
Proceedings Paper
An adaptive background estimation technique for enhancing target detection in through-the-wall-radar imaging applicationsFormat | Member Price | Non-Member Price |
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Paper Abstract
The challenge in detecting behind the wall stationary targets appears when the target is close to the wall and has a
frequency response that is fully or partially overlapping with the wall's spectrum. In order to detect such targets,
background subtraction is usually applied. The main challenge of using this method is the availability of the empty
scene, which is typically unavailable to the user. In this paper, we introduce an adaptive background estimation and
subtraction technique, to detect objects behind the wall with the focus on human detection. This technique is based on
the architecture of the adaptive side-lobe canceller, where a number of antenna elements are used to form a subarray that
captures the background in the main beam, while receiving the incident scatterings from the target in the sidelobes. The
output of this subarray is then used as the reference signal to suppress the background components at the output of each
sensor, through adaptive Recursive Least Squares (RLS) algorithm. This technique can be used with both co- and cross-polarization
returns, in order to further reduce the effect of the background and enhance the detectability of the target.
Paper Details
Date Published: 5 May 2009
PDF: 10 pages
Proc. SPIE 7305, Sensors, and Command, Control, Communications, and Intelligence (C3I) Technologies for Homeland Security and Homeland Defense VIII, 730516 (5 May 2009); doi: 10.1117/12.818360
Published in SPIE Proceedings Vol. 7305:
Sensors, and Command, Control, Communications, and Intelligence (C3I) Technologies for Homeland Security and Homeland Defense VIII
Edward M. Carapezza, Editor(s)
PDF: 10 pages
Proc. SPIE 7305, Sensors, and Command, Control, Communications, and Intelligence (C3I) Technologies for Homeland Security and Homeland Defense VIII, 730516 (5 May 2009); doi: 10.1117/12.818360
Show Author Affiliations
Moeness Amin, Villanova Univ. (United States)
Habib Estephan, Villanova Univ. (United States)
Published in SPIE Proceedings Vol. 7305:
Sensors, and Command, Control, Communications, and Intelligence (C3I) Technologies for Homeland Security and Homeland Defense VIII
Edward M. Carapezza, Editor(s)
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