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Progress in Centralized Monitoring of the International GPS Service Network

This article discusses the progress made in centralized monitoring of the International GPS Service Network, focusing on parameters such as L1 multipath, L2 multipath, number of observations, and slips. The article explores the use of cumulative sum change-point analysis and the detection of outliers in the data. It highlights how this approach can aid in identifying significant changes and patterns in time-series data, assisting operators in making informed decisions.

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Progress in Centralized Monitoring of the International GPS Service Network

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  1. Progress in Centralized Monitoring of the International GPS Service Network Angelyn W. Moore Peter N. Jeziorek Eric W. Richardson Ruth E. Neilan IGS Central Bureau http://igscb.jpl.nasa.gov

  2. 4 quantities from the teqc summary L1 multipath L2 multipath Number of observations Slips (x1000) per observations

  3. Changes in these parameters can be sudden or gradual L1 multipath Slips/obs

  4. Compare value & variance against the rest of the IGS Slips/obs

  5. Change point analysis Cumulative sum of the differences between the values and the mean S0 = 0 S1 = S0 +X1 – Xmean SN = SN-1 + XN - Xmean “Bootstrap” (randomly reorder) the data set and check whether peak of cusum is higher or lower. Repeat a bunch of times. Confidence level of the change point is the fraction of times the bootstrapped set’s cusum is flatter

  6. Outliers? Original data We don’t really want isolated outliers flagged, but we do want significant changes to be found. When outliers are detected, we use the rank of the data point, instead of the value. This decreases the impact of the outliers on the cumulative sum, but real changes are still detected. Same data; ranks instead of values

  7. Someexamples

  8. How are we using this? As a screening tool to decide what a human should look at more closely. We’re gathering data on what patterns in the time series correspond to what kinds of real events. No automatic notification is sent to operators at this time.

  9. Conclusions • I have lots of time-series data to examine • Maybe you do too • The computer can help by making a first pass through the data, using cumulative sum change-point analysis to decide what deserves a closer look from a human.

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