Comparing the resolution of Bartlett and MVDR processors for bottom parameter estimation using pressure and vector sensor short array data
2013
Felisberto, P. | Schneiderwind, J. | Santos, P. | Rodríguez, O. C. | Jesus, S. M.
This work compares the resolution of a pressure and vector sensor based conventional Bartlett estimator, with their MVDR estimator counterparts, in the context of bottom characterization with a short vertical array. Santos et al. [1] demonstrated the gain of a vector sensor array (VSA) based linear estimator (Bartlett) for generic parameter estimation. Moreover, it was shown that for bottom characterization the highest resolution of the estimates were achieved with the vertical particle velocity measurements alone. The present work highlights the gain in parameter resolution of a VSA based MVDR estimator. It is shown, that also for a MVDR estimator, the vector sensor array data improves the resolution of parameter estimation. But, it is also shown, through simulations, that for bottom parameter estimation, the pressure based MVDR estimator has higher resolution and sidelobe attenuation than the VSA based Bartlett estimator. These results were verified for experimental data acquired by a four element, 30 cm long vertical VSA in the 8–14 kHz band, during the Makai Experiment 2005 sea trial, off Kauai I., Hawaii (USA).
显示更多 [+] 显示较少 [-]The authors would like to thank Michael Porter, chief scientist for the Makai Experiment, Jerry Tarasek for the loan of the vector sensor array used in the experiment, Paul Hursky, Martin Siderius, and Bruce Abraham for providing assistance with the data acquisition. The Makai Experiment was supported by the U.S. Office of Naval Research. This work was funded by National Funds through FCT- Foundation for Science and Technology under project SENSOCEAN (PTDC/EEA-ELC/104561/2008).
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