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-the-wall 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 slow-moving 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.