Seismic Network Operations

US KSU1

Kansas State University--Konza Prairie, Kansas, USA

US KSU1 commences operations on: 2003,148

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Host:
Latitude: 39.101
Longitude: -96.609
Elevation: 317
Datalogger: Q330
Broadband: CMG3TB
Accelerometer: EST-S4G
Telemetry Status at the NEIC: Last Data In Less Than 10 Minutes
Station Photo Station Photo Station Photo Station Photo 
Location CodeChannel CodeInstrumentFlagsSample RateDipAzimuthDepth
00LH1TRILLIUM 120 PHCG1.000.0038.0030.50
00BH1TRILLIUM 120 PHCG40.000.0038.0030.50
00LH2TRILLIUM 120 PHCG1.000.00128.0030.50
00LHZTRILLIUM 120 PHCG1.00-90.000.0030.50
00BH2TRILLIUM 120 PHCG40.000.00128.0030.50
00BHZTRILLIUM 120 PHCG40.00-90.000.0030.50
00VH1TRILLIUM 120 PHCG0.100.0038.0030.50
00VH2TRILLIUM 120 PHCG0.100.00128.0030.50
00VHZTRILLIUM 120 PHCG0.10-90.000.0030.50
10LH1STS2-IHGCG1.000.000.000.00
10LH2STS2-IHGCG1.000.0090.000.00
10LHZSTS2-IHGCG1.00-90.000.000.00
10BH1STS2-IHGCG40.000.000.000.00
10BH2STS2-IHGCG40.000.0090.000.00
10BHZSTS2-IHGCG40.00-90.000.000.00
10VH1STS2-IHGCG0.100.000.000.00
10VH2STS2-IHGCG0.100.0090.000.00
10VHZSTS2-IHGCG0.10-90.000.000.00
20LNZEST-S4GCG1.00-90.000.000.00
20LN1EST-S4GCG1.000.000.000.00
20HN2EST-S4GTG200.000.0090.000.00
20HNZEST-S4GTG200.00-90.000.000.00
20HN1EST-S4GTG200.000.000.000.00
20LN2EST-S4GCG1.000.0090.000.00
30LDOMICROBAROGRAPHCG1.000.000.000.00
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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
00BHZ2013:1512012:138 to No Ending TimeA0.0919460.021480.63910.59506CMG3Random
00BH22013:1512013:073 to No Ending TimeA0.00886220.00784280.0896530.078812CMG3Random
00BH12013:1512013:073 to No Ending TimeA0.00995140.0118220.0961640.073276CMG3Random
  1. Current Issues.
    The steel cable on the KS-54000 is broken and the sensor is not operational at this time. The primary sensor (a CMG3TB) is operational but has high LP noise. A station maintenance trip is scheduled.
  2. 2012-05-16
    Noisy Episensor was replaced. The CMG3T was replaced to address pulsing present since early 2011.
  3. 2006-06-01
    Upgraded to Q330 digitizer.