Multi-Task Bayesian Compressive Sensing for microwave imaging exploiting multi-frequency data

Poli, L. and Oliveri, G. and Massa, A. (2015) Multi-Task Bayesian Compressive Sensing for microwave imaging exploiting multi-frequency data. Technical Report. University of Trento.

[img]
Preview
Text
Multi-Task Bayesian Compressive Sensing for microwave imaging exploiting multi-frequency data.pdf

Download (11MB) | Preview

Abstract

This report deals with the multi-frequency Multi-Task Bayesian Compressive Sensing (BCS) technique for retrieving the dielectric features of sparse scatterers within an inaccessible investigation domain. A calibration of the MT-BCS method is firstly proposed, before to evaluate the performance of the algorithm on a wide set of scatterer configurations, showing that additional information can be educed from different illumination frequencies to improve the quality of the reconstructions. The impact of the number of frequencies exploited during the reconstruction process on the results is also investigated.

Item Type: Monograph (Technical Report)
Uncontrolled Keywords: Compressive Sensing, Inverse Scattering, Interval Analysis, Array Synthesis
Subjects: M Methodologies > M CS Compressive Sensing
URI: http://www.eledia.org/students-reports/id/eprint/667

Actions (login required)

View Item View Item