Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Vector sensor array processing and geoacoustic inversion with MAKAI'05 sea trial data
SiPLAB, University of Algarve, Campus de Gambelas.
2013 (English)Report (Other academic)
Abstract [en]

Underwater acoustic vector sensor has received much more attentions in recent a few decades. One type of high precise high-frequency vector sensor TV-001, succeeded for several applications in Makai Ex05 sea trial, such as direction-of-arrival (DOA) estimation, geoacoustic inversion, tomography, MIMO communications. In this report, the vector sensor array (VSA) direction finding performance, including the array directivity index (DI), array gain (AG), and Cramér-Rao bound (CRB) are studied. Besides, the main research was focused on the geoacoustic inversion by using various propagation models. One simple inversion method by comparing the downward and upward beams was studied, i.e. bottom reflection coefficient (BRC) matching method, the results showed that the (p+v) processor is the best. The seabed parameter sensitivities were studied, and the compressional velocity was found could be inverted by matched-field inversion (MFI) methods. The CRB's of geoacoustic parameter estimates are derived, which also demonstrated that the (p+v) processing outperforms others. A two-step inversion method was proposed. First, the compressional velocity, along with the receiver range and depth were optimized using genetic algorithm (GA). Secondly, the optimized range and depth information was fed back to improve the accuracy of the replica fields, then the compressional velocity dependent replicas were matched with the real data, giving high resolution and precise results during the period of nearly two hours

Place, publisher, year, edition, pages
Algarve: SiPLAB, University of Algarve, Campus de Gambelas , 2013.
National Category
Signal Processing
Research subject
Signal Processing
Identifiers
URN: urn:nbn:se:ltu:diva-23056Local ID: 56eccfbd-afaf-4b0c-89ce-21289a8d9233OAI: oai:DiVA.org:ltu-23056DiVA, id: diva2:996105
Note
Upprättat; 2013; 20150704 (biajia)Available from: 2016-09-29 Created: 2016-09-29 Last updated: 2025-10-21Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

http://www.siplab.fct.ualg.pt/pubs/rep_0313.html

Authority records

Jiang, Biao

Search in DiVA

By author/editor
Jiang, Biao
Signal Processing

Search outside of DiVA

GoogleGoogle Scholar

urn-nbn

Altmetric score

urn-nbn
Total: 495 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf