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Geometric and seabed parameter estimation using a vector sensor array — Experimental results from Makai experiment 2005

机译:使用矢量传感器阵列的几何和海底参数估计— Makai实验2005的实验结果

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A vector sensor is constituted by one omni directional pressure sensor and three velocity-meters that are sensitive in a specific direction - x, v or z. Since a vector sensor is able to measure the three particle velocity directional components it acts as a spatial filter and therefore is advantageous 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 geoacoustic 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 behavior will be illustrated for geometric and seabed parameters clearly showing the advantages of the use of VSA over hydrophone arrays. In source localization the VSA outperforms 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 difficult to estimate using an array of hydrophones.
机译:矢量传感器由一个全向压力传感器和三个在特定方向(x,v或z)上敏感的速度计组成。由于矢量传感器能够测量三个粒子速度方向分量,因此它起着空间滤波器的作用,因此在三维到达方向(DOA)估计中具有优势。在DOA估计中获得的潜在增益可以扩展到其他几何参数,例如源范围和深度以及海床参数。本文的目的是介绍在MakaiEx'05实验期间收集的四元素垂直矢量传感器阵列(VSA)数据集的实验结果,用于几何(范围和深度)和海底地声参数估计(沉积物压缩速度,密度和压缩衰减) )。参数估计问题被提出为一种反演方法,该方法基于传统的仅压力Bartlett估计器对粒子速度的扩展。基于VSA的已开发的Bartlett估计器与唯一压力的Bartlett估计器响应成比例因子,与仅压力响应相比,改善了旁瓣的减小甚至抑制。将针对几何参数和海底参数说明此行为,从而清楚显示使用VSA优于水听器阵列的优势。在源定位中,VSA优于具有相同数量传感器的水听器阵列。此外,当将VSA Bartlett估计器应用于海床参数估计时,将显示这些参数的估计分辨率显着提高,即使对于密度和压缩衰减而言,也难以使用水听器阵列来估计参数。

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