Maximum Likelihood Deconvolution of Beamformed Images with Signal-Dependent Speckle Fluctuations from Gaussian Random Fields: With Application to Ocean Acoustic Waveguide Remote Sensing (OAWRS)
Wide area acoustic remote sensing often involves the use of coherent receiver arrays to determine the spatial distribution of sources and scatterers at any instant. The resulting acoustic intensity images are typically corrupted by signal-dependent noise from Gaussian random field fluctuations arisi...
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| Format: | Article |
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MDPI AG
2018
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| Online Access: | http://hdl.handle.net/1721.1/114950 https://orcid.org/0000-0003-4369-296X |
| _version_ | 1826201761026670592 |
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| author | Jain, Ankita Deepak Makris, Nicholas |
| author2 | Massachusetts Institute of Technology. Department of Mechanical Engineering |
| author_facet | Massachusetts Institute of Technology. Department of Mechanical Engineering Jain, Ankita Deepak Makris, Nicholas |
| author_sort | Jain, Ankita Deepak |
| collection | MIT |
| description | Wide area acoustic remote sensing often involves the use of coherent receiver arrays to determine the spatial distribution of sources and scatterers at any instant. The resulting acoustic intensity images are typically corrupted by signal-dependent noise from Gaussian random field fluctuations arising from the central limit theorem and have a spatial resolution that depends on the incident direction, sensing array aperture and wavelength. Here, we use the maximum likelihood method to deconvolve the intensity distribution measured on a coherent line array assuming a discrete angular distribution of incident plane waves. Instantaneous wide area population density images of fish aggregations measured with Ocean Acoustic Waveguide Remote Sensing (OAWRS) are deconvolved to illustrate the effectiveness of this approach in improving angular resolution over conventional planewave beamforming. |
| first_indexed | 2024-09-23T11:56:40Z |
| format | Article |
| id | mit-1721.1/114950 |
| institution | Massachusetts Institute of Technology |
| last_indexed | 2024-09-23T11:56:40Z |
| publishDate | 2018 |
| publisher | MDPI AG |
| record_format | dspace |
| spelling | mit-1721.1/1149502022-10-01T07:09:40Z Maximum Likelihood Deconvolution of Beamformed Images with Signal-Dependent Speckle Fluctuations from Gaussian Random Fields: With Application to Ocean Acoustic Waveguide Remote Sensing (OAWRS) Jain, Ankita Deepak Makris, Nicholas Massachusetts Institute of Technology. Department of Mechanical Engineering Jain, Ankita Deepak Makris, Nicholas Wide area acoustic remote sensing often involves the use of coherent receiver arrays to determine the spatial distribution of sources and scatterers at any instant. The resulting acoustic intensity images are typically corrupted by signal-dependent noise from Gaussian random field fluctuations arising from the central limit theorem and have a spatial resolution that depends on the incident direction, sensing array aperture and wavelength. Here, we use the maximum likelihood method to deconvolve the intensity distribution measured on a coherent line array assuming a discrete angular distribution of incident plane waves. Instantaneous wide area population density images of fish aggregations measured with Ocean Acoustic Waveguide Remote Sensing (OAWRS) are deconvolved to illustrate the effectiveness of this approach in improving angular resolution over conventional planewave beamforming. United States. Office of Naval Research National Oceanographic Partnership Program (U.S.) 2018-04-24T20:04:56Z 2018-04-24T20:04:56Z 2016-08 2016-08 2018-03-02T14:47:00Z Article http://purl.org/eprint/type/JournalArticle 2072-4292 http://hdl.handle.net/1721.1/114950 Jain, Ankita, and Nicholas Makris. “Maximum Likelihood Deconvolution of Beamformed Images with Signal-Dependent Speckle Fluctuations from Gaussian Random Fields: With Application to Ocean Acoustic Waveguide Remote Sensing (OAWRS).” Remote Sensing, vol. 8, no. 9, Aug. 2016, p. 694. © 2016 by the Authors https://orcid.org/0000-0003-4369-296X http://dx.doi.org/10.3390/RS8090694 Remote Sensing Attribution 4.0 International (CC BY 4.0) https://creativecommons.org/licenses/by/4.0/ application/pdf MDPI AG MDPI |
| spellingShingle | Jain, Ankita Deepak Makris, Nicholas Maximum Likelihood Deconvolution of Beamformed Images with Signal-Dependent Speckle Fluctuations from Gaussian Random Fields: With Application to Ocean Acoustic Waveguide Remote Sensing (OAWRS) |
| title | Maximum Likelihood Deconvolution of Beamformed Images with Signal-Dependent Speckle Fluctuations from Gaussian Random Fields: With Application to Ocean Acoustic Waveguide Remote Sensing (OAWRS) |
| title_full | Maximum Likelihood Deconvolution of Beamformed Images with Signal-Dependent Speckle Fluctuations from Gaussian Random Fields: With Application to Ocean Acoustic Waveguide Remote Sensing (OAWRS) |
| title_fullStr | Maximum Likelihood Deconvolution of Beamformed Images with Signal-Dependent Speckle Fluctuations from Gaussian Random Fields: With Application to Ocean Acoustic Waveguide Remote Sensing (OAWRS) |
| title_full_unstemmed | Maximum Likelihood Deconvolution of Beamformed Images with Signal-Dependent Speckle Fluctuations from Gaussian Random Fields: With Application to Ocean Acoustic Waveguide Remote Sensing (OAWRS) |
| title_short | Maximum Likelihood Deconvolution of Beamformed Images with Signal-Dependent Speckle Fluctuations from Gaussian Random Fields: With Application to Ocean Acoustic Waveguide Remote Sensing (OAWRS) |
| title_sort | maximum likelihood deconvolution of beamformed images with signal dependent speckle fluctuations from gaussian random fields with application to ocean acoustic waveguide remote sensing oawrs |
| url | http://hdl.handle.net/1721.1/114950 https://orcid.org/0000-0003-4369-296X |
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