Sparsity-Based Multipath Exploitation for Through-the-Wall Radar Imaging

In this PhD thesis sparsity-based multipath exploitation methods are developed for through-the-wall radar imaging. This imaging modality uses the radar principle to reveal targets in a scene obscured by, for example, a building wall. The scattered electromagnetic wave returning from a target may reach the receiver via different propagation paths which is called multipath. This creates ambiguities in the measurements provoking unwanted ghost targets in the image. For image reconstruction, the aforementioned issue can be resolved by utilizing the sparsity of the scene. Hence, compressive sensing is employed to recover the positions of valid targets while suppressing ghosts. As an additional benefit, fewer measurements are required for image reconstruction. An additive multipath signal model is developed that includes returns from the targets of interest and the building structure. Incorporating the model in the image reconstruction methods allows exploitation of additional energy contained in secondary reflections. Multipath exploitation of stationary and moving targets employs compressive sensing. Therein, both sparsity and the structure originating from multipath propagation are utilized in the reconstruction problem. Moreover, the Doppler information contained in indirect propagation paths is investigated. A computationally efficient two-step approach is proposed that localizes the targets first. As a second step, the velocity vector is estimated from multipath Doppler. The scenario is extended to multiple compact radar modules, distributed around the scene. The reconstruction performance for closely-spaced and widely-separated placement is analyzed. This work also deals with adverse effects on the imaging results caused by signal interaction with the building structure. Returns from the front wall, so-called wall clutter, are normally suppressed using a pre-processing step. A joint wall signal and target image reconstruction approach is proposed that renders prior wall clutter mitigation unnecessary. Furthermore, the case of imperfect prior knowledge of the building layout is discussed. It is shown that errors in the position of interior walls lead to complete failure of multipath exploitation. The proposed joint wall position estimation and image reconstruction procedure can deal with uncertainties in the building layout. All proposed methods are evaluated using simulated as well as measured data from semi-controlled laboratory experiments