Entropy-Based Clutter Rejection for Intrawall Diagnostics

The intrawall diagnostic problem of detecting localized inhomogeneities possibly present within the wall is addressed. As well known, clutter arising from masonry structure can impair detection of embedded scatterers due to high amplitude reflections that wall front face introduces. Moreover, internal multiple reflections also can make it difficult ground penetrating radar images (radargramms) interpretation. To counteract these drawbacks, a clutter rejection method, properly tailored on the wall features, is mandatory. To this end, here we employ a windowing strategy based on entropy measures of temporal traces “similarity.” Accordingly, instants of time for which radargramms exhibit entropy values greater than a prescribed threshold are “silenced.” Numerical results are presented in order to show the effectiveness of the entropy-based clutter rejection algorithm. Moreover, a comparison with the standard average trace subtraction is also included. 1. Introduction Microwave RADAR imaging is a pervasive research field which finds applications in a number of scenarios where it is mandatory and/or convenient to achieve diagnostics in a nondestructive way. Applicative contexts range from subsurface prospecting to cultural heritage monitoring and preservation [1], from biomedical diagnostics [2] to through-the-wall imaging (TWI) [3], and many others. Each one of these scenarios characterizes imaging in terms of the challenges to be tackled in order to succeed in target detection and localization. This of course depends on the scatterers’ nature and the host medium within which they are embedded. Indeed, the host medium is the background against which targets have to be discerned. First, the host medium imposes a suitable trade-off between resolution and electromagnetic wave penetration in order to comply with losses and dispersive effects it introduces. Moreover, host medium also determines that clutter signal against field backscattered from targets must compete. Literature is extremely reaches imaging algorithms arisen from different scientific areas. Now, it is recognized that wave equation is their common mathematical rationale. Accordingly, they all attempt to solve an electromagnetic inverse scattering problem by approximating, in different way, the inverse of the relevant scattering operator. The interested reader can refer to [4], where many of these imaging algorithms are compared under the light of inverse scattering theory. In any case, imaging greatly benefits from a preliminary stage where useful signals (i.e., the ones coming from targets) are