Progressive compressive sensing for exploiting frequency-diversity in GPR imaging

Full-Vectorial 3D Microwave Imaging of Sparse Scatterers through a Multi-Task Bayesian Compressive Sensing Approach

“…[MHz]) [6]. As for the setting of the MF-MT-BCS control parameters ( 8), the optimal trade-off values     ).…”

“…For instance, the wide-band nature of GPR measurements above the interface [1] provides an intrinsic frequency diversity in the collectable data. Such an information on the scenario under test can be profitably exploited with both frequency-hopping (FH) [6][7] and multifrequency (MF) [8][9] MI techniques by processing each spectral component in a cascaded fashion or jointly, respectively. Another effective recipe against the IP is the use of the a-priori information on the class of imaged targets.…”

“…Another effective recipe against the IP is the use of the a-priori information on the class of imaged targets. As a matter of fact, Compressive Sensing (CS)-based techniques [6][11]- [14] faithfully retrieved sparse objects (i.e., objects representable with few non-null expansion coefficients with respect to a suitably-chosen representation basis). In such a framework, Bayesian CS (BCS) solvers have emerged as effective, computationally-fast, and also feasible tools since they do not require the compliancy of the scattering operator with the restricted isometry property (RIP), whose check is often computationally unaffordable [11].…”

“…) frequency in a cascaded fashion, from the lowest to the highest one, by either enforcing the correlation between multiple views ( V L  -FH-MT-BCS method [6]) or considering each view as a single task ( 1  L -FH-ST-BCS method [6]). As it can be observed, the MF-MT-BCS outperforms both FH strategies, the worst inversion being performed by the FH-ST-BCS [Figs.…”

Accurate and robust inversion of buried objects based on the linear sampling method and differential evolution

“…It is shown in [5] and [6] that aspect‐limited measurements provide insufficient spectral information, resulting in a low reconstruction quality and resolution (bounded by Rayleigh‐limit). To compensate the weak availability to objects information in the space domain, a scheme of exploiting frequency diversity [7–9] is proposed to enhance the information in the spectral domain either by a stepwise way [10, 11] or processing the whole multi‐frequency data simultaneously [7]. In stepwise (or hopping‐frequency) method, the results obtained at a lower frequency serve as an initial for the following inversion at a higher frequency, presenting multi‐focusing behaviour, which is apparently computationally expensive since a series of optimisation problems need to be solved.…”