network point detection using a coning scan imager

May 1996

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=1996spie.2759..171c&link_type=abstract

Proc. SPIE Vol. 2759, p. 171-181, Signal and Data Processing of Small Targets 1996, Oliver E. Drummond; Ed.

Computer Science

Scientific paper

A very compact and inertially pointed imaging device can be constructed by combining the functions of a telescope and a gyroscope into a single assembly. However, the image resulting from this device is not easily processed owing to scan-induced geometric distortions. We have devised a method for adaptively processing the imager outputs to facilitate detection of bright points in a cluttered background. Pseudo-image neighborhoods are vectorized and have scan angle bits appended, allowing a neural net to learn the best matched filter for each scan configuration. We present the results of testing this filter using both synthetic and measured solar sea glint clutter.

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