A Compressive Sensing Approach to Moving Target Indication for Urban Sensing.

In this paper, we apply compressive sensing to moving target indication for urban sensing and through-thewall imaging applications using stepped-frequency radar. In particular, we consider sparsity-driven imaging combined with change detection. Stationary targets and clutter are removed via change detection, resulting in a sparse scene of few slowmoving targets inside enclosed structures and behind walls. Using compressive sensing, a sizable reduction in the number of samples is achieved without degradation in system performance. Laboratory experiments are conducted to validate the proposed approach.

Main Author: Amin, Moeness.
Other Authors: Ahmad, Fauzia., Zhang, Wenji.
Format: Villanova Faculty Authorship
Language: English
Published: 2011
Online Access: http://ezproxy.villanova.edu/login?url=https://digital.library.villanova.edu/Item/vudl:173030