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RDI ADCP Time Series
Data files for Tele=
dyne RDI ADCPs are described here. Ancillary data (e.g., temperature, p=
itch, roll) are also available independently, through scalar data products,=
see time series scalar data and time series scalar plots .
Oceans 3.0 API filt=
er : dataProductCode=3DRADCPTS
Revision History
2020304: netCDF file format update: added ancillary data (e.g. Beam Vel=
ocity, Correlations, Intensity), apply compression, and change format to ne=
tcdf4 classic.
20180501: New options added for three-beam solutions, screening and fis=
h detection.
20150903: RDI files now use corrected heading/pitch/roll as specified b=
y site and sitedevice meta data. RDI files with Earth co-ord data are rotat=
ed to the corrected heading or apply magnetic declination. These changes do=
not change the MAT/PNG/NC/PDF data products produced from RDI files other =
than the compassHeading/pitch/roll values within the MAT/NC files. These ch=
anges will allow RDI files to be made available.
20150601: Added bin-mapping options (None, nearest vertical, linear).=
li>
20150228: Depth cell / bin mapping added to correct range and velocity =
for tilt.
20141222: Heading correction rework (affecting ENU / uvw velocities): h=
andle sites with null positions, mobile sensors, autonomous deployments, an=
d better documentation of processing was done to the data.
20130317: Bug fixes, including making the number of dimensions of data =
structures fixed (trailing singleton dimensions are always dropped in MATLA=
B however).
20110328: NetCDF, CF1.5 compliant product released.
20110202: Correction for determination of ENU (with respect to true Nor=
th) velocities. Prior code assumed ADCP was downward-facing. Updated code u=
ses orientation or instrument to convert to ENU coordinates.
20100521: Derived backscatter added to MAT contents.
20100513: Initial NetCDF product released for RDI ADCPs, available in <=
a class=3D"external-link" href=3D"http://cf-pcmdi.llnl.gov/" rel=3D"nofollo=
w">CF-1.4 compliant format.
20100218: MAT contents made more complete and descriptive
20091208: Initial RDI and MAT products released
This data is available as processed data in MAT an=
d NETCDF formats. Content descriptions and example files a=
re provided below.
This binary format is specific to the manufacturer. Direct access to RDI=
files may be restricted until verified versions are available. When using =
Teledyne-RDI data acquisition software, data is normally stored in this way=
. Although we use custom-built drivers to communicate with our instruments,=
we can use the raw data in the log file to produce the RDI file which can =
be interpreted by Teledyne-RDI post-processing software. These files are us=
ually pre-generated and stored in the archive for fast retrieval, otherwise=
they are made on the fly like most other data products.
To produce the file, the following requirements apply:
A new RDI file is started at the beginning of each day, when the maximu=
m records per file is exceeded, or when the driver is restarted (this shoul=
d account for configuration changes, site changes, etc).
Only records with valid checksums are included.
The instrument date/time field is replaced using the NEPTUNE timestamp =
at the beginning of the log file (since this =
timestamp is more accurate than the instrument clock), and the checksum is =
recalculated.
For Beam or Instrument co-ordinate data, heading/pitch/roll (EH/EP/ER) =
data in the variable length data header are replaced as specified by s=
ite and sitedevice metadata (replacing the often unreliable onboard compass=
) (the EZ sensor source value is changed to manual for each). For Earth co-=
ordinate data, only the heading is updated with the value from the site and=
sitedevice metadata, if the internal compass sensor is used, it is correct=
ed for magnetic declination, else if the internal heading value is set manu=
ally, it is left alone. Also for Earth data, because the heading has change=
d, the North/South current velocities are rotated to the new heading. These=
changes do not change the velocities in the MAT/PNG/NC/PDF data products p=
roduced from RDI files, other than the compassHeading/pitch/roll values wit=
hin the MAT/NC files. The original magnetic compass, pitch and roll maybe r=
eplaced by these fixed or external sensor values, however, users can access=
the original sensor data via scalar data products and services.
For users' information and interest, the site and sitedevice information=
is available through the device details pages, for example: http://dmas.uvic.ca/DeviceListing?DeviceId=3D20003 =
. This information is also included in the metadata report that accompanies=
most data products.
This format is further described in the manufacturer's documentation .
The Teledyne-RDI software to read RDI files (winADCP) is available throu=
gh their website, although it is not obvious how to download. There are als=
o some questionable sites offering downloads that don't go anywhere except =
to potential malware. Users can request access through the Teledyne Marine =
Download Portal: https://tm-portal.force.com=
/TMsoftwareportal/s/ As always you can contact us for support, thr=
ough the main website, on Oceans 3.0 or here: Contact Support .
Example: RDIADCP75WH17432_20131113T000000.000Z.rdi
Oceans 3.0 API filt=
er : extension=3Drdi
Processed Data
Ensemble Period (ping averagi=
ng)
For RDI AD=
CP data file products (MAT and netCDF formats)
Ensemble Period:
When selecting any of the ensemble periods, this option will cause the s=
earch to perform the standard box-car average resampling on the data. 'Boxe=
s' of time are defined based on the ensemble period, e.g. starting every 15=
minutes on the 15s, with the time stamp given as the center of the 'box'. =
Acoustic pings that occur within that box are averaged and the summary stat=
istics are updated. This process is often called 'ping averaging'. The proc=
ess uses log scale averaging on the intensity data, which involves backing =
out the logarithmic scale, compute the weighted average, and then comp=
ute the logarithmic scale again. Weighted averages are used when raw files =
bridge an ensemble period and when the data is already an ensemble or ping =
average.
New files are started when the maximum records per file is exceeded=
(usually set to make files that will use less than 1 GB of memory when loa=
ded), or when there is a configuration, device or site changes. In the case=
where there is data from either side of a configuration change within the =
one ensemble period, two files will be produced with the same ensemble peri=
od, with the same time stamps, but different data. Users may use the ensemb=
le statistics on the number of pings or samples per ensemble to filter out =
ensembles that do not have enough data. (As an aside, we do this by default=
with clean averaged scalar data - each ensemble period needs to have at le=
ast 70% of it's expected data to be reported as good.)
The default value is no averaging, meaning the data is not altered. This=
option is only available for MAT and NETCDF files.
File-name mode field
Selecting an ensemble period will add 'Ensemble' followed by the ensembl=
e period. For example '-Ensemble600s'.
Velocity Bin-mappin=
g (tilt compensation EX)
For all RDI =
ADCP data products (PNG/PNG and MAT and netCDF formats)
This option specifies the bin-mapping processing method to be applied. B=
in-mapping is also known as 'depth cell mapping' or 'tilt compensation' or =
even 'map to vertical'. There are two methods, both correct for tilt effect=
s on ADCP velocity data, while the none option leaves the velocity data as =
is. For details on the two methods, see the section on correction and rota=
tion of velocities (included below). The 'None' option is the default f=
or Nortek ADCPs since the free version of the manufacturer's software does =
not apply bin-mapping (a core goal of our data products is to replicate the=
functionality offered by the manufacturer's software). The 'Nearest vertic=
al bin' is the default for RDI ADCPs as winADCP applies =
this method for Instrument or Beam co-ordinate data. The 'As configured on =
the device' option uses the configuration onboard to determine whether to a=
pply bin-mapping, this matches processing on-board the device (for Earth-co=
-ordinate data, while for Instrument or Beam co-ordinate data winADCP ignor=
es the device configuration and always uses 'Nearest vertical bin'). T=
he best method has been shown to be the linear interpolation method (Ott, 1992 ).
File-name mode field
The velocity bin-mapping option will be appended to the filename. For ex=
ample: '-binMapNone', 'binMapLinearInterp', 'binMapNearest'.
Three-beam Solutions (EX)
For all RDI =
ADCP data products (PNG/PNG and MAT and netCDF formats)
Three-beam solutions allow computation of velocity from three beams when=
the fourth beam has been masked or screened to NaN, as described in&n=
bsp;ADCP Velocity Computation: Correction and Rotation to East-North-Up Co=
-ordinate System, Three-beam Solutions and Screening (included bel=
ow). This option allows the user to use the on-device configured value=
or override it and select whether or not to use three-beam solutions. The =
default value retains the previous behaviour of ONC data products: off. Onl=
y available on Instrument or Beam co-ordinate data.
File-name mode field
If a value other than the default is used, a '-3beam'<value> will =
be appended to the file-name, where <value> is the value of the optio=
n matching the API filter.
Low Correlation Screen Th=
reshold (WC)
For all RDI =
ADCP data products (PNG/PNG and MAT and netCDF formats)
This option allows the user to control the RDI correlation screening ste=
p. The default value retains the previous behaviour of ONC data products: a=
threshold of 64 counts. Beam-velocities that have associated correlation v=
alues lower than this threshold are are masked / screened to NaN values. On=
ly available on Instrument or Beam co-ordinate data. The WC command configu=
res this value on-board the device which is then used for on-board processi=
ng (Earth co-ordinate data only). ONC data products can use the WC set=
value to match winADCP output or the user can override it.
File-name mode field
If a value other than the default is used, a '-corr'<value> will b=
e appended to the file-name, where <value> is the value of the option=
matching the API filter.
Error Veloci=
ty Screen Threshold (WE)
For all RDI =
ADCP data products (PNG/PNG and MAT and netCDF formats)
This option allows the user to control the RDI error veloctiy screening =
step. The default value retains the previous behaviour of ONC data products=
: a threshold of 2 m/s. Final East-North-Up co-ordinate velocities that hav=
e associated error velocity values higher than this threshold are masked / =
screened to NaN values (lower values are more stringent). Available on all =
data, except for velocities are the result of a three-beam solution, see&nb=
sp;ADCP Velocity Computation: Correction and Rotation to East-North-Up Co-=
ordinate System, Three-beam Solutions and Screening (included below) fo=
r more information on how three-beam solutions and the error velocites are =
related. The WE command configures this value on-board the device which is =
then used for on-board processing (Earth co-ordinate data only). ONC data p=
roducts can use the WE set value to match winADCP output or the user can ov=
erride it.
File-name mode field
If a value other than the default is used, a '-errVal'<value> will=
be appended to the file-name, where <value> is the value of the opti=
on matching the API filter.
False Target Thresh=
old Maximum (WA)
For all RDI =
ADCP data products (PNG/PNG and MAT and netCDF formats)
This option controls the False Target Detection algorithm, which is also=
known as the Fish Rejection algorithm. See chapter 7 in the adcp coordinate =
transformation_Jan10.pdf documentation from RDI. Essentially, the algor=
ithm looks at the echo levels from bins at the same depth/range and if ther=
e is a large difference in their levels, it rejects them in two steps: reje=
ct one bin (then the 3-beam solution may apply, so it is suggested to use F=
ish Rejection and Three-beam solutions together), and if that does not reso=
lve the difference, reject all bins at that depth/range. Lower values of th=
e threshold are more stringent. Available on Beam and Instrument co-ordinat=
e data only, Earth co-ordinate data may have had this algorithm to it onboa=
rd the device, see the WA command and configuration value. ONC data pr=
oducts can use the WA configuration value to match winADCP output or the us=
er can override it.
File-name mode field
If a value other than the default is used, a '-falseTar'<value> wi=
ll be appended to the file-name, where <value> is the value of the op=
tion matching the API filter.
ADCP Velocity Computatio=
n: Correction and Rotation to East-North-Up Co-ordinate System, Three-beam =
Solutions and Screening
Overall Processing Flow
Velocity data acquired from RDI and Nortek ADCPs can take on several for=
ms. The original, unaltered velocity data, read from the raw files is norma=
lly presented in the MAT file product as adcp.vel=
ocity (RDI) or data.velocity (Nortek). (Please note that the =
data structure names for RDI is adcp and for Nortek we use dat=
a , substitute data for adcp when looking at Nortek d=
ata). Also in the MAT file product is the config stru=
ct that contains information on how the data was collected. Based on the co=
nfiguration, the original data is processed to present the velocities relat=
ive to East-North-Up: this is the final data in the netCDF =
, MAT files and in the daily current plot PNG and PDF (see adcp.u, adcp.v, adcp.w in the <=
strong>MAT file and in the MAT file description below). u,v,w velo=
cities are always relative to geographic North and local gravity (for Up).<=
/p>
In general, the aim of ADCP post-processing is to replicate the function=
ality in the manufacturer's post-processing software: RDI's winADC=
P and Nortek's Surge and Storm &n=
bsp;(which replaced ExploreP ). RDI provides documentation on =
their rotations, see: ADCP Coordinate Transformation and the mor=
e general guide Acoustic Doppler Current=
Profiler: Principles of Operation - A Practical Primer (as a back=
ground only). Nortek's rotations are documented online, see: http://www.nortek-as.com/li=
b/forum-attachments/coordinate-transformation/view or the matlab c=
ode directly: post-2-71782-Xform.m . See <=
a class=3D"external-link" href=3D"http://www.rdinstruments.com/Support/logi=
n/Login.aspx?ReturnUrl=3D%2fsupport%2fsoftwarefirmware%2fcc_software.aspx" =
rel=3D"nofollow">RDI software support login for RDI software and&n=
bsp;http://www.nortek-as.com/en/support/software =
for Nortek software.
The overall processing flow is listed below. This sequence is as the cod=
e is written. Some of the steps listed here are expanded upon in sections f=
ollowing this one. Right away there is a decision point based on the co-ord=
inate system: Instrument & Beam versus Earth. The coordinate system par=
ameter in each device's configuration determines the type of data that is a=
cquired and how it is processed to produce u,v,w velocities. In the MAT file product, see config.coordSys . If the co-or=
dinate system is set to 'Beam', the original data contains the radial =
(along-beam) velocities for each of the 4 or 5 beams, otherwise the velocit=
ies are rotated to an orthogonal co-ordinate system: 'Instr' (RDI) or 'XYZ'=
(Nortek) means the original velocities have been rotated to a basis define=
d by horizontal plane of the instrument with an azimuth relative to the dir=
ection of beam 3, while 'Earth' is relative to the onboard magnetic compass=
or a fixed direction defined by config.heading_EH (RDI only). Our default =
setting is 'Beam' so that the most raw form of the data is collected. 'Ship=
' is not recognized/used. For RDI ADCPs, when the co-ordinate system i=
s either 'Earth' or 'Instr', the 4th row in the adcp.velocity matr=
ix is the error velocity (the measurement error on the velocity at that bin=
and time).
From Instrument or Beam data:
If Instrument co-ordinate data, convert from Instrument to Beam co-ordi=
nate data
Exclude bad beams (RDI only, specified by device attribute, forces thre=
e-beam solutions to on)
Apply correlation screening (RDI only, except for a fixed 50% screen on=
Nortek Signature55 data, applied to match Nortek's Signature Viewer softwa=
re, option available)
Apply fish detection screening (RDI only, if requested, tunable)
Apply bin-mapping (RDI default is 'nearest vertical bin', Nortek defaul=
t is none, option available)
Apply three-beam solutions (RDI only, if requested, option availab=
le)
Transform from Beam co-ordinate data to to Instrument co-ordinate data<=
/li>
Rotate Instrument data to true Earth (via a combination of fixed h=
eading/pitch/roll, magnetic declination corrected compass heading and onboa=
rd pitch/roll data)
Apply error velocity screening (RDI only, option available)
Do ensemble averaging if requested (option available)
From Earth data (for RDI only):
Do nothing if RDI source file has been rotated to true=
Earth (via a combination of fixed heading/pitch/roll, magne=
tic declination corrected compass heading and onboard pitch/roll data),
otherwise rotate from magnetic Earth to True Earth  =
;(via a combination of fixed heading/pitch/roll, magnetic declina=
tion corrected compass heading and onboard pitch/roll data)
Apply error velocity screening if the requested threshold is more strin=
gent than the screening applied onboard the device (option available)<=
/li>
Do ensemble averaging if requested (option available)
The steps above with option available (in brackets above) are t=
uneable by the user as detailed in the data product options below. The =
;ADCP.processingComments field in both Nortek and RDI MAT<=
/strong> file data products provides the user with a log of the decisions m=
ade in this processing flow. The MAT files (RDI only) also=
has a structure called ADCP.processingOptions that details w=
hat options the user chose and what options were actually applied, as some =
options, such as the error velocity screening threshold, are not always app=
licable. See the data product options and MAT file format sections below fo=
r more information. This is complicated, contact us =
for help.
Rotation of Velocities to East-North-Up Co-ordinate=
System (Earth step #1, Instr/Beam step #8)
RDI sensor source and sensor availability parameters determine if additi=
onal sensors are available to be used for rotation, such sensors include: m=
agnetic compass, tilt sensor (for pitch and roll), depth, conductivity and =
temperature (the last three are used to determine the sound speed, however =
we normally fix that value, see config.soundspeed_EC ). In the MAT file, see config.sensorSource_EZ and con=
fig.sensorAvail. If the magnetic compass is available, it is ofte=
n used for Earth co-ordination rotation. The Nortek ADCPs always have compa=
ss and tilt sensors and prescribed sound speeds.
Magnetic compasses are not reliable when in close proximity to varying e=
lectromagnetic or magnetic fields (electric power cables or the steel instr=
ument platform can cause the compass to be inaccurate). To improve the data=
, we normally supply a fixed heading from the site and device metadata. If =
the device is mobile, deployed on a mooring, cabled profiler or glider, a m=
obile position sensor is normally supplied. Here is an example of a mobile =
ADCP site: http://dmas.uvic.ca/Sites?siteId=3D1002=
06 and here is an example of a fixed site: ht=
tp://dmas.uvic.ca/Sites?siteId=3D1000359 . If the device is mobile and i=
s attached to a device that can supply better orientation information, such=
as an optical gyro, the data processing code will make use of that device =
when its sensors are assigned to the heading/pitch/roll of the ADCP's site =
(we currently do not yet have an example of such a scenario). If neither fi=
xed or mobile heading/pitch/roll are assigned, then the system defaults to =
the device's internal sensors. When using the onboard magnetic compass, a c=
orrection is applied for magnetic declination (if onboard heading is set ma=
nually (RDI only), magnetic declination correction is not done). For RDI on=
ly, we replicate RDI's gimbal correction for pitch.
Rotation of the input velocities to produce East-North-Up velocities (u,=
v,w) is performed accounting for the incoming co-ordinate system, types and=
sources of the data. This is somewhat complicated, therefore, all of the p=
rocessing steps are documented in the MAT files, see a=
dcp.processingComments . As an example, here is a common scenario: raw =
data has been collected in the 'Earth' co-ordinate system defined by the on=
board magnetic compass and pitch/roll senors, but the instrument is station=
ary with a known fixed heading, then difference between compass heading and=
the fixed is calculated and used to rotate the East and North velocities. =
In that case, adcp.processingComments would say (use the matl=
ab command char):
For advanced, interested users, here is the core code that does the rota=
tion for the scenario above, rotating Earth co-ordinate data derived on-boa=
rd the instrument to a fixed heading true Earth co-ordinate data set.
R=
DI ADCP Earth co-ordinates to True Earth (declination correction or heading=
rotation only, step #1 in Earth co-ordinate process flow)
=
if useCompassForHeading
ADCP.uMagnetic =3D squeeze(velocityInstrOrEarth(1,:,:)); % east=
velocity relative to magnetic North
ADCP.vMagnetic =3D squeeze(velocityInstrOrEarth(2,:,:)); % nort=
h velocity relative to magnetic north
% rotate to true Earth coords, get magnetic declination at this=
location
magdevRadians =3D -ADCP.magneticDeclination * pi/180; % magneti=
c declination in radians (negation is to convert heading to yaw) =
=20
M =3D [cos(magdevRadians) -sin(magdevRadians); sin(magdevRadian=
s) cos(magdevRadians)]; % standard 2D rotation
velocityTrue =3D M * velocityScreenedReshape(1:2,:);
ADCP.processingComments(end+1,1) =3D {'Rotated Earth co-ordinat=
e, device-supplied adcp.u/v to true North from onboard magnetic North, by a=
pplying a magnetic declination correction (pitch/roll rotation unchanged). =
'};
else =20
% rotate to true Earth coords: get the difference in yaw (trans=
forming heading to yaw first), apply standard 2D rotation
% Verification method: grab a bin, calculate the EN vector dire=
ction, do the correction, calculate vector direction, take the
% difference and it is the same difference as between the headi=
ng and the compass. The original method failed that test.=20
velocityTrue =3D nan(2, n*p);
for i =3D 1:p
yawCorrection =3D -(heading(min(length(heading),i)) - ADCP.=
compassHeading(i));
M =3D [cosd(yawCorrection) -sind(yawCorrection); sind(yawCo=
rrection) cosd(yawCorrection)]; % standard 2D rotation
velocityTrue(:, (i-1)*n+1:i*n) =3D M * velocityScreenedResh=
ape(1:2, (i-1)*n+1:i*n);
end
ADCP.processingComments(end+1,1) =3D {'Rotated Earth co-ordinat=
e, device-supplied adcp.u/v to true North from onboard magnetic North, usin=
g a fixed or variable external source true heading (pitch/roll rotation unc=
hanged). '};
end =20
velocityTrue =3D reshape(velocityTrue, [2 n p]);
ADCP.u =3D squeeze(velocityTrue(1,:,:));
ADCP.v =3D squeeze(velocityTrue(2,:,:));
Here's the rotation to true Earth co-ordina=
tes when the original data is in Instrument or Beam co-ordinates. This does=
not include the transformation from beam to instr (step #7). This is step =
#8 in the Instr/Beam overall process flow:
R=
DI ADCP rotate Instr co-ordinates to True Earth
vel=
ocityTrue =3D nan(3, n*p);
maxNumPosData =3D max([length(heading) length(pitch) length(roll)]); %=
either 1 or p, the number of time stamps
for i =3D 1:maxNumPosData =20
if any(isnan([heading(min(length(heading),i)) pitch(min(length(pitc=
h),i)) roll(min(length(roll),i))]))
M =3D nan(3,3);
else =20
% heading/pitch/roll matrices - this isn't the standard rotatio=
ns, but it matches what winADCP does, and this is how it was originally imp=
lemented: =20
% I considered various ways to get the heading index - pointers=
, use an eval, etc, but this is actually faster: heading(min(length(heading=
), i)) =20
M1 =3D [cosd(heading(min(length(heading),i))) sind(heading(min(=
length(heading),i))) 0; -sind(heading(min(length(heading),i))) cosd(heading=
(min(length(heading),i))) 0; 0 0 1];=20
M2 =3D [1 0 0; 0 cosd(pitch(min(length(pitch),i))) -sind(pitch(=
min(length(pitch),i))); 0 sind(pitch(min(length(pitch),i))) cosd(pitch(min(=
length(pitch),i)))];
M3 =3D [cosd(roll(min(length(roll),i))) 0 sind(roll(min(length(=
roll),i))); 0 1 0; -sind(roll(min(length(roll),i))) 0 cosd(roll(min(length(=
roll),i)))];
M =3D M1 * M2 * M3;
if strcmp(Config.orient, 'Up') % negate 1st & 3rd column
M(1:3,1) =3D -M(1:3,1);
M(1:3,3) =3D -M(1:3,3);
end =20
end
=20
% apply heading/pitch/roll rotations
if maxNumPosData =3D=3D 1
velocityTrue =3D M * velocityScreenedReshape(1:3,:);
else
velocityTrue(:, (i-1)*n+1:1:i*n) =3D M * velocityScreenedReshap=
e(1:3, (i-1)*n+1:i*n);
end
end
% extract u,v,w,error values - singleton dimensions handled later
velocityTrue =3D reshape([velocityTrue; velocityScreenedReshape(4,:)], =
[m n p]);=20
ADCP.u =3D squeeze(velocityTrue(1,:,:));
ADCP.v =3D squeeze(velocityTrue(2,:,:));=20
ADCP.w =3D squeeze(velocityTrue(3,:,:));
ADCP.velocityError =3D squeeze(velocityTrue(4,:,:));
For Nortek ADCPs, the process is a bit diff=
erent and simpler. We convert all data back to Beam co-ordinate data and th=
en use the same beam to true Earth code to derive the true Earth co-ordinat=
e data.
N=
ortek ADCP Earth and Instrument co-ordinates to Beam
%% get =
the original beam velocities
if strcmp(Config.coordSys, 'BEAM')
ADCP.processingComments(end+1,1) =3D {'Raw data matrix, data.velocity,=
is the beam radial velocities.'};
beamMatrix =3D ADCP.velocity;
elseif strcmp(Config.coordSys, 'XYZ')
ADCP.processingComments(end+1,1) =3D {'Raw data matrix, data.velocity, =
is the XYZ velocities (instrument co-ordinates). Used the instrument transf=
orm matrix to revert to beam radial velocities. '};
beamMatrix =3D T \ ADCP.velocity;
elseif strcmp(Config.coordSys, 'ENU')
ADCP.processingComments(end+1,1) =3D {'Raw data matrix, data.velocity, =
is the ENU velocities (Earth co-ordinates relative to onboard compass, pitc=
h, roll sensors). Used the instrument transform matrix and raw onboard sens=
or data to revert to beam velocities. '};
beamMatrix =3D nan(3, n*p);
for i =3D 1:p =20
hThis =3D (ADCP.compassHeading(i) - 90) * pi/180;
pThis =3D ADCP.pitch(i) * pi/180;
rThis =3D ADCP.roll(i) * pi/180;
H =3D [cos(hThis) sin(hThis) 0; -sin(hThis) cos(hThis) 0; 0 0 1];
PR =3D [cos(pThis) -sin(pThis)*sin(rThis) -cos(rThis)*sin(pThis);..=
.
0 cos(rThis) -sin(rThis); ...
sin(pThis) sin(rThis)*cos(pThis) cos(pThis)*cos(rThis)];
beamMatrix(:, (i-1)*n+1:1:i*n) =3D (H * PR * T) \ ADCP.velocity(:, =
(i-1)*n+1:i*n);
end
beamMatrix =3D reshape(beamMatrix, [3 p n]); =20
else
error('ONC:nortekENUvelocities:unknownCoodSys', 'Unknown co-ord system'=
); =20
end
N=
ortek ADCP Beam co-ordinates transform to True Earth (includes transform st=
ep, steps #7 & 8)
velocit=
yTrue =3D nan(3, n*p);
maxNumPosData =3D max([length(heading) length(pitch) length(roll)]); % eit=
her 1 or p, the number of time stamps
for i =3D 1:maxNumPosData
% heading/pitch/roll matrices =20
% this rotation is from Nortek: http://www.nortek-as.com/lib/forum-atta=
chments/coordinate-transformation/view
% I considered various ways to get the index - pointers, use an eval, e=
tc, but using 'min(length(heading),i)' is actually faster =20
hThis =3D (heading(min(length(heading),i)) - 90) * pi/180; % convert he=
ading to yaw, the Nortek code doesn't have a '-' here, but the sine term is=
negated below
pThis =3D pitch(min(length(pitch),i)) * pi/180;
rThis =3D roll(min(length(roll),i)) * pi/180;
H =3D [cos(hThis) sin(hThis) 0; -sin(hThis) cos(hThis) 0; 0 0 1];
PR =3D [cos(pThis) -sin(pThis)*sin(rThis) -cos(rThis)*sin(pThis);...
0 cos(rThis) -sin(rThis); ...
sin(pThis) sin(rThis)*cos(pThis) cos(pThis)*cos(rThis)]; =20
% apply heading/pitch/roll rotations
if maxNumPosData =3D=3D 1
velocityTrue =3D H * PR * T * beamReshape;
else
velocityTrue(:, (i-1)*n+1:1:i*n) =3D H * PR * T * beamReshape(:, (i=
-1)*n+1:i*n);
end
end
% extract w values (u,v below) - use permute to ensure we don't lose single=
ton dimensions
velocityTrue =3D reshape(velocityTrue, [3 p n]);
ADCP.u =3D permute(velocityTrue(1,:,:), [3 2 1]);
ADCP.v =3D permute(velocityTrue(2,:,:), [3 2 1]);
ADCP.w =3D permute(velocityTrue(3,:,:), [3 2 1]);
Correction for Tilt: Bin-mapping (For Instr/Beam data only, step #5)
In addition to coordinate system rotations, the orientation of the instr=
ument affects the vertical range on which the measurement bins are spaced (=
depth cell and measurement bin are synonymous). If the instrument is signif=
icantly tilted, the bins used to determine the velocities at each range wil=
l be at different water depths. Here is Figure 21 from Acoustic Doppler Current Profiler: Principles of Operation - A Pr=
actical Primer , notice in (B) that the highlighted depth cells are not =
the same as in (A):
=
RDI ADCP data collected in Earth co-ordinates normally has had a depth cel=
l mapping algorithm applied to align the depth cells to correct for tilt, w=
hile the other modes have not had it applied. Depth cell mapping is applied=
in post-processing in winADCP . Nortek's Storm =
/ Surge post-processing software also applies bin-mapping whe=
n doing co-ordinate system rotations/transforms. (The term 'bin-mappin=
g' is used by Nortek, RDI uses 'depth cell mapping'. We use 'bin-mapping' a=
s it's the most common term in the literature.) Conversely, Nortek ADC=
P data collected in ENU co-ordinates has not had bin mapping applied. To ap=
ply bin-mapping, ENU data is converted back to Beam data, bin-mapping is ap=
plied and then converted back to ENU, doing any rotations as needed. The ap=
proach originated as described by Pulkkinen (1992) . The Pulkkinen / RDI bin-mapping method is bas=
ed on matching up the nearest vertical bin in each beam for each of the ori=
ginal range steps, then the radial velocities from those bins are used in t=
he rotation to true Earth velocities. For compatibility with original VENUS=
ADCP data products, an alternative method is offered as a option as well, =
as described by Ott (2002) . In that paper, the Ott method is shown to be an improvemen=
t over the discrete nearest vertical bin matching method. The Ott method us=
es a linear interpolation between the nearest vertical bins for each beam f=
or each of the original range steps. The Ott method also interpolates over =
a small number of missing bins, otherwise missing data nullifies a greater =
extent of the data than it does in the nearest vertical bin method. The inn=
er and outer most bins can end up with NaN values when there are less than =
4 bins at the same vertical level, see the above graphic. This affects the =
nearest vertical bin method more so than the Ott method, and more bins are =
affected with increasing tilts.
Users are offered the option of 'None', 'Nearest vertical bin', or 'Line=
ar interpolation (Ott method)'. When the data is in Earth co-ordinates, bin=
-mapping cannot be applied/modified. For RDI Earth data, the nearest vertic=
al bin method has normally been applied, while Nortek Earth data does not h=
ave bin-mapping applied. In both cases, the users' preference may be overri=
dden. The RDI manual indicates that pitch or roll values greater than 20 de=
grees are not possible and nominal processing has, in the past, applied NaN=
values when the pitch or roll exceeds that limit. However, we have found t=
hat RDI ADCPs can accurately report higher tilts. The limit is now set to 6=
0 degrees for pitch/roll and at or above 90 degrees of average tilt, bin-ma=
pping is overridden to the 'None' option.
Bin-mapping is not applied to the backscatter and intensity data. Instea=
d, we offer a vertically corrected range in the mat file products and use t=
his range for the plots when plotting against depth. For example, if the bi=
n spacing is 1 m, but the tilt is 10 degrees, the vertical spacing is 0.98 =
m.
For advanced, interested users, here is the core code that does bin-mapp=
ing:
Near=
est vertical bin (RDI method)
%% =
apply nearest vertical bin-mapping (RDI method)
if isOrientUp
ZSG =3D [+1 -1 +1 -1]; % ADCP up/convex
else
ZSG =3D [+1 -1 -1 +1]; % ADCP down/convex
end
beamElAbsRad =3D abs(beamElevation) * pi/180; % calcs below, from beam2=
uvw.m, take the abs() and convert to rad, so do it here for speed
beamElRad =3D beamElevation * pi/180;
beamNearestVert =3D nan(size(beam)); =20
maxNumPosData =3D max([length(pitch) length(roll)]); % either 1 or p, =
the number of time stamps - gotta be the same length, error if not!
for k =3D 1:maxNumPosData % loop over time stamps and pitch/roll valu=
es
% NaN any pings that don't have good pitch/roll =20
if any([pitchOverLim(k) rollOverLim(k)])
doMaxPitchRollWarning =3D true;
continue
end
if any([isnan(pitch(k)) isnan(roll(k))])
doNaNPitchRollWarning =3D true;
continue
end
=20
% use the bin-mapping math from beam2uvw.m (not sure what ZSG and S=
C are supposed to be named for, but keep them for historical reasons)
SC =3D sin(beamElAbsRad)*cos(pitch(k))*cos(roll(k)) + ...
cos(beamElRad) .* ZSG .* [-sin(roll(k)) -sin(roll(k)) sin(pitc=
h(k))*cos(roll(k)) sin(pitch(k))*cos(roll(k))];
SC =3D abs(sin(beamElAbsRad) ./ SC); % the abs wasn't in beam2uvw=
.m but even with nominal conditions it needs to be there
vertBinIndex =3D (round(binIndex.' * SC)).';
indexOutBoundsFlag =3D vertBinIndex < 1 | vertBinIndex > n;
vertBinIndex(indexOutBoundsFlag) =3D 1;=20
for i =3D 1:m
beamNearestVert(i, :, k) =3D beam(i, vertBinIndex(i,:), k);
beamNearestVert(i, indexOutBoundsFlag(i), k) =3D NaN;
end =20
end
beam =3D beamNearestVert;
O=
tt method bin-mapping
%% do t=
he Ott method bin mapping, including Ott's filling/smoothing method
binSpacing =3D mean(diff(range));
minRangeExtrap =3D min(range) - binSpacing;
maxRangeExtrap =3D max(range) + binSpacing;
=20
for i =3D 1:m % loop over beams
% do this calc here since it doesn't change in time
matrixBeamElevationAzimuth =3D [-cosd(beamElevation(i))*sind(beamAz=
imuth(i)); cosd(beamElevation(i))*cosd(beamAzimuth(i)); -sind(beamElevation=
(i))] ./ sind(abs(beamElevation(i)));
for k =3D 1:p % loop over time stamps
iP =3D min(length(pitch),k);
iR =3D min(length(roll),k);
% NaN any pings that don't have good pitch/roll
pThis =3D pitch(iP);
rThis =3D roll(iR); =20
if any([pitchOverLim(iP) rollOverLim(iR)])
beam(i,:,k) =3D NaN;
doMaxPitchRollWarning =3D true;
continue
end
if any([isnan(pThis) isnan(rThis)])
beam(i,:,k) =3D NaN;
doNaNPitchRollWarning =3D true;
continue
end
% skip any pings that are all NaN
thisBeamTime =3D squeeze(beam(i,:,k));
iNaNthisBeamTime =3D isnan(thisBeamTime);
numNaNthisBeamTime =3D sum(iNaNthisBeamTime);
if numNaNthisBeamTime >=3D min(n * maxFracNaN, n - 1) % skip=
this beam time if too much data is NaN (need at least 2 valid points)
beam(i,:,k) =3D NaN;
continue
end
% for this time and beam, fill the NaNs with linear interpolati=
on, except where there are too many NaNs in a row
% this won't fill on outside of valid data - linear interpolati=
on doesn't extrapolate by default
if any(iNaNthisBeamTime)
% find consecutive NaNs for this beam and time, only if the=
re are enough of them to flag
iTooManyConsecNaNs =3D false(1, n);
if numNaNthisBeamTime >=3D maxConsecutiveNaNs
numConsec =3D 0;
for j =3D find(iNaNthisBeamTime, 1, 'first') : find(iNa=
NthisBeamTime, 1, 'last') % loop over depth bins
if iNaNthisBeamTime(j)
numConsec =3D numConsec + 1;
if numConsec > maxConsecutiveNaNs
iTooManyConsecNaNs((j-numConsec+1):j) =3D t=
rue;
end =20
else
numConsec =3D 0;
end
end =20
end
iNaNsInterp =3D iNaNthisBeamTime & ~iTooManyConsecNaNs;
thisBeamTime(iNaNsInterp) =3D interp1(binIndex(~iNaNthisBea=
mTime), thisBeamTime(~iNaNthisBeamTime), binIndex(iNaNsInterp));
end
% this is simplicaton of the commented code below
Mp =3D [1 0 0;0 cos(pThis) -sin(pThis);0 sin(pThis) cos(pThis)]=
;
Mr =3D [cos(rThis) 0 sin(rThis);0 1 0;-sin(rThis) 0 cos(rThis)]=
;
beamXYZ =3D Mr * Mp * matrixBeamElevationAzimuth;
actualVerticalRange =3D range * abs(beamXYZ(3));
=20
% % range calculation code from beam2uvw.m
% Mp =3D [1 0 0;0 cos(pThis) -sin(pThis);0 sin(pThis) cos(pThis=
)];
% Mr =3D [cos(rThis) 0 sin(rThis);0 1 0;-sin(rThis) 0 cos(rThis=
)];
% beamXYZ =3D Mr * Mp * [-cosd(beamElevation(i))*sind(beamAzimu=
th(i)); cosd(beamElevation(i))*cosd(beamAzimuth(i)); -sind(beamElevation(i)=
)];
% actualVerticalRange =3D range * abs(beamXYZ(3) ./ sind(abs(be=
amElevation(i)))); =20
% map the beam bins to the vertical range - allow some extrapol=
ation - won't extrap through NaNs though (good).=20
% Extrapolation limited to +/- one bin spacing.
beam(i,:,k) =3D interp1( actualVerticalRange, thisBeamTime, ran=
ge, 'linear', 'extrap' );
beam(i, actualVerticalRange > maxRangeExtrap | actualVertica=
lRange < minRangeExtrap, k) =3D NaN;
end
end
Three=
-Beam Solutions (For RDI ADCPs Only, Instr/Beam step #5)
In systems with four beams, the transformation from radial velocites to =
Earth co-ordinates velocities has redundant information; only three beams a=
re needed to resolve currents in the three orthogonal directions, while the=
4th beam effectively provides error estimation. In the case where exactly =
one bin out of of the four at any level is flagged and NaN'ed, then current=
s can still be calculated from the remaining three radial velocities, using=
the three-beam transformation solution. The screening steps that can flag =
the data 'NaN' prior to transformation include fish detection and correlati=
on threshold, as well as any bin-mapping (particularly the RDI nearest vert=
ical bin which can set many bins to NaN). The three-beam solution works by =
assigning the error velocity to be zero and then solving the transformation=
for the missing bin (for more details see Three Beam Solutions in adcp coord=
inate transformation_Jan08.pdf ). With the missing data filled in, =
the normal transform from Beam to Instrument co-ordinate data is applied.=
p>
In cases where the data quality team has determined that an entire beam =
is bad, they can supply a device attribute specifying the bad beam number. =
That beam is then excluded in the processing from beam or instr co-ords and=
the values are filled in with the three-beam solution. Only the U,V,W resu=
lts are affected, the raw velocity data as recorded by the instrument is pr=
esented without the exclusion. This forces the 3 beam option to on, regardl=
ess of the user input. The excluded beam number is mentioned in a comment o=
n both the currents plot and intensity plots and in the processing comments in the mat files . This is currently only available for RDI=
ADCPs with 4 beams.
Here is the code for three-beam solutions and transform from Beam to Ins=
trument (XYZ) co-ordinate data:
T=
hree beam solution and transform
%% =
apply the three beam solution
% Note, for instr data, this may be a bit redundant unless some data ha=
s been screened or bin-mapped out
if Config.coord_EX(4) =3D=3D '1' % only 3-beam if the EX parameter is =
set, this replicates winADCP's behaviour
isnanBM =3D isnan(beamMatrix);
is3beam =3D squeeze(sum(isnanBM, 1)) =3D=3D 1; % index of all bins=
over time that have 1 NaN only (3 beam)
transformMatrixRow4 =3D transformMatrix(4,:).';
for j =3D find(any(is3beam,2)).' % loop over the bin indices that=
have at least one 3 beam instance
for k =3D find(is3beam(j,:)) % loop over the times when the c=
urrent bin has a 3 beam instance
isnanThis =3D isnan(beamMatrix(:,j,k));
temp =3D beamMatrix(:,j,k) .* transformMatrixRow4;
beamMatrix(isnanThis,j,k) =3D -sum(temp(~isnanThis)) / tran=
sformMatrix(4, isnanThis);
end
end =20
ADCP.processingComments(end+1,1) =3D {['Three beam solution applied=
to ' num2str(sum(is3beam(:))) ' individual bins (of ' num2str(numel(beamMa=
trix)) ' total). ']};
else
ADCP.processingComments(end+1,1) =3D {'Three beam solution not appl=
ied as the EX command was set to xxx0x. (This matches the behaviour of winA=
DCP which responds to EX(4). We can override this on request, contact us. A=
s a side note, winADCP does not respond to EX(5), the command for bin-mappi=
ng; winADCP always does bin-mapping on beam co-ord data.'};
end
=20
%% convert bin-mapped, screened and 3-beamed data to XYZ
vTemp =3D reshape(beamMatrix, 4, n * p);
velocityInstrOrEarth =3D reshape(transformMatrix * vTemp, [m n p]);
Screening
Correlation screening is the most widely applied and effective screening=
step, noted as step #3 in the Instr/Beam overall processing flow. It is al=
so applied onboard RDI ADCPs when in Earth co-ordinate configuration, the v=
alue applied is available in the config structure.
Nortek ADCPs are generally three beam (so the three-beam solution option=
is not offered) and screening is not applied in the data products, except =
for a fixed 50% correlation screen on Nortek Signature55 data only, applied=
to match Nortek's Signature Viewer software.
RDI ADCPs screening steps also include a fish detection algorithm and sc=
reening, Instr/Beam step #4 in the overall process flow.
Once in Earth co-ordinates, the data can also be screened by the error v=
elocity. Error velocity screening only applies to data with four valid beam=
s (and non-zero error velocities). For further information on the screening=
steps, including algorithms, see adcp coordinate transformation_Jan08.pdf =
(RDI ADCPs only). This is step #9 in Instr/Beam and #2 in Earth data proce=
ss flows.
Data Verification
As noted earlier, the ultimate requirement for the ADCP data products is=
that they replicate the results of the manufacturer's software. We test ag=
ainst the manufacturer's software to verify the data at every software rele=
ase (regression testing). There are cases where this adherence is intention=
ally not true: if users choose any non-default option (or that says it's no=
t the RDI default), the results will not match the default processing in th=
e manufacturer's software, in particular, the Ott bin-mapping option is not=
available on winADCP at all. The testing suite includes manual and a=
utomated testing where the output of the manufacturer's software is compare=
d to the data products and where data products are compared to the captured=
files from the previous release. The test suite is regularly updated for a=
ny new scenarios. Improvements in the test procedure are also made as neede=
d. In addition to testing the software, there has been a significant effort=
to ensure that the metadata, in particular the heading metadata, is correc=
t. These steps include careful measurement and documentation at deployment =
time, verifying and vetting ROV heading sensors, comparing data to nearby A=
DCPs, comparing results between various processing methods, and perhaps the=
best check is to compare the currents with the known/modelled tides. Contact us for information on the testing procedures and =
metadata verification.
A recent simplification in testing came about because of an improvement =
in the generation of RDI file data products, which we arch=
ive to speed up generation of subsequent products, MAT /NC files and plots. As of November 2015, RD=
I files with Beam or Instr co-ordinate data will incorporate =
the same heading/pitch/roll values as used for rotation and bin-mapping, th=
at way, users and testers may load and process these files with RDI softwar=
e, matching the values they can obtain from MAT =
and NC file products. For Earth co-ordinate data in&n=
bsp;RDI files, if we update the heading, we also need=
to rotate the East (u) and North (v) velocities as the new heading will be=
different from the internal compass heading (either fixed value, mobile po=
sition sensor or a magnetic declination is applied) on which the onboard Ea=
rth co-ordinate rotation was done. In this case, we don't update the pitch/=
roll as we cannot update the bin-mapping done for Earth data. Fortunately, =
the pitch/roll data is generally good and we do not yet have any examples w=
here we do not use the internal pitch/roll data. Once the RDI files produced prior to November 2015 are re-generated, =
all RDI files will be made available in Data Search.
In all, the results from RDI winADCP, and Nortek software will match the=
processed data products. In addition, the original data, particularly=
the Beam co-ordinate data is always available in the RDI and Nortek raw binary files and as=
data.velocity (Nortek) and adcp.velocity &=
nbsp;(RDI) in the MAT files. The proces=
singComments will completely describe the steps applied to produc=
e the u,v,w processed velocities. In addition to the cod=
e snippets above, we are happy to supply more code, collaborate on that cod=
e, etc. We are interested in collaborating on QAQC processes, data verifica=
tion, processing, analysis and research. Contact us=
if you have any questions.
MAT Files
MAT files (v7) can be opened using MathWorks MATLAB 7.0 or later. The fi=
le contains four structures: meta, adcp, config, and units. For short durat=
ion searches (less than one day) or short duration data returned, the files=
will be concatenated, otherwise, expect one file per RDI file. (RDI files =
can break in the middle of a day due to data quantity limits or configurati=
on changes, otherwise there is one file per day. RDI files are used as a pr=
ocessing intermediary format.)
Meta: a structure array containing the following metada=
ta fields:
deviceID: A unique identifier to represent the instrument within the Oc=
ean Networks Canada data management and archiving system.
creationDate:Date and time (using ISO8601 format) that the data product=
was produced. This is a valuable indicator for comparing to other revision=
s of the same data product.
deviceName: A name given to the instrument.
deviceCode: A unique string for the instrument which is used to generat=
e data product filenames.
deviceCategory: Device category to list under data search ('Echosounder=
').
deviceCategoryCode: Code representing the device category. Used for acc=
essing webservices, as described here: API / webservice documentation (log in to see this link).
lat: Fixed value obtained at time of deployment. Will be NaN if mobile =
or if both site latitude and device offset are null. If mobile, sensor info=
rmation will be available in mobilePositionSensor structure..
lon: Fixed value obtained at time of deployment. Will be NaN if mo=
bile or if both site longitude and device offset are null. If mobile, senso=
r information will be available in mobilePositionSensor structure.
depth: Fixed value obtained at time of deployment. Will be NaN if =
mobile or if both site depth and device offset are null. If mobile, sensor =
information will be available in mobilePositionSensor structure.
deviceHeading: Fixed value obtained at time of deployment. Will be NaN =
if mobile or if both site heading and device offset are null. If mobile, se=
nsor information will be available in mobilePositionSensor structure.
devicePitch: Fixed value obtained at time of deployment. Will be NaN if=
mobile or if both site pitch and device offset are null. If mobile, s=
ensor information will be available in mobilePositionSensor structure.
deviceRoll: Fixed value obtained at time of deployment. Will be NaN if =
mobile or if both site roll and device offset are null. If mobile, sen=
sor information will be available in mobilePositionSensor structure.
siteName: Name corresponding to its latitude, longitude, depth position=
.
locationName: The node of the Ocean Networks Canada observatory. E=
ach location contains many sites.
stationCode: Code representing the station or site. Used for accessing =
webservices, as described here: API=
/ webservice documentation (log in to see this link).
dataQualityComments: In some cases, there are particular quality-relate=
d issues that are mentioned here.
MobilePositionSensor: A structure with information about sensors that p=
rovide additional scalar data on positioning and attitude (latitude, longit=
idue, depth below sea surface, heading, pitch, yaw, etc).
name: A cell array of sensor names for mobile position sensors. If not =
a mobile device, this will be an empty cell string.
sensorID: An array of unique identifiers of sensors that provide positi=
on data for mobile devices - this data may be used in this data product.
deviceID: An array of unique identifiers of devices that provide positi=
on data for mobile devices - this data may be used in this data product.
dateFrom: An array of datenums denoting the range of applicability of e=
ach mobile position sensor - this data may be used in this data product.
dateTo: An array of datenums denoting the range of applicability of eac=
h mobile position sensor - this data may be used in this data product.
typeName: A cell array of sensor names for mobile position sensors. If =
not a mobile device, this will be an empty cell string. One of: Latitude, L=
ongitude, Depth, COMPASS_SENSOR, Pitch, Roll.
offset: An array of offsets between the mobile position sensors' values=
and the position of the device (for instance, if cabled profiler has a dep=
th sensor that is 1.2 m above the device, the offset will be -1.2m).
sensorTypeID: An array of unique identifiers for the sensor type.=
correctedSensorID: An array of unique identifiers of sensors that=
provide corrected mobile positioning data. This is generally used for prof=
iling deployments where the latency is corrected for: CTD casts primarily.<=
/span>
deploymentDateFrom: The date of the deployment on which the data was ac=
quired.
deploymentDateTo: The date of the end of the deployment on which the da=
ta was acquired (will be NaN if still deployed).
samplingPeriod: Sample period / data rating of the device in seconds, t=
his is the sample period that controls the polling or reporting rate of the=
device (some parsed scalar sensors may report faster, some devices report =
in bursts) (may be omitted for some data products).
samplingPeriodDateFrom: matlab datenum of t=
he start of the corresponding sample period (may be omitted for some data p=
roducts).
samplingPeriodDateTo: matlab datenum of the end of the corresponding sa=
mple period (may be omitted for some data products).
sampleSize: the number of readings per sample period, normally 1, excep=
t for instruments that report in bursts. Will be zero for intermittent devi=
ces (may be omitted for some data products).
SamplePeriodSensor: A structure array with an entry for each scalar sen=
sor on the device (even though this metadata is for complex data products t=
hat don't use scalar sensors).
sp: sample period in seconds (array), unless sensorid is NaN then this =
is the device sample period
dateFrom: array of date from / start date (inclusive) for each sample p=
eriod in MATLAB datenum format.
dateTo: array of date to / end date (exclusive) for each sample period =
in MATLAB datenum format.
sampleSize: the number of readings per sample period (array). Normally =
1, except for instruments that report in bursts. Will be zero for intermitt=
ent devices.
deviceID: array of unique identifiers of devices (should all be th=
e same).
sensorID: array of unique identifiers of sensors on this device.=
li>
isDeviceLevel: flag (logical) that indicates, when true or 1, if the co=
rresponding sample period/size is from the device-level information (i.e. a=
pplies to all sensors and the device driver's poll rate).
sensorName: the name of the sensor for which the sample period/size app=
lies (much more user friendly than a sensorID).
citation: a char array containing the DOI citation text as it appears o=
n the Dataset Landing Pag=
e . The citation text is form=
atted as follows: <Author(s) in alphabetical order>. <Publication =
Year>. <Title, consisting of Location Name (from searchTreeNodeName o=
r siteName in ONC database) Deployed <Deployment Date (sitedevicedatefro=
m in ONC database)>. <Repository>. <Persistent Identifier, whic=
h is either a DOI URL or the queryPID (search_dtlid in ONC database) >. Accessed Date <query creation date (sea=
rch.datecreated in ONC database)>
Attribution: A structure array with information on any contributors, or=
dered by importance and date. If an organization has more than one rol=
e it will be collated. If there are gaps in the date ranges, they are fille=
d in with the default Ocean Networks Canada citation. If the "Attribution Required?" field is set to "No" on the=
Network Console then the citation will not appear. Here are the fields:<=
img class=3D"confluence-embedded-image confluence-content-image-border" dra=
ggable=3D"false" src=3D"9a03d508026c5153a7bcdc2740675494" data-image-src=3D=
"/download/attachments/42175743/image2022-3-4_16-35-23.png?version=3D1&=
modificationDate=3D1646440526000&api=3Dv2" data-unresolved-comment-coun=
t=3D"0" data-linked-resource-id=3D"104924041" data-linked-resource-version=
=3D"1" data-linked-resource-type=3D"attachment" data-linked-resource-defaul=
t-alias=3D"image2022-3-4_16-35-23.png" data-base-url=3D"https://wiki.oceann=
etworks.ca" data-linked-resource-content-type=3D"image/png" data-linked-res=
ource-container-id=3D"42175743" data-linked-resource-container-version=3D"3=
2" alt=3D"" width=3D"468" height=3D"116">
acknowledgement: the acknowledgement text, usually formatted as "<or=
ganizationName> (<organizationRole>)", except for when there are n=
o attributions and the default is used (as shown above).
startDate: datenum format
endDate: datenum format
organizationName
organizationRole: comma separated list of roles
roleComment: primarily for internal use, usually used to reference rele=
vant parts of the data agreement (may not appear)
adcp: structure containing the ADCP data, having the fo=
llowing fields.
range: vector of distance to each bin centre. If bin mapping compens=
ation for tilt is active, then the bins are moved so that ADCP.range is now=
the vertical range to the corrected bin centres (ADCP.range values are not=
changed by bin-mapping). See adcp.processingComments to see if bin mapping=
was applied. To calculate the depth of each velocity bin, use the followin=
g:
if strcmp(Config.orient, 'Up')
&=
nbsp; binDepth =3D Meta.depth - ADCP.range;
else binDepth =3D Meta.depth + ADCP.range;
end
corr: 3D matrix, correlation time-series for each bin
intens: 3D matrix, intensity time-series for each bin (also known as re=
ceived signal strength intensity or RSSI, multiply by 0.45 dB/count to conv=
ert to a relative dB scale)
velocity: 3D matrix, corresponds directly to output of instrument and s=
o depends on configuration coordinate system
percentGood: 3D matrix, percent good time-series for each bin
ens: vector, ensemble number (replaced ensFirst for averaged products)<=
/li>
ensFirst: vector of the first ensemble number in an ensemble average (a=
veraged products only, replaces ens).
compassHeading: vector, containing the EH values from the RDI files. Th=
is is either the fixed value from site and sitedevice headings (if not null=
), or values from an assigned true heading mobile position sensor. If neith=
er, then it defaults to the magnetic compass heading data.
pitch: vector, containing the EP values from the RDI files. This is eit=
her the fixed value from site and sitedevice headings (if not null), or val=
ues from an assigned true heading mobile position sensor. If neither, then =
it defaults to the onboard pitch sensor data.
roll: vector, containing the ER values from the RDI files. This is eith=
er the fixed value from site and sitedevice headings (if not null), or valu=
es from an assigned true heading mobile position sensor. If neither, then i=
t defaults to the onboard roll sensor data.
time: vector, timestamp in datenum format (obtained from time the readi=
ng reached the shore station)
temperature: vector, temperature time-series
salinity: vector salinity time-series, (may contain constant values dep=
ending on device configuration)
pressure: vector, pressure time-series. From RDI manual: "Contains the =
pressure of the water at the transducer head relative to one atmosphere (se=
a level). Output is in decapascals" . Converted to decibar. Can be a =
fixed value depending on configuration and hardware. In the binary RDI file=
s and raw data streams, negative pressure values wrap - this isn't document=
ed. In winADCP, negative values are truncated to zeroes, while in our data =
products and parsers we unwrap them to express the negative values (negativ=
e pressures should only occur in test or erroneous data).
depth: vector, depth of the device below the water surface as measured =
by the device for each ping. Can be set to a fixed value by the ED command =
/ device attribute. For fixed deployments, this value is replaced in the RD=
I file by our code with the site depth plus offset, which is also reported =
as meta.depth. If not a fixed location deployment where the device is auton=
omous or mobile, this value is unaltered. It will vary with the tide and mo=
vement.
soundSpeed: vector speed of sound time-series, (may contain constant va=
lues depending on device configuration)
uMagnetic (optional): 2D matrix, East velocity relative to magnetic Nor=
th
vMagnetic (optional): 2D matrix, North velocity relative to magnetic No=
rth
processingCommments: a string documenting all of the processing steps d=
one to produce adcp.u/v/w. Use char(adcp.processingComments)
t=
o print out the text.
processingOptions: a structure with the data product option set that wa=
s requested and what was actually done (not all options are available and m=
aybe overriden at run time, this will be explained in the processingComment=
s).
velocity_sourceInfo: a string describing the source of data in adcp.vel=
ocity
uvw_sourceInfo: a string describing the resulting final, rotated data i=
n adcp.u/v/w
magneticDeclination: value that can be applied to correct the compassHe=
ading to true North
binMappingOption: bin-mapping method applied as determined by the data =
product option chosen and data available.
u: 2D matrix, East velocity relative to True North
v: 2D matrix, North velocity relative to True North
w: 2D matrix, Upward Velocity
u_std, v_std, w_std: standard deviations for ensemble averaged u,v,w&nb=
sp;(averaged products only)
u_count, v_count, w_count: the number of ensembles/pings that contribut=
ed to u,v,w (averaged products only). Differs from pingsPerEnsemble in that=
it accounts for filtered / NaN-ed data
velocityError: 2D matrix, computed using RDI algorithm
backscatter: 3D matrix based on received signal strength intensity (adc=
p.intensity), compensated for two-way spreading (20LogR) and absorption. Eq=
uation based on Gostiaux and van Ha=
ren ("Extracting Meaningful Information from Uncalibrated Backscattered=
Echo Intensity Data, Journal of Atomsheric and Oceanic Technology, 72, 943=
-949, 2010). The absorption computation follows Ainslie and Malcolm ("A sim=
plified formula for viscous and chemical absorption in sea water", Journal =
of the Acoustical Society of America, 103(3), 1671-1672, 1998). Absorption =
coefficient based on mean depth, temperature and salinity in adcp structure=
.
meanBackscatter: same as above, except averaged over the four beams to =
create a 2D matrix. Averaging is done by converting to standard intensity, =
averaging, then converting back to decibels.
config : structure conta=
ining ADCP configuration details, where some field names are appended with =
'_XX' to represent the corresponding configuration command (beneficial for =
experienced RDI ADCP users).
=
fwVer: CPU firmware version
fwRev: CPU firmware revision
sysCfg: hardware configuration definition
freq: frequency
beamPattern: convex or concave
orient: orientation (e.g.,'Up' indicates transducers are looking upward=
)
beamAngle: beam angle
janusCfg: description of Janus Configuration
lagLength: time period between sound pulses
nbeams: number of beams
nbins_WN: number of bins
npings_WP: number of pings per ensemble
cellSize_WS: length per cell
profilingMode: sigal processing mode
corrThresh_WC: correlation threshold
codeReps: code repetitions in transmit pulse
percentGoodMin_WG: percent good threshold
errVelThreshold_WE: error velocity threshold
timePing_TP: time between pings within ensemble
coord_EX: coordinate transformation processing parameters
coordSys: coordinate system (evaluated from coord_EX)
headingAlign_EA: correction factor for physical heading misalignment
headingBias_EB: correction factor for electrical/magnetic heading bias<=
/li>
heading_EH: manual setting of the heading from device attributes (not i=
n RDI file, added after)
sensorSrc_EZ: defines selected source of environmental sensor data
sensorAvail: defines available sources of environmental sensor data
bin1Dist: distance to the middle of the first depth cell
transmitLength_WT: length of the transmit pulse
falseTrgt_WA: false target threshold
transmitLagDistance: distance between pulse repetitions
cpuSN: CPU board SN
sysBndwdth_WB: bandwidth setting (narrow or wide)
sysPower_CQ: system power setting
instSN: instrument serial number
ensInterval: ensemble interval
ambiguityVelocity_WV: radial ambiguity velocity (not in RDI, added afte=
r)
soundAbsorptionCoefficient: sound absorption coefficient used for compu=
ting backscatter
units : structure containing unit of measure for fields =
in structures above. For instance, units.pressure=3D'decibar'.
=
p>
For details about the configuration parameters, refer to the manufacturer documentation (esp=
ecially the WorkHorse Commands and Output Data Format manual).
Example: RDI=
ADCP75WH3808_20101106T000225.mat
Oceans 3.0 API filt=
er : extension=3Dmat
NETCDF Files
NetCDF is a machine-independent data format o=
ffered by numerous institutions, particularly within the earth and ocean sc=
ience communities. Additional resources are noted here . For short duration searches (less than one day) or sho=
rt duration data returned, the files will be concatenated, otherwise, expec=
t one file per RDI file. (RDI files can break in the middle of a day due to=
data quantity limits or configuration changes, otherwise there is one file=
per day. RDI files are used as a processing intermediary format.)
The RDI NetCDF file is extracted from the data con=
tained in the above MAT file. The NetCDF =
file contains the following main variables: u, v, w, time, binmap_depth=
, where the binmap_depth variable here is distinct from =
the pressure sensor measurement in the MAT file (adcp.=
depth ). When there is bin-mapping performed on the data, the =
binmap_depth is calculated as meta.depth - adcp.range ; i=
t is the approximate water depth at which the measurement bins are located.=
If bin-mapping is 'none', then the binmap_depth and the depth=
are equal. depth is calculated as meta.depth - adcp=
.backscatterVerticalRange, which is the range corrected for tilt.=
depth is used to plot the beam-averaged backscatter and any other=
beam-averaged values that are not bin-mapped. The structure and content of=
the netCDF file is very similar to that of the MAT file, =
including the variable naming. The RDI a=
nd Nortek netCDF files are intended to be ve=
ry similar, even interchangeable with the same structure and definitions.&n=
bsp;
The NetCDF files are intended to be in comp=
liance with the CF-1.7 standard. Depending on the compliance checker that i=
s used the data may not meet this standard for the following reasons: The u=
nits dB are not defined, and the feature type of the data is not defined.=
span>
Oceans 3.0 API filter : extension=3Dnc =
span>
Example: RDIADCP75WH17575_20130314T194500Z_20130502T164500Z-Ensemble90=
0s_binMapNearest.nc
C=
lick here to see the netCDF structure from the example file above... =
Above example may be out of date. Recent ch=
anges include: added compass heading, updated units.
Discussion
To comment on this product, click Add Comment below.
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