eprintid: 515
rev_number: 4
eprint_status: archive
userid: 5
dir: disk0/00/00/05/15
datestamp: 2011-05-10
lastmod: 2013-06-30 09:01:11
status_changed: 2013-06-30 09:01:11
type: techreport
metadata_visibility: show
item_issues_count: 0
creators_name: Rocca, Paolo
creators_name: Massa, Andrea
title: An integrated stochastic multi-scaling strategy for microwave imaging applications
ispublished: unpub
subjects: TU
full_text_status: public
abstract: This work presents an improved Multi-Scale algorithm for microwave imaging of two-dimensional scatterers. The proposed methodology includes a feedback between high- and low-resolution reconstructions in order to correlate the iterative reconstruction steps. Towards this end, the appealing features of a Particle Swarm-based algorithm are fully exploited. Such an integration is aimed at better matching a suitable representation of the unknowns with the global optimization properties of the stochastic optimizer to allow faithful reconstructions.
date: 2011-01
date_type: published
institution: University of Trento
department: informaticat
refereed: FALSE
referencetext: [1] M. Bertero and P. Boccacci, Introduction to Inverse Problem in Imaging. IOP Publishing Ltd, Bristol, 1998. [2] O.M. Bucci and G. Franceschetti, “On the degrees of freedom of scattered fields,” IEEE Trans. Antennas Propagat., vol. 37, pp. 918-926, Jul. 1989. [3] O.M. Bucci and T. Isernia, “Electromagnetic inverse scattering: Retrievable information and measurement strategies,” Radio Sci., vol. 32, pp. 2123-2138, Nov.-Dec. 1997. [4] O. M. Bucci, L. Crocco, T. Isernia, and V. Pascazio, “Subsurface inverse scattering problems: Quantifying qualifying and achieving the available information,” IEEE Tran. Geosci. Remote Sensing, vol. 39, pp. 2527-2537, Nov. 2001. [5] E. L. Miller and A. Willsky, “A multiscale, statistically based inversion scheme for linearized inverse scattering problems,” IEEE Trans. Geosci. Remote Sensing, vol. 34, pp. 346-357, Mar. 1996. [6] E. L. Miller, “Statistically based methods for anomaly characterization in images observation of scattered fields,” IEEE Trans. Image Processing, vol. 8, pp. 92-101, Jan. 1999. [7] S. Caorsi, M. Donelli, D. Franceschini, and A. Massa, “A new methodology based on an iterative multiscaling for microwave imaging,” IEEE Trans. Microwave theory Tech., vol. 51, pp. 1162-1173, Apr. 2003. [8] J. Kennedy, R. C. Eberhart, and Y. Shi, Swarm Intelligence. San Francisco: Morgan Kaufmann Publishers, 2001. [9] S. Caorsi, M. Donelli, and A. Massa, “Detection, location, and imaging of multiple scatterers by means of the iterative multiscaling method,” IEEE Trans. Microwave Theory Tech., vol. 52, pp. 1217-1228, Apr. 2004. [10] J R. Robinson and Y. Rahmat-Sami, “Particle Swarm optimization in electromagnetics,” IEEE Trans. Antennas Propagat., vol. 52, pp. 771-778, Mar. 2004. [11] K. Belkebir and M. Saillard, “Testing Inversion algorithms against experimental data,” Inverse problems, vol. 17, pp. 1565-1702, Dec. 2001.
citation:   Rocca, Paolo and Massa, Andrea  (2011) An integrated stochastic multi-scaling strategy for microwave imaging applications.  [Technical Report]    (Unpublished)  
document_url: http://www.eledia.org/students-reports/515/1/DISI-11-275.C90.pdf