Neural network point detection using a coning scan imager

Emily D. Claussen; Kim T. Constantikes

doi:10.1117/12.241180

31 May 1996 Neural network point detection using a coning scan imager

Emily D. Claussen, Kim T. Constantikes

Proceedings Volume 2759, Signal and Data Processing of Small Targets 1996; (1996) https://doi.org/10.1117/12.241180
Event: Aerospace/Defense Sensing and Controls, 1996, Orlando, FL, United States

Abstract

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.

Citation Download Citation

Emily D. Claussen and Kim T. Constantikes "Neural network point detection using a coning scan imager", Proc. SPIE 2759, Signal and Data Processing of Small Targets 1996, (31 May 1996); https://doi.org/10.1117/12.241180

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