Paper Info
Title
Broadband localization in a dispersive medium through sparse wavenumber analysis
Abstract
Matched field processing is a powerful tool for accurately localizing targets in dispersive media. However, matched field processing requires a precise model of the medium under test. In underwater acoustics, where matched field processing has been extensively studied, authors often resort to extremely detailed numerical models of the propagation medium, which are computationally expensive and impractical for many applications. As an alternative, this paper uses convex sparse recovery techniques to construct, directly from measured data, an accurate model of a plate medium based on its dispersion characteristics. From this data-driven model, the Green's function between two points can be readily predicted. We demonstrate the effectiveness of this model by localizing a source in a dispersive plate medium. The results visually illustrate our approach to significantly improve localization accuracy and reduce artifacts when compared to a conventional narrowband technique.
Year
DOI
Venue
2013
10.1109/ICASSP.2013.6638424
Acoustics, Speech and Signal Processing
Keywords
Field
DocType
Green's function methods,acoustic signal processing,Green's function,broadband localization,convex sparse recovery techniques,data-driven model,dispersion characteristics,dispersive media,dispersive medium,dispersive plate medium,matched field processing,propagation medium,source localization,sparse wavenumber analysis,target localization,underwater acoustics,Sparse recovery,inverse problems,localization,matched field processing,time reversal
Dispersion (optics),Narrowband,Pattern recognition,Numerical models,Dispersive medium,Computer science,Wavenumber,Underwater acoustics,Broadband,Regular polygon,Artificial intelligence,Acoustics
Conference
ISSN
Citations 
PageRank 
1520-6149
2
0.48
References 
Authors
2
2
Name
Order
Citations
PageRank
Joel B. Harley1123.11
José M. F. Moura25137426.14