In brandynlucca/acousticTS: Estimating acoustic target strength via physics-based scattering models

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acousticTS

Acoustic backscatter from a single target or organism is expressed as the intensity of an echo typically denoted as the backscattering cross-section (σ~bs~, m^2^). Target strength (TS, dB re. 1 m^2^) is the logarithmic representation of σ~bs~ where: TS = 10 log~10~ (σ~bs~). TS can be used to convert integrated (e.g. nautical area scattering coefficient, S~A~, dB re. 1(m^2^ nmi^-2^) or volumetric backscatter (e.g. S~v~, dB re. 1 m^-1^) collected from fisheries acoustic surveys into units of number density, such as the volumetric density of a fish school (i.e. animals m^-3^). This parameter can also aid in classifying backscatter based on the multifrequency response of targets, such as separating likely echoes of large predatory fish from smaller prey. While there are several approaches for estimating TS, one common method is to apply physics-based models to predict theoretical TS that comprise exact and approximate solutions. The models provided in the acousticTS package can help provide TS estimates parameterized using broad statitsical distributions of inputs. This package is in a constant state of development with updates to the available model library, computational efficiency, and quality-of-life improvements.

General DOI https://doi.org/10.5281/zenodo.7600659

Latest release DOI

[Installation]{.underline}

You can install the current released version of acousticTS via:

devtools::install_github("brandynlucca/acousticTS")

Or you can install the development version of acousticTS like so:

devtools::install_github("brandynlucca/acousticTS@test-branch")

[Models currently available]{.underline}

Two-ray model for uniformly bent fluid-like cylinders ([DCM]{.underline})

Stanton, T.K., Clay, C.S., and Chu, D. (1993). Ray representation of sound scattering by weakly scattering deformed fluid cylinders: Simple physics and application to zooplankton. J. Acoust. Soc. Am., 94, 3454-3462.

Distorted wave Born approximation ([DWBA]{.underline})

Stanton, T.K., Chu, D., and Wiebe, P.H. (1998). Sound scattering by several zooplankton groups. II. Scattering models. J. Acoust. Soc. Am., 103, 236-253.

Stochastic distorted wave Born approximation ([SDWBA]{.underline})

Demer, D.A., and Conti, S.G. 2003. Reconciling theoretical versus empirical target strengths of krill: effects of phase variability on the distorted-wave Born approximation. ICES J. Mar. Sci., 60, 429-434.

SDWBA for uniformly bent scatterers ([SDWBA_curved]{.underline})

Demer, D.A., and Conti, S.G. 2003. Reconciling theoretical versus empirical target strengths of krill: effects of phase variability on the distorted-wave Born approximation. ICES J. Mar. Sci., 60, 429-434.

Stanton, T.K., Chu, D., and Wiebe, P.H. (1998). Sound scattering by several zooplankton groups. II. Scattering models. J. Acoust. Soc. Am., 103, 236-253.

Kirchoff-ray mode approximation ([KRM]{.underline})

Clay C.S. and Horne J.K. (1994). Acoustic models of fish: The Atlantic cod (Gadus morhua). J. Acoust. Soc. Am., 96, 1661-1668.

Modal series solution for gas-filled fluid spheres ([MSS_anderson]{.underline})

Anderson, V.C. (1950). Sound scattering from a fluid sphere. J. Acoust. Soc. Am., 22, 426-431.

Homogeneous solid sphere ([calibration]{.underline})

MacLennan D. N. (1981). The theory of solid spheres as sonar calibration targets. Scottish Fisheries Research No. 22, Department of Agriculture and Fisheries for Scotland.

[Examples]{.underline}

Below are examples of different models used to predict TS for a sardine with a gas-filled swimbladder, a tungsten carbide calibration sphere, a crustacean modeled as a prolate spheroid, and a generic gas-filled bubble.

Kirchoff Ray-Mode approximation for a Sardine with a gas-filled swimbladder

library( acousticTS )
### Call in the built-in sardine shape dataset
data( sardine )
### Inspect the object
print( sardine )
plot( sardine )
### We will now define a frequency range to predict TS over
frequency <- seq( 1e3 , 400e3 , 1e3 )
### And now we use the target_strength(...) function to model TS for this fish
sardine <- target_strength( sardine, 
                            frequency = frequency, 
                            model = "KRM" )
### Plot results
plot( sardine, type = 'model' )
### Extract model results
sardine_ts <- extract( sardine , "model") $KRM

Calibration sphere

### Let's create a calibration sphere 
### Default inputs here are a 38.1 mm diameter and a tungsten carbide 
### (WC) material properties.
cal_sphere <- cal_generate( )
### We will use the same frequency range as the previous example
### Calculate TS
cal_sphere <- target_strength( object = cal_sphere,
                               frequency = frequency,
                               model = "calibration" )
### Plot results
plot( cal_sphere , type = 'model' )
### Extract model results
calibration_ts <- extract( cal_sphere , "model" )$calibration

Fluid sphere (Anderson, 1950)

### Let's create a gas-filled bubble with a raidus of 4 mm
### This defaults to a density contrast, g_body, of 0.0012
### This defaults to a soundspeed contrast, h_body, of 0.220
bubble <- gas_generate( radius = 4e-3 ,
                        ID = "gas bubble" )
print( bubble )
### Model TS using the Anderson (1950) model
bubble <- target_strength( bubble,
                           frequency = seq( 1e3 , 300e3 , 0.5e3 ) ,
                           model = "MSS_anderson" )
### Plot results
plot( bubble , type = 'model' )

Fluid-like crustacean (prolate spheroid) using the distorted Born wave approximation (DWBA) and ray-based deformed cylinder model (DCM)

### First let's create a prolate spheroid shape 
### 25 mm long with a length-to-radius ratio of 16
crustacean <- fls_generate( shape = "prolate_spheroid" ,
                            length_body = 25.0e-3 , 
                            length_radius_ratio = 16 ,
                            radius_curvature_ratio = 3.3 ,
                            g_body = 1.03 ,
                            h_body = 1.02 )
print( crustacean )
plot( crustacean )
### Model TS using the ray-path deformed cylinder model (DCM), distorted wave
### Born approximation (DWBA), the stochastic variation of the DWBA (SDWBA) , 
### and specifically curved versions of both the DWBA and SDWBA 
crustacean <- target_strength( crustacean ,
                               frequency = seq( 1e3 , 200e3 , 1e3 ) ,
                               model = c( "DCM" , "DWBA" , "SDWBA" ,
                                          "DWBA_curved" , "SDWBA_curved" ) )
### Plot results
plot( crustacean , type = 'model' )

brandynlucca/acousticTS documentation built on July 4, 2025, 12:43 a.m.