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International Journal of Antennas and PropagationVolume 2012 2012, Article ID 251497, 11 pages

Research Article

Center for Advanced Communications, Villanova University, Villanova, PA 19085, USA

Department of Electrical Engineering, Duke University, Durham, NC, USA

The Ohio State University, Columbus, OH 43210, USA

Received 6 December 2011; Accepted 13 February 2012

Academic Editor: Francesco Soldovieri

Copyright © 2012 Wenji Zhang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Compressive Sensing CS provides a new perspective for addressing radar applications requiring large amount of measurements and long data acquisition time; both issues are inherent in through-the-wall radar imaging TWRI. Most CS techniques applied to TWRI consider stepped-frequency radar platforms. In this paper, the impulse radar two-dimensional 2D TWRI problem is cast within the framework of CS and solved by the sparse constraint optimization performed on time-domain samples. Instead of the direct sampling of the time domain signal at the Nyquist rate, the Random Modulation Preintegration architecture is employed for the CS projection measurement, which significantly reduces the amount of measurement data for TWRI. Numerical results for point-like and spatially extended targets show that high-quality reliable TWRI based on the CS imaging approach can be achieved with a number of data points with an order of magnitude less than that required by conventional beamforming using the entire data volume.

Autor: Wenji Zhang, Moeness G. Amin, Fauzia Ahmad, Ahmad Hoorfar, and Graeme E. Smith

Fuente: https://www.hindawi.com/


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