In-Wall Clutter Suppression Based on Low-Rank and Sparse Representation for Through-the-Wall Radar


For through-the-wall-radar signal processing, there exist intensive studies on removing the wall surface reflection signal, while the way to eliminate/alleviate the in-wall structure reflection is not well addressed. In several building structures, a layer of bolstered steel bars and utility pipes exist within the wall that will cause sturdy clutter to overwhelmingly mask the reflection signal from the targets under take a look at behind the wall. Such muddle can't be mitigated using the standard wall litter removal ways. Thus, a new effective technique to remove the robust inside-wall rebar or pipe reflection is indispensable. Considering the correlated options of the in-wall rebar or pipes and also the spatial sparsity of the behind-wall targets below check, a low-rank and sparse representation model-based in-wall muddle suppression algorithm is developed in this letter for target feature enhancement and detection. Experiments on each simulation information and field check information are performed for performance analysis and validation.

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