TY  - RPRT
PB  - University of Trento
N2  - 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.
Y1  - 2015///
M1  - technical_report
UR  - http://www.eledia.org/students-reports/667/
AV  - public
A1  - Poli, L.
A1  - Oliveri, G.
A1  - Massa, A.
TI  - Multi-Task Bayesian Compressive Sensing for microwave imaging exploiting multi-frequency data
ID  - elediasc12667
KW  - Compressive Sensing
KW  -  Inverse Scattering
KW  -  Interval Analysis
KW  -  Array Synthesis
ER  -