Geoacoustic inversion of the acoustic-pressure vertical phase gradient from a single vector sensor

2019 ◽  
Vol 146 (5) ◽  
pp. 3159-3173 ◽  
Author(s):  
Junjie Shi ◽  
Stan E. Dosso ◽  
Dajun Sun ◽  
Qingyu Liu
Keyword(s):  
Acoustic Pressure ◽  
Geoacoustic Inversion ◽  
Phase Gradient ◽  
Vector Sensor

Geoacoustic inversion of the pressure gradient data using a single vector sensor

2018 ◽  
Vol 144 (3) ◽  
pp. 1974-1974
Author(s):  
Junjie Shi ◽  
Dajun Sun ◽  
Stan E. Dosso ◽  
Qingyu Liu
Keyword(s):  
Pressure Gradient ◽  
Geoacoustic Inversion ◽  
Vector Sensor

scholarly journals Geoacoustic inversion based on both acoustic pressure and particle velocity

2006 ◽  
Vol 120 (5) ◽  
pp. 3355-3356
Author(s):  
A. Vincent van Leijen ◽  
Jean‐Pierre Hermand ◽  
Kevin B. Smith
Keyword(s):  
Particle Velocity ◽  
Acoustic Pressure ◽  
Geoacoustic Inversion

Acoustic pressure‐vector sensor array

2004 ◽  
Vol 115 (5) ◽  
pp. 2620-2620 ◽  
Author(s):  
Dehua Huang ◽  
Roy C. Elswick ◽  
James F. McEachern
Keyword(s):  
Sensor Array ◽  
Acoustic Pressure ◽  
Vector Sensor ◽  
Vector Sensor Array

scholarly journals A Novel Self-Calibration Method for Acoustic Vector Sensor

2018 ◽  
Vol 2018 ◽  
pp. 1-9
Author(s):  
Yao Zhang ◽  
Jin Fu ◽  
Guannan Li
Keyword(s):  
Acoustic Pressure ◽  
Calibration Method ◽  
Estimation Accuracy ◽  
Spatial Gradient ◽  
Arrival Angle ◽  
Acoustic Vector Sensor ◽  
Self Calibration ◽  
Vector Sensor ◽  
Calibration Algorithm ◽  
Simulation Results

The acoustic vector sensor (AVS) can measure the acoustic pressure field’s spatial gradient, so it has directionality. But its channels may have nonideal gain/phase responses, which will severely degrade its performance in finding source direction. To solve this problem, in this study, a self-calibration algorithm based on all-phase FFT spectrum analysis is proposed. This method is “self-calibrated” because prior knowledge of the training signal’s arrival angle is not required. By measuring signals from different directions, the initial phase can be achieved by taking the all-phase FFT transform to each channel. We use the amplitude of the main spectrum peak of every channel in different direction to formulate an equation; the amplitude gain estimates can be achieved by solving this equation. In order to get better estimation accuracy, bearing difference of different training signals should be larger than a threshold, which is related to SNR. Finally, the reference signal’s direction of arrival can be estimated. This method is easy to implement and has advantage in accuracy and antinoise. The efficacy of this proposed scheme is verified with simulation results.

scholarly journals Open-Lake Experimental Investigation of Azimuth Angle Estimation Using a Single Acoustic Vector Sensor

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Anbang Zhao ◽  
Lin Ma ◽  
Juan Hui ◽  
Caigao Zeng ◽  
Xuejie Bi
Keyword(s):  
Acoustic Pressure ◽  
Azimuth Angle ◽  
Estimation Methods ◽  
Acoustic Vector Sensor ◽  
Angle Estimation ◽  
Passive Detection ◽  
Vector Sensor ◽  
Sonar System ◽  
Multichannel Signals ◽  
Structure Sensor

Five well-known azimuth angle estimation methods using a single acoustic vector sensor (AVS) are investigated in open-lake experiments. A single AVS can measure both the acoustic pressure and acoustic particle velocity at a signal point in space and output multichannel signals. The azimuth angle of one source can be estimated by using a single AVS in a passive sonar system. Open-lake experiments are carried out to evaluate how these different techniques perform in estimating azimuth angle of a source. The AVS that was applied in these open-lake experiments is a two-dimensional accelerometer structure sensor. It consists of two identical uniaxial velocity sensors in orthogonal orientations, plus a pressure sensor—all in spatial collocation. These experimental results indicate that all these methods can effectively realize the azimuth angle estimation using only one AVS. The results presented in this paper reveal that AVS can be applied in a wider range of application in distributed underwater acoustic systems for passive detection, localization, classification, and so on.

Localization Technology Basing Two-Dimensional Vector Sensor

2012 ◽  
Vol 622-623 ◽  
pp. 1384-1388
Author(s):  
Peng Han ◽  
Yang Liu
Keyword(s):  
Performance Analysis ◽  
Acoustic Pressure ◽  
Simulation Experiment ◽  
Simple Algorithm ◽  
Two Dimensional ◽  
Dimensional Vector ◽  
New Approach ◽  
Localization Method ◽  
Vector Sensor ◽  
Vector Sensors

A two-dimensional (2D) vector sensor measures one acoustic pressure and two acoustic particle velocity components of the acoustic field. In this paper, a new approach is presented for localization of acoustic sources using an array of 2D vector sensors. A simple algorithm for estimating the source location with this array is presented along with their statistical performance analysis. The simulation experiment is presented to verify the efficacy of the proposed localization method and simultaneously analyzing the factors which affects the accuracy of localization.

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