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Geometric and Seabed parameter estimation using a Vector Sensor Array - Experimental results from Makai experiment 2005

P. Santos,
ISR, University of Algarve, Campus de Gambelas, 8005-139 Faro, Portugal
J. João,
ISE, University of Algarve, 8005-139 Faro, Portugal
O.C. Rodríguez,
P. Felisberto,
S.M. Jesus,
ISR, University of Algarve, Campus de Gambelas, 8005-139 Faro, Portugal

Comments: download pdf file.
Ref.: Oceans'11, Santander, Spain, June 2011.

A vector sensor is constituted by one omni directional pressure sensor and three velocity-meters that are sensitive in a specific direction - x, y or z direction. Since, the vector sensor is able to measure the three particle velocity components it acts as a spatial filter, therefore has advantage in three dimensional direction of arrival (DOA) estimation. The potential gain obtained in DOA estimation can be extended to other geometric parameters such as source range and depth, as well as seabed parameters. The objective of this paper is to present experimental results of a four element vertical vector sensor array (VSA) data set collected during MakaiEx’05 experiment for geometric (range and depth) and seabed parameter estimation (sediment compressional speed, density and compressional attenuation). The parameter estimation problem is posed as an inversion method based on an extension of the conventional pressure only Bartlett estimator to particle velocity. The developed VSA based Bartlett estimator is proportional to the pressure only Bartlett estimator response by a directivity factor, providing an improved side lobe reduction or even suppression when compared with the pressure only response. This behaviour will be illustrated for geometric and seabed parameters showing clearly the advantages of the use of VSA over hydrophone arrays. The VSA Bartlett estimator outperforms the localization of the source when compared with an array of hydrophones of same number of sensors. Moreover, when the VSA Bartlett estimator is applied for seabed parameter estimation, it will be shown that the estimation resolution of these parameters increased significantly, even for density and compressional attenuation, parameters with difficult estimation using an array of hydrophones.

Acknowledgement: The authors would like to thank Michael Porter, chief scientist for the Makai Experiment, Jerry Tarasek at Naval Surface Weapons Center for the vector sensor array used in this work. The authors also thank Bruce Abraham at Applied Physical Sciences for providing assistance with the data acquisition and the team at HLS Research, particularly Paul Hursky for their help with the data used in this analysis. This work was supported by the project SENSOCEAN funded by FCT program PTDC/EEA-ELC/104561/2008.

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