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Proceedings Paper

Unsupervised ICA neural networks applied to reticle optical trackers
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Paper Abstract

Reticle systems are considered to be the classical approach for estimating the position of a target in a considered field of view an are widely used in IR seekers. Due to the simplicity and low cost, since only a few detectors are used, reticle seekers are still in use and are subject of further research. However, the major disadvantage of reticle trackers has been proven to be sensitivity on the IR countermeasures such as flares and jammers. When redesigned adequately they produce output signals that are linear convolutive combinations of the reticle transmission functions that are considered as the source signals in the context of the Independent Component Analysis (ICA) theory. Each function corresponds with single optical source position. That enables ICA neural network to be applied on the optical tracker output signals giving on its outputs recovered reticle transmission functions. Position of each optical source is obtained by applying appropriate demodulation method on the recovered source signals. The three conditions necessary for the ICA theory to work are shown to be fulfilled in principle for any kind of the reticle geometry.

Paper Details

Date Published: 5 April 2000
PDF: 15 pages
Proc. SPIE 4056, Wavelet Applications VII, (5 April 2000); doi: 10.1117/12.381677
Show Author Affiliations
Ivica Kopriva, Institute for Defense Studies (United States)
Harold H. Szu, Office of Naval Research (United States)


Published in SPIE Proceedings Vol. 4056:
Wavelet Applications VII
Harold H. Szu; Martin Vetterli; William J. Campbell; James R. Buss, Editor(s)

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