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Proceedings Paper

Adaptive system for detecting stationary targets with real-aperture radar
Author(s): Hiralal C. Khatri; Francois Koenig; Roberto Innocenti; Kenneth I. Ranney
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Paper Abstract

Trained algorithms are required for detecting stationary targets with practical real-beam radars. The parameters of these algorithms are unique to each site or clutter class. A problem arises when an algorithm trained on one clutter class is applied, perhaps inadvertently, to another class. In this case, the performance of the system can degrade to an unacceptable level. We have developed a system that adapts, online, the parameters of the algorithm to the encountered clutter type. This system consists of two neural networks - one for adapting the coefficients of the algorithm and the other for adapting the threshold level.

Paper Details

Date Published: 20 August 2003
PDF: 15 pages
Proc. SPIE 5077, Passive Millimeter-Wave Imaging Technology VI and Radar Sensor Technology VII, (20 August 2003); doi: 10.1117/12.488641
Show Author Affiliations
Hiralal C. Khatri, U.S. Army Research Lab. (United States)
Francois Koenig, U.S. Army Research Lab. (United States)
Roberto Innocenti, U.S. Army Research Lab. (United States)
Kenneth I. Ranney, U.S. Army Research Lab. (United States)


Published in SPIE Proceedings Vol. 5077:
Passive Millimeter-Wave Imaging Technology VI and Radar Sensor Technology VII
Roger Appleby; Robert Trebits; David A. Wikner; James L. Kurtz, Editor(s)

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