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

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

It is my pleasure to introduce Dr. Michael Leigsnering’s thesis work, accepted for publication with Springer, and which received in 2016 the best thesis award, sponsored by the Vereingung von Freuden der Technischen Universität zu Darmstadt e.V.. Dr. Leigsnering joined my Signal Processing Group (SPG) as a Research Associate in September 2010 after completing his Electrical Engineering and Information Technology degree at Technische Universität Darmstadt. During his tenure as Research Associate, Dr. Leigsnering visited Prof. Moeness G. Amin’s Center for Advanced Communications at Villanova University, Villanova, PA, in 2012, 2013, and 2014.

Through-the-wall imaging employs radar to reveal targets in a scene obscured by, for example, a building wall. The scattered electromagnetic wave reflected by a target may reach the receiver via different propagation paths, a phenomenon called multipath. This creates ambiguities in the measurements, resulting in unwanted ghost targets in the constructed image. Michael Leigsnering’s Ph.D. thesis deals with the mitigation and exploitation of multipath using sparse reconstruction techniques. In his thesis, he develops a comprehensive multipath signal model that includes building walls, stationary and moving targets. This allows efficient treatment of various image reconstruction scenarios, such as the reconstruction of location and velocity of targets or the consideration of multiple distributed radar units.

The proposed methods combine the benefits of multipath exploitation and compressive sensing. In this way, a ghost-free scene can be reconstructed from relatively few measurements, in fact much fewer as compared to conventional imaging techniques. Furthermore, the developed algorithms can deal with various real-life issues, such as front wall reverberations (multiple reflections within the front wall) and uncertainties in the wall locations. He evaluates the methods using simulated as well as measured data from semi-controlled laboratory experiments conducted in the Radar Imaging Lab at Villanova University.

Dr. Leigsnerings’s thesis comprises important original scientific contributions that advanced the field of through-the-wall radar imaging using sparse reconstruction techniques, which he published as first author in first-tier journals and prestigious international conferences. With the exploitation of multipath, he overcomes the problems of traditional image reconstruction methods and mitigates ghost targets within the scene. His proposed methods allow for an efficient reconstruction of stationary and moving scenes. Dr. Leigsnering’s concepts pave the way for the development of robust, inexpensive, and compact systems for through-the-wall radar imaging. This has the potential to be used in future portable and mobile devices by police, firefighters, and disaster relief teams. A compact through-the-wall imaging system can be applied in any circumstance where, e.g., an overview of a situation inside a building which is impossible or too dangerous to access is desired. This is the case in, for example, hostage crises, building fires, damaged buildings after natural disasters or detection of hidden weapon stashes; a fire brigade may use a through-the-wall radar imaging system to gain an overview of a situation, including the presence of survivors in a place that caught fire, without accessing it. Hence, the safety of firefighters need not be unnecessarily compromised.

Prof. Dr.-Ing. Abdelhak M. Zoubir


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