Seismic Network Operations

IU MSKU

Masuku, Gabon

IU MSKU commences operations on: 1999,058

Country Flag
Host: Masuku University of Science and Technology
Latitude: -1.656
Longitude: 13.612
Elevation: 312
Datalogger: Q680
Broadband: STS-1V/VBB
Accelerometer: FBA-23
Telemetry Status at the NEIC: No Data In More Than 24 Hours
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Vault Condition: Tunnel into a hill side.

Location CodeChannel CodeInstrumentFlagsSample RateDipAzimuthDepth
00VK1Quanterra DA temperature monitorCG0.100.000.000.00
BC1CMG3-TTG40.000.000.000.00
BC0STS-1V/VBBTG20.000.000.000.00
20LNZFBA-23CG1.00-90.000.0025.00
20LNNFBA-23CG1.000.002.0025.00
20LNEFBA-23CG1.000.0092.0025.00
20HNZFBA-23TG80.00-90.000.0025.00
20HNNFBA-23TG80.000.002.0025.00
20HNEFBA-23TG80.000.0092.0025.00
10LHZCMG3-TCG1.00-90.000.0025.00
10LHNCMG3-TCG1.000.002.0025.00
10LHECMG3-TCG1.000.0092.0025.00
10HHZCMG3-TTG80.00-90.000.0025.00
10HHNCMG3-TTG80.000.002.0025.00
10HHECMG3-TTG80.000.0092.0025.00
10BHZCMG3-TCG40.00-90.000.0025.00
10BHNCMG3-TCG40.000.002.0025.00
10BHECMG3-TCG40.000.0092.0025.00
00VHZSTS-1V/VBBCG0.10-90.000.0025.00
00VHNSTS-1H/VBBCG0.100.000.0025.00
00VHESTS-1H/VBBCG0.100.0090.0025.00
00LHZSTS-1V/VBBCG1.00-90.000.0025.00
00LHNSTS-1H/VBBCG1.000.000.0025.00
00LHESTS-1H/VBBCG1.000.0090.0025.00
00BHZSTS-1V/VBBCG20.00-90.000.0025.00
00BHNSTS-1H/VBBCG20.000.000.0025.00
00BHESTS-1H/VBBCG20.000.0090.0025.00
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As part of the annual calibration process, the USGS runs a sequence that includes a random, a step, and several sine wave calibrations.  The USGS analyzes the random binary calibration signal in order to estimate the instrument response.  The figures below show the results from the analysis of the most recent processed calibration at the station.

We use an iterative three-step method to estimate instrument response parameters (poles, zeros, sensitivity and gain) and their associated errors using random calibration signals. First, we solve a coarse non-linear inverse problem using a least squares grid search to yield a first approximation to the solution. This approach reduces the likelihood of poorly estimated parameters (a local-minimum solution) caused by noise in the calibration records and enhances algorithm convergence. Second, we iteratively solve a non-linear parameter estimation problem to obtain the least squares best-fit Laplace pole/zero/gain model. Third, by applying the central limit theorem we estimate the errors in this pole/zero model by solving the inverse problem at each frequency in a 2/3rds-octave band centered at each best-fit pole/zero frequency. This procedure yields error estimates of the 99% confidence interval.

LocChanCal DateEpoch-SpanGradeAmp Nominal Error (dB)Amp Best Fit Error (dB)Phase Nominal Error (degree)Phase Best Fit Error (degree)SensorCal Type
10BHN2008:168 2008:166 to 2009,211 A0.0290320.0285590.206540.20297 CMG3-TRandom
10BHE2008:168 2008:166 to 2009,211 A0.0341540.0336140.220290.22119 CMG3-TRandom
10BHZ2008:168 2008:166 to 2009,211 A0.0309660.0294880.209020.21044 CMG3-TRandom
  1. Current Issues
    No current communication with site. Station awaiting upgrade.