2005
DOI: 10.1121/1.1921449
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The effects of ignored seabed variability in geoacoustic inversion

Abstract: Geoacoustic inversion using a matched-field inversion algorithm is a well-established technique for estimating the geoacoustic parameters of the seabed. This paper demonstrates how parameter estimation can be affected by unknown or wishfully ignored random range dependence of the true environment when the inversion model is--for practicality--assumed to be range independent. Simulations with controlled statistics were carried out using a simple shallow water model: an isospeed water column over a homogeneous e… Show more

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Cited by 10 publications
(4 citation statements)
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“…II C point 10͒. For example, Lapinski and Chapman 27 and Moreley et al 28 studied this non-linear aspect in some detail for variability in sediment sound speed ͑and water depth͒ using a numerical approach ͑i.e., using parabolic equation, PE, and normal mode propagation models͒. They showed that ignoring sound speed variability in matched field geoacoustic inversion leads to bias errors in sound speed estimates all other parameters that were inverted for.…”
Section: Range-independent Effective Parametersmentioning
confidence: 99%
“…II C point 10͒. For example, Lapinski and Chapman 27 and Moreley et al 28 studied this non-linear aspect in some detail for variability in sediment sound speed ͑and water depth͒ using a numerical approach ͑i.e., using parabolic equation, PE, and normal mode propagation models͒. They showed that ignoring sound speed variability in matched field geoacoustic inversion leads to bias errors in sound speed estimates all other parameters that were inverted for.…”
Section: Range-independent Effective Parametersmentioning
confidence: 99%
“…Over the past six decades, the principal observations used to estimate geoacoustic seabed properties have involved acoustic propagation over horizontal spatial scales of O (10 3 ) to O (10 4 ) m. Most often, the seabed is assumed as laterally invariant, or range independent, over such scales. However, it is clear from modeling that ignoring this dependence can lead to biases in the property estimates 22 24 . At much finer scales, direct sampling methods, such as cores and in situ probes, provide understanding of vertical variability at O (10 −2 ) to O (10 0 ) m. But direct sampling is costly due to the need of ship time, has limited penetration depth, and the sampling process can disturb the sample.…”
Section: Introductionmentioning
confidence: 99%
“…[32][33][34][35][36] The approach is to start the inversions with a half-space model and then bootstrapping each successive inversion by adding an underlying layer to determine the validity of using a particular number of layers. Here, the number of sediment layers that overlie a half-space is specified in a model.…”
Section: Introductionmentioning
confidence: 99%