Experimental demonstration of sound‐speed inversion with matched‐field processing

1993 ◽  
Vol 93 (5) ◽  
pp. 2649-2655 ◽  
Author(s):  
Carolyn C. Karangelen ◽  
Orest Diachok
Keyword(s):  
Sound Speed ◽  
Experimental Demonstration ◽  
Matched Field Processing

scholarly journals Estimating the parameters of the seabed using the spatial characteristics of ocean ambient noise

2019 ◽  
Vol 283 ◽  
pp. 08004
Author(s):  
He Li ◽  
Xiniyi Guo ◽  
Li Ma ◽  
Guoli Song
Keyword(s):  
Experimental Data ◽  
Sound Speed ◽  
Critical Angle ◽  
Ambient Noise ◽  
Array Processing ◽  
Sound Field ◽  
Spatial Characteristics ◽  
Matched Field Processing ◽  
Spectrum Density ◽  
Snell Law

When solving traditional underwater problems, the boundary condition is always used to calculate the sound field. In practice, however, it is hard to get the boundary conditions of the seabed. So geoacoustics inversion is needed to acquire the parameters of the seabed. In this paper, a method estimating seabed parameters by using the spatial characteristics of ocean ambient noise is demonstrated without using matched-field processing. For the reason of the limit of the resolution of conventional beamforming (CBF), a method of synthetic array processing (SAP) is used because of some characters of cross-spectrum density matrix (CSDM). The result shows that the method of synthetic array processing enhanced the resolution of critical angle to some degree. By comparing the true bottomloss calculated by OASR, the result of traditional beamforming and the synthetic array processing, the result of synthetic array processing is closer to the true bottomloss than the result of traditional beamforming. After ensuring a range of critical angle, the sound speed of the seabed can be estimated by using Snell law. And then, an experimental data collected in Qingdao, China, 2016 is used to prove the validity of the method of synthetic array processing and estimate the local seabed parameters.

Bottom Geoacoustic Inversion by "Broadband" Matched-Field Processing

1998 ◽  
Vol 06 (01n02) ◽  
pp. 167-183 ◽  
Author(s):  
Michael I. Taroudakis ◽  
Maria G. Markaki
Keyword(s):  
Frequency Domain ◽  
Source Localization ◽  
Sound Speed ◽  
Good Accuracy ◽  
Depth Estimation ◽  
Benchmark Problems ◽  
Sediment Layer ◽  
Objective Functions ◽  
Matched Field Processing ◽  
Acoustic Data

Matched-Field Processing with a Genetic Algorithm is applied to the problem of bottom recognition with synthetic noise-free acoustic data. The data correspond to three classes of benchmark problems. Four alternative objective functions have been tested, all of them defined to be used with broadband data with either coherent or incoherent processing in the frequency domain. It has been concluded that the parameters corresponding to the sediment layer and especially the sound speed, are more accurately recovered by all means. Source localization and water depth estimation are made with good accuracy in all cases. It has also been shown that incoherent processing in the frequency domain has led to better results for the cases studied.

The Comparison of Bottom Parameter Inversion in Geoacoustic Space and in (P,Q) Space

2017 ◽  
Vol 25 (02) ◽  
pp. 1750011 ◽  
Author(s):  
Z. D. Zhao ◽  
E. C. Shang ◽  
Daniel Rouseff
Keyword(s):  
Sound Speed ◽  
Shift Parameter ◽  
Matched Field Processing ◽  
Acoustical Properties ◽  
Model Free ◽  
Parameter Inversion ◽  
Sea Bottom ◽  
Potential Possibility ◽  
Profile Estimation

The acoustical properties of the sea-bottom can be described by geoacoustic (GA) parameters or by reflective parameters: [Formula: see text] (phase shift parameter) and [Formula: see text] (absorption parameter). Both in GA space and in ([Formula: see text], [Formula: see text]) space, the parameters are difficult to measure and are instead estimated by inversion methods such as matched field inversion (MFI). In GA space, an assumed model is needed to mount the GA parameters for inverting (model dependent), while the reflective parameters ([Formula: see text], [Formula: see text] are model-free. In this paper, the efficiency and quality of matched field processing (MFP) in GA space as well as in ([Formula: see text]) space are compared and the potential possibility of bottom sound-speed-profile estimation is discussed.

DEDUCTIVE MULTI-TONE INVERSION OF SEABED PARAMETERS

2000 ◽  
Vol 08 (02) ◽  
pp. 271-284 ◽  
Author(s):  
M. A. AINSLIE ◽  
R. M. HAMSON ◽  
G. D. HORSLEY ◽  
A. R. JAMES ◽  
R. A. LAKER ◽  
...  
Keyword(s):  
Sound Speed ◽  
Differential Evolution Algorithm ◽  
Synthetic Data ◽  
Low Frequency ◽  
Intermediate Frequency ◽  
Practical Reasons ◽  
Unknown Parameters ◽  
Processing Scheme ◽  
Matched Field Processing ◽  
Two Phases

An iterative matched field processing scheme is described for efficient inversion of geoacoustic parameters in shallow water using a vertical receiving array at three frequencies in the range 50–500 Hz. The method relies on the assumption that the acoustic data are sensitive to different geoacoustic parameters at different frequencies. First an exhaustive 2D search is carried out at high frequency to determine initial estimates for density and sound speed. A second 2D search follows at an intermediate frequency to determine sediment attenuation and sound speed gradient. An iteration is carried out over these first two phases until these four parameters converge. In a third phase, the low frequency data are used to search for the remaining unknown parameters (primarily sediment thickness, substrate density and substrate sound speed) with a differential evolution algorithm. Finally all three phases are repeated iteratively, in principle until a complete converged solution (a self-consistent set of all inverted parameters) is found, although for practical reasons the search is terminated before convergence is demonstrated. Tests on synthetic data are reported demonstrating the accuracy and stability of the method. Initial results for measured data are also presented.

PROPAGATION MODEL ACCURACY FOR MFP

2000 ◽  
Vol 08 (03) ◽  
pp. 389-399 ◽  
Author(s):  
A. TOLSTOY
Keyword(s):  
High Resolution ◽  
Sound Speed ◽  
High Accuracy ◽  
Propagation Model ◽  
Model Accuracy ◽  
Geoacoustic Inversion ◽  
Propagation Models ◽  
Matched Field Processing ◽  
Selection Of ◽  
Excellent Accuracy

The selection of a propagation model for use in many underwater acoustic applications has been understood to be highly important for quite some time. However, it has not previously been understood how various models might actually degrade Matched Field Processing (MFP) performance even when input parameters are known exactly. That is, acoustic propagation models have not previously been benchmarked within the context of MFP where acoustic amplitudes and phases need to be highly accurate depending on the nature of the processor of interest, such as for a high resolution Capon processor. This paper discusses the SCOOTER, ORCA, and KRAKEN models, and a high angle PE model within the context of MFP. These models are compared to the SAFARI data generated for the Workshop97 geoacoustic inversion CAL case. In general it seems that all the abovementioned models show excellent accuracy for use with the Linear Processor. However, it is found that KRAKEN may experience unexpected difficulties at unpredictable frequencies where these errors can affect high resolution processing (as demonstrated by geoacoustic inversions via the RIGS method),14 that SCOOTER and PE require relatively long CPU times for high accuracy, and that how accurately parameters are interpolated, e.g., sound-speed profiles, can also be important. It should be noted that all of the models discussed in this work may be considered to be very accurate in the context of most applications, particularly those involving data.

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