Notes
on processing random binary calibration signals at IRIS/IDA GSN stations
Peter
Davis
Cecil and Ida Green Institute of
Geophysics and Planetary Physics
University of California, San Diego
La Jolla CA 92093-0225
pdavis@ucsd.edu
INTRODUCTION.
This
document is intended to provide users with supplemental information that may be
used to analyze random binary calibration tests routinely performed at IRIS/IDA
GSN stations. The procedures
used to characterize the full system response of sensors deployed at Global
Seismographic Network stations are described in Davis et al. (2005). Responses are encoded into
dataless SEED volumes and made available to users through the IRIS Data
Management System (DMS).
Independent tests of the accuracy of these published responses are
reported in the above paper and in Davis and Berger (2007).
One
important step in the system calibration process is to measure the relative
response of the principal seismometers and any analog anti-aliasing filters
shaping their output as a function of frequency. The procedure and theory of
calibration is explained in detail in Berger
et al. (1979). A random binary signal is fed into the calibration coils of
the seismometer, and the output, recorded for later analysis. In newer systems
(those deployed post 2000), the input signal is digitized on a separate channel
and retained for later analysis.
The shape of the sensor frequency response is found by fitting a
perturbed function of the nominal system to the cross-spectrum of the output
and the (known) input (Fels and Berger, 1994). The outcome is a representation of the
sensorŐs portion of the total system response in standard pole-zero format.
The
input random binary signal is a sequence of step functions of identical
amplitude but alternating polarity and characterized by a clock period T (see Berger et al. 1979, pg 272 for complete
references). At each interval T,
the signal has a 50-50 chance of changing state. Examples of several input series for clock periods used to
calibrate older IDA instruments are provided with this document. These series already have the FIR
filter response convolved into the random binary series. For users who wish to generate the
original series without the FIR response, the random number seed file and a C
program to read it are included as well.
(See File Notes below.) The clock
periods of the signals employed are listed in Table 1
and provided as a csv file.
Recordings of these random binary tests were
originally withheld from distribution to avoid confusing users. These time series have now been
encapsulated into SEED and will be made available as a special data product by
the DMS. The random binary input
to the coil varies with the version of data logger and with the run-time
configuration of various parameters set when the operator initiates the test. Although the field engineers note this
information in trip reports, it is not tabulated here, and no effort is made to
track the amplitude of the various input signals. Below are plots of example time series for each data logger
type and details of how they are generated.
NEXT GENERATION SYSTEM
At the core of the Next Generation System is the
Quanterra Q330HR data logger. The
Q330HR DAS generates the random binary signal and is configured at IRIS/IDA
stations to record the input on the ENZ-00 and LNZ-00 channels. Because the recorded input has been
processed by the DAS with the same digital filters as the output data stream,
comparison of the input and output permits a direct estimate of the pure sensor
transfer function.
Due to a design limitation, the Q330HR will not
generate a random binary series longer than 4.5 hours (16383 sec) nor with a
frequency lower than 0.49 Hz. The
series shown in Figure
1 and Figure
2 was generated with the following parameters:
Signal attnenuation -12 dB (+/- 2.5 V), frequency .4902
Hz
Duration = 4calc hours
The
response of the Z, N and E components of the seismometer are shown in the top
three traces, the input to the coils, on the bottom trace. Note that the polarity of the Z signal
is different from the N and E components.
This is always the case for the STS1 sensors.
SAN
2012 (IDA MK8) DAS
Like the
Q330HR, the MK8 records the random binary input signal, in this case on the
BHZ-10 and LHZ-10 channels, so a direct estimate of the sensor transfer
function may be made. Two examples
of waveforms from random binary tests are shown here. In the first example (Figure 3 and Figure 4),
intended to capture the low frequency response of the sensor, a twelve-hour
long signal with a clock period of 10 seconds is routed into the cal coils of
the STS1s. The response of the Z,
N and E components of the seismometer are shown in the top three traces, the
input to the coils, on the bottom trace.
In the second example (Figure 5 and Figure 6), a
higher frequency random binary signal ( clock period 0.1 sec, duration 30 mins)
is used to deduce the short period response.
REFTEK
9716 and 9718 (IDA MK7) DAS
Unlike
the systems listed above, the IDA MK7A, MK7B and MK7-ISP systems do not record
the input to the coil. Waveforms
from a random binary test recorded by a MK7 DAS are shown in Figure 7
and Figure 8. These waveforms were recorded on a
KS-54000 sensor. In such cases,
the polarity of the Z trace should be the same as for the N and E traces.
The
clock period used for the MK7A and MK7B DASs is typically 10 seconds and for
the MK7-ISP, 20 seconds. An
example of the input signal for each is contained in files input_mk7_cl10 and input_mk7_cl20, respectively.
FILE
NOTES
The
following files will be useful in dealing with data loggers preceding the MK8:
input_m7_cl10 - input signal from the MK7 DAS with a clock period
of 10 seconds. File is written in
4-byte floating point numbers.
input_m7_cl20 - input signal from the MK7 DAS with a clock period
of 20 seconds. File is written in
4-byte floating point numbers.
ranseeds - random numbers used as seed for the input signal
generator. File is written in
2-byte integers.
randstp.c - C-language program to read file ranseeds and generate a pseudo-random
binary time series.
REFERENCES
Berger,
J., D.C. Agnew, R.L. Parker and W.E. Farrell, Seismic system calibration: 2.
Cross-spectral calibration using random binary signals, BSSA, 69, 271-288, 1979.
Davis,
P. and J. Berger, Calibration of the Global Seismographic Network using tides, SRL,
78, 454-459,
2007.
Davis,
P., M. Ishii and G. Masters, An assessment of the accuracy of GSN sensor
response information, SRL, 76, 678-683, 2005.
Fels, J.-F. and J. Berger,
Parametric analysis and calibration of the STS-1 seismometer of the IRIS/IDA
seismographic network, BSSA, 84, 1580-1592, 1994.