Abstract
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.
Highlights
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
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
Summary
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. It is known that targets have localized spatial supports, whereas sources of clutter do not This occurs, for example, when targets are embedded in layered host media, as in subsurface or through-wall imaging. In these cases, clutter contribution mainly arises from medium interfaces whose spatial Fourier spectrum is concentrated around low frequencies. By introducing an entropy-based measure of this similarity, signals at instants of time where entropy exceeds a prescribed threshold are nulled [9] Note that this allows for clutter reduction when it does not appear before the target scattered field.
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