Compensate ADP signal strength for spherical spreading.
beamUnspreadAdp(
x,
count2db = c(0.45, 0.45, 0.45, 0.45),
asMatrix = FALSE,
debug = getOption("oceDebug")
)
a set of coefficients, one per beam, to convert from beam echo intensity to decibels.
a boolean that indicates whether to return a numeric matrix, as opposed to returning an updated object (in which the matrix is cast to a raw value).
an integer specifying whether debugging information is
to be printed during the processing. This is a general parameter that
is used by many oce
functions. Generally, setting debug=0
turns off the printing, while higher values suggest that more information
be printed. If one function calls another, it usually reduces the value of
debug
first, so that a user can often obtain deeper debugging
by specifying higher debug
values.
First, beam echo intensity is converted from counts to decibels, by
multiplying by count2db
. Then, the signal decrease owing to
spherical spreading is compensated for by adding the term
x[["distance"]]
.
The coefficient to convert to decibels is a personal communication. The logarithmic term is explained in textbooks on acoustics, optics, etc.
Other things related to adp data:
[[,adp-method
,
[[<-,adp-method
,
ad2cpHeaderValue()
,
adp-class
,
adpEnsembleAverage()
,
adp_rdi.000
,
adp
,
as.adp()
,
beamName()
,
beamToXyzAdpAD2CP()
,
beamToXyzAdp()
,
beamToXyzAdv()
,
beamToXyz()
,
binmapAdp()
,
enuToOtherAdp()
,
enuToOther()
,
handleFlags,adp-method
,
is.ad2cp()
,
plot,adp-method
,
read.adp.ad2cp()
,
read.adp.nortek()
,
read.adp.rdi()
,
read.adp.sontek.serial()
,
read.adp.sontek()
,
read.adp()
,
read.aquadoppHR()
,
read.aquadoppProfiler()
,
read.aquadopp()
,
rotateAboutZ()
,
setFlags,adp-method
,
subset,adp-method
,
subtractBottomVelocity()
,
summary,adp-method
,
toEnuAdp()
,
toEnu()
,
velocityStatistics()
,
xyzToEnuAdpAD2CP()
,
xyzToEnuAdp()
,
xyzToEnu()
# NOT RUN {
library(oce)
data(adp)
plot(adp, which=5) # beam 1 echo intensity
adp.att <- beamUnspreadAdp(adp)
plot(adp.att, which=5) # beam 1 echo intensity
## Profiles
par(mar=c(4, 4, 1, 1))
a <- adp[["a", "numeric"]] # second arg yields matrix return value
distance <- adp[["distance"]]
plot(apply(a,2,mean), distance, type='l', xlim=c(0,256))
lines(apply(a,2,median), distance, type='l',col='red')
legend("topright",lwd=1,col=c("black","red"),legend=c("original","attenuated"))
## Image
plot(adp.att, which="amplitude",col=oce.colorsJet(100))
# }
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