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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实验的实验结果2005

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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方向压力传感器和三个速度仪表构成,在特定方向上敏感 - x,v或z。由于向量传感器能够测量其作为空间滤波器的三个粒子速度方向部件,因此在三维到达方向(DOA)估计中是有利的。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,以及海底参数。本文的目的是呈现在MakaieX'05在Makaiex'05期间收集的四元素垂直向量传感器阵列(VSA)数据集的实验结果,用于几何(范围和深度)和海底地理声学参数估计(沉积物压缩速度,密度和压缩衰减)。参数估计问题作为基于传统压力的延伸的反演方法,仅仅是Bartlett估计器到粒子速度。基于VSA的Bartlett估计器与通过方向性因子的基于Bartlett估计器响应的压力成比例,与仅限压力相比,提供了改进的侧瓣减少甚至抑制。将针对几何和海底参数说明这种行为,清楚地显示了使用VSA在水中阵列上使用VSA的优点。在源定值中,VSA优于相同数量的传感器的一个流水声阵列。此外,当VSA Bartlett估计器应用于海底参数估计时,将显示这些参数的估计分辨率显着增加,即使是密度和压缩衰减,也难以使用一种水机阵列估计的参数。

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