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Proceedings Paper

High resolution through-the-wall radar image based on beamspace eigenstructure subspace methods
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Paper Abstract

Through-the-wall imaging (TWI) is a challenging problem, even if the wall parameters and characteristics are known to the system operator. Proper target classification and correct imaging interpretation require the application of high resolution techniques using limited array size. In inverse synthetic aperture radar (ISAR), signal subspace methods such as Multiple Signal Classification (MUSIC) are used to obtain high resolution imaging. In this paper, we adopt signal subspace methods and apply them to the 2-D spectrum obtained from the delay-andsum beamforming image. This is in contrast to ISAR, where raw data, in frequency and angle, is directly used to form the estimate of the covariance matrix and array response vector. Using beams rather than raw data has two main advantages, namely, it improves the signal-to-noise ratio (SNR) and can correctly image typical indoor extended targets, such as tables and cabinets, as well as point targets. The paper presents both simulated and experimental results using synthesized and real data. It compares the performance of beam-space MUSIC and Capon beamformer. The experimental data is collected at the test facility in the Radar Imaging Laboratory, Villanova University.

Paper Details

Date Published: 15 April 2008
PDF: 11 pages
Proc. SPIE 6947, Radar Sensor Technology XII, 69470C (15 April 2008); doi: 10.1117/12.777171
Show Author Affiliations
Yeo-Sun Yoon, Villanova Univ. (United States)
Moeness G. Amin, Villanova Univ. (United States)

Published in SPIE Proceedings Vol. 6947:
Radar Sensor Technology XII
Kenneth I. Ranney; Armin W. Doerry, Editor(s)

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