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Proceedings Paper

Nonlinear adaptive recursive least squares (NRLS) algorithm for target detection in infrared imagery
Author(s): Mohammad Abu-Tahnat; Michael W. Thompson
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Paper Abstract

In this paper we consider the detection of small targets within an IR scene that are embedded in a dominant clutter background. A feasible approach toward addressing this issue is to invoke some form of signal processing that allows the clutter to be reduced from the scene prior to target detection. An NRLS scheme is employed which functions as whitening filter prior to matched filtering. The NRLS scheme is based on a second order truncated Volterra series expansion. The goal is to adapt to image nonstationarities and to equalize unknown system nonlinearities, prior to matched filtering. Simulation results based on both synthesized and `real world' nonstationary IR images are presented.

Paper Details

Date Published: 31 May 1996
PDF: 11 pages
Proc. SPIE 2765, Detection and Remediation Technologies for Mines and Minelike Targets, (31 May 1996); doi: 10.1117/12.241257
Show Author Affiliations
Mohammad Abu-Tahnat, Colorado State Univ. (United States)
Michael W. Thompson, Univ. of Texas Pan American (United States)


Published in SPIE Proceedings Vol. 2765:
Detection and Remediation Technologies for Mines and Minelike Targets
Abinash C. Dubey; Robert L. Barnard; Colin J. Lowe; John E. McFee, Editor(s)

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