Geomagnetic Activity and GPS Anomalies at High Latitudes Adam - - PowerPoint PPT Presentation

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Geomagnetic Activity and GPS Anomalies at High Latitudes Adam - - PowerPoint PPT Presentation

Sep 23, 2023 29 likes •291 views

Geomagnetic Activity and GPS Anomalies at High Latitudes Adam Jacobs Mentor: Rob Steenburgh NOAA SWPC OUTLINE Motivation Motivation Background Data Details Alaskas citizens use GPS for many daily activities Data Processing

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SLIDE 1

Geomagnetic Activity and GPS Anomalies at High Latitudes

Adam Jacobs Mentor: Rob Steenburgh NOAA SWPC

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SLIDE 2

OUTLINE Motivation Background Data Details Data Processing Results/Plots Conclusions Future Work Comments or Questions Jacobs· Steenburgh Colorado REU Presentation · slide 2

  • Alaska’s citizens use GPS for

many daily activities

  • Solar and Geomagnetic activity

effect the accuracy of GPS

  • GPS customers wonder when

they can and can’t rely on GPS positioning (some situations are life threatening)

  • Is there a strong correlation or

predictable relationship?

  • If so--we want to eventually be

able to forecast GPS disruption (timing/magnitude) given certain levels of geomagnetic activity

Motivation

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SLIDE 3

Background Info

OUTLINE Motivation Background

Scintillation Cycle Slips Positioning Error

Data Details Data Processing Results/Plots Conclusions Future Work Comments or Questions Jacobs· Steenburgh Colorado REU Presentation · slide 3

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SLIDE 4

Scintillation

OUTLINE Motivation Background

Scintillation Cycle Slips Positioning Error

Data Details Data Processing Results/Plots Conclusions Future Work Comments or Questions Jacobs· Steenburgh Colorado REU Presentation · slide 4

  • Solar wind and CMEs cause

perturbations in the Earth’s magnetic field

  • These perturbations in turn cause

particle precipitation and complex structure to develop in the ionosphere—especially at high latitudes (top pic)

  • Large gradients in TEC—bubbles and

blobs—disrupt GPS signals (bottom pic)

  • Irregularities cause diffraction and

refraction of the GPS signal which in turn cause phase shifts and amplitude variability respectively

  • Scintillation refers to observed rapid

changes amplitude and phase

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SLIDE 5

GPS Positioning Errors

  • The perturbed ionosphere can

cause unpredictable variations in Total Electron Content

  • These variations can cause

complex signal group (pseudorange) delay

  • Pseudorange—the apparent

distance between the reference station and a satellite using the time for the signal to get there

  • Triangulation of pseudoranges

are used to get the distance OUTLINE Motivation Background

Scintillation Cycle Slips Positioning Error

Data Details Data Processing Results/Plots Conclusions Future Work Questions Jacobs· Steenburgh Colorado REU Presentation · slide 5

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SLIDE 6

GPS Cycle Slips

  • Occur as a result of phase shifts
  • When the phase shift exceeds

the bandwidth of a receiver’s phase lock loop (PLL) the receiver loses lock

  • The duration of loss of lock

determines the number of cycles that will slip by unrecorded(hence cycle-slips)

  • There are several relatively

successful correction methods for cycle slips including polynomial fitting OUTLINE Motivation Background

Scintillation Cycle Slips Positioning Error

Data Details Data Processing Results/Plots Conclusions Future Work Comments or Questions Jacobs· Steenburgh Colorado REU Presentation · slide 6

Numerous cycle slips in the GPS observations create jumps in the time series. (Banville et. al. 2010—Radio Science)

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SLIDE 7

Data Details

OUTLINE Motivation Background Data Details

GPS data Geomagnetic data

Data Processing Results/Plots Conclusions Future Work Questions Jacobs· Steenburgh Colorado REU Presentation · slide 7

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SLIDE 8

GPS Data Used

  • Chose eight Alaska GPS

reference stations

  • Various latitudes to

check for latitude dependence in GPS errors

  • Stations are part of the

Nation Geodetic Survey (NGS) Continuously Operating Reference Stations (CORS) network

OUTLINE Motivation Background Data Details

GPS data Geomagnetic data

Data Processing Results/Plots Conclusions Future Work Questions Jacobs· Steenburgh Colorado REU Presentation · slide 8

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SLIDE 9

Geomagnetic Data Used

  • Used daily A-index data and 3-

hourly K-index data from College, AK

  • K-index—represents the

maximum fluctuations in the horizontal mag. Field components relative to a quiet day, during a three hour interval

  • A-index—daily average of the

eight “equivalent three hourly” (a-index) values which have been converted nonlinearly from the K-index values

OUTLINE Motivation Background Data Details

GPS data Geomagnetic data

Data Processing Results/Plots Conclusions Future Work Questions Jacobs· Steenburgh Colorado REU Presentation · slide 9

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SLIDE 10

Data Processing

  • Started with the daily number of cycle slips from all eight GPS

stations and the A-index at College for 2003 and 2008 (quiet and active years)

  • Examined the temporal and spatial relationships between the two

data sets and calculated correlation coefficients

  • Moved to GPS positioning errors (daily max and median) and

compared these data sets to the A-index

  • Created histograms of position errors
  • Explored higher granularity data (Fairbanks only), specifically

College K-index and three hourly medians for GPS positioning errors

  • Examined relationships, correlations, cross-correlations,

distributions, and seasonal variability (looked at specific events)

OUTLINE Motivation Background Data Details Data Processing Results/Plots Conclusions Future Work Questions Jacobs· Steenburgh Colorado REU Presentation · slide 10

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Results/Plots

OUTLINE Motivation Background Data Details Data Processing Results/Plots

Cycle Slips Position Error

Conclusions Future Work Questions Jacobs· Steenburgh Colorado REU Presentation · slide 11

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Fairbanks Cycle Slip Correlation

OUTLINE Motivation Background Data Details Data Processing Results/Plots

Cycle Slips Daily Corr. 1 Daily Corr. 2 Daily Corr. 3 Position Error

Conclusions Future Work Questions Jacobs· Steenburgh Colorado REU Presentation · slide 12

  • Daily cycle slip count and College A-index data
  • Note excellent correlation
  • Also note the lack of separation between 2003 and 2008
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SLIDE 13

PUO1 Cycle Slip Correlation

OUTLINE Motivation Background Data Details Data Processing Results/Plots

Cycle Slips Daily Corr. 1 Daily Corr. 2 Daily Corr. 3 Position Error

Conclusions Future Work Questions Jacobs· Steenburgh Colorado REU Presentation · slide 13

  • Strong Correlation
  • Excellent separation in years
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SLIDE 14

TSEA Cycle Slip Correlation

OUTLINE Motivation Background Data Details Data Processing Results/Plots Cycle Slips

Daily Corr. 1 Daily Corr. 2 Daily Corr. 3 Position Error

Conclusions Future Work Questions Jacobs· Steenburgh Colorado REU Presentation · slide 14

  • Worst case out of the eight stations
  • This station is located at a lower latitude than

stronger cases

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SLIDE 15

Fairbanks 2003 Time Series

OUTLINE Motivation Background Data Details Data Processing Results/Plots Cycle Slips Position Error Fair TS 2003 2003 Zoom Fair TS 2008 2008 Zoom Fair Corr. 1 Fair Corr. 2 Fair Corr.

Jacobs· Steenburgh Colorado REU Presentation · slide 15

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Fairbanks 2003 Zoom In

OUTLINE Motivation Background Data Details Data Processing Results/Plots Cycle Slips Position Error Fair TS 2003 2003 Zoom Fair TS 2008 2008 Zoom Fair Corr. 1 Fair Corr. 2 Fair Corr.

Jacobs· Steenburgh Colorado REU Presentation · slide 16

  • There doesn’t seem to be an obvious direct
  • r lagged correlation in this data.
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SLIDE 17

Fairbanks 2008 Time Series

OUTLINE Motivation Background Data Details Data Processing Results/Plots Cycle Slips Position Error Fair TS 2003 2003 Zoom Fair TS 2008 2008 Zoom Fair Corr. 1 Fair Corr. 2 Fair Corr.

Jacobs· Steenburgh Colorado REU Presentation · slide 17

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SLIDE 18

Fairbanks 2008 Zoom In

OUTLINE Motivation Background Data Details Data Processing Results/Plots Cycle Slips Position Error Fair TS 2003 2003 Zoom Fair TS 2008 2008 Zoom Fair Corr. 1 Fair Corr. 2 Fair Corr.

Jacobs· Steenburgh Colorado REU Presentation · slide 18

  • Again there are no obvious correlations in

2008

  • Interesting ~5-day periodic structure to GPS

errors though

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SLIDE 19

Fairbanks Daily Max Error Correlation

OUTLINE Motivation Background Data Details Data Processing Results/Plots Cycle Slips Position Error Fair TS 2003 2003 Zoom Fair TS 2008 2008 Zoom Fair Corr. 1 Fair Corr. 2 Fair Corr.

Jacobs· Steenburgh Colorado REU Presentation · slide 19

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SLIDE 20

Fairbanks Daily Median Error Correlation

OUTLINE Motivation Background Data Details Data Processing Results/Plots Cycle Slips Position Error Fair TS 2003 2003 Zoom Fair TS 2008 2008 Zoom Fair Corr. 1 Fair Corr. 2 Fair Corr.

Jacobs· Steenburgh Colorado REU Presentation · slide 20

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SLIDE 21

Fairbanks 3-hourly Median Error Correlation

OUTLINE Motivation Background Data Details Data Processing Results/Plots Cycle Slips Position Error Fair TS 2003 2003 Zoom Fair TS 2008 2008 Zoom Fair Corr. 1 Fair Corr. 2 Fair Corr.

Jacobs· Steenburgh Colorado REU Presentation · slide 21

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SLIDE 22

Fairbanks Histograms

OUTLINE Motivation Background Data Details Data Processing Results/Plots Cycle Slips Position Error Fair TS 2003 2003 Zoom Fair TS 2008 2008 Zoom Fair Corr. 1 Fair Corr. 2 Fair Corr. 3

Jacobs· Steenburgh Colorado REU Presentation · slide 22

  • We were looking for a “circle of trust”

and outer ring to subtract out noise

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SLIDE 23

Conclusions

  • The daily number of GPS cycle slips

in 2003 and 2008 are strongly correlated with the College daily A- index

  • GPS positioning errors —

inconclusive…a strong correlation with daily and 3-hourly geomagnetic indices was not found, but further investigation may yet reveal a relationship

OUTLINE

Motivation Background Data Details Data Processing Results/Plots Conclusions Future Work Questions Jacobs· Steenburgh Colorado REU Presentation · slide 23

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SLIDE 24

Future Work

With Current Data

  • Running Average
  • Weighted K-index
  • Even higher granularity and

interpolation

  • Seasonal Analysis of Lags

With New Data

  • Use of Auroral Oval

Location/Intensity data (POES data)

  • Include an elevation mask

to eliminate multipath

  • Replace (impute) missing

data — when GPS really went haywire

OUTLINE

Motivation Background Data Details Data Processing Results/Plots Conclusions Future Work Questions Jacobs· Steenburgh Colorado REU Presentation · slide 24

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SLIDE 25

Acknowledgments

OUTLINE Motivation Background Data Details Data Processing Results/Plots Conclusions Future Work Questions Jacobs· Steenburgh Colorado REU Presentation · slide 25

SWPC Project Help

  • Mihai Codrescul
  • Tomoko Matsuo
  • Rodney Viereck
  • Kenneth Kehoe
  • Faizan Naqvi
  • Bruce Marshak
  • Russel Henson
  • Robert Masten

Internship Experience

  • Marty Snow
  • Erin Wood
  • Robert Steenburgh
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SLIDE 26

Fairbanks Lag Time Correlations

OUTLINE

Motivation Background Data Details Data Processing Results/Plots Conclusions Future Work Questions Jacobs· Steenburgh Colorado REU Presentation · slide 26

Daily Lags 3-hourly Lags