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Proceedings Paper

Adaptive whitening filters for small target detection
Author(s): Tarun Soni; James R. Zeidler; Walter H. Ku
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Paper Abstract

This paper studies the performance of the two dimensional least mean square adaptive filter as a prewhitening filter for detection systems. In two dimensional infrared sensor data, the clutter is correlated and much wider in spatial extent than the signal of interest. The two dimensional adaptive filter can be trained to adapt and predict the clutter, thereby enabling the error channel output to contain the signal of interest in white noise. Performance of the adaptive prewhitener, in terms of local signal to clutter ratio's(LSCR) and the gain obtained is described. The gain in LSCR due to this augmenting filter, is shown to depend on the statistics of the background clutter, in particular on the local mean. It is shown that, as the amount of color in the background clutter increases, the performance of the conventional matched filter performance degrades much more than the performance of a detector based on the augmenting prewhitener.

Paper Details

Date Published: 25 August 1992
PDF: 11 pages
Proc. SPIE 1698, Signal and Data Processing of Small Targets 1992, (25 August 1992); doi: 10.1117/12.139383
Show Author Affiliations
Tarun Soni, Univ. of California/San Diego (United States)
James R. Zeidler, Univ. of California/San Diego (United States)
Naval Command, Control and Ocean Surveillance Ctr. (United States)
Walter H. Ku, Univ. of California/San Diego (United States)

Published in SPIE Proceedings Vol. 1698:
Signal and Data Processing of Small Targets 1992
Oliver E. Drummond, Editor(s)

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