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Prediction of Earth Prediction of Earth orientation parameters orientation parameters by artificial neural by artificial neural networks networks Kalarus Maciej and Kosek Wiesław Space Research Centre, Polish Academy of Sciences Annual Seminar of Commission of Satellite Geodesy, EARTH ROTATION AND SATELLITE GEODESY - FROM ASTROMETRY TO GNSS Warsaw, 18-19 September 2003

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Page 1: Prediction of Earth orientation parameters by artificial neural networks Kalarus Maciej and Kosek Wiesław Space Research Centre, Polish Academy of Sciences

Prediction of Earth orientation Prediction of Earth orientation parametersparameters

by artificial neural networksby artificial neural networks

Kalarus Maciej and Kosek Wiesław

Space Research Centre, Polish Academy of Sciences

Annual Seminar of Commission of Satellite Geodesy, EARTH ROTATION AND SATELLITE GEODESY - FROM ASTROMETRY TO GNSS

Warsaw, 18-19 September 2003

Page 2: Prediction of Earth orientation parameters by artificial neural networks Kalarus Maciej and Kosek Wiesław Space Research Centre, Polish Academy of Sciences

In this poster the Neural Network Toolbox version 3.0.1 software of Matlab ver.5.3 was used to predict the IERS EOPC04 x, y pole coordinates data and obtained results were compared to the predictions of the IERS Sub-Bureau for Rapid Service and Prediction.

Page 3: Prediction of Earth orientation parameters by artificial neural networks Kalarus Maciej and Kosek Wiesław Space Research Centre, Polish Academy of Sciences

Prediction of x, y pole coordinates data by combination of the LS extrapolation and Prediction of x, y pole coordinates data by combination of the LS extrapolation and Neural Network predictionNeural Network prediction

x, y LS extrapolation

residuals

Prediction ofx, y

LS extrapolation residuals

LS extrapolation of x, y

Prediction of x, y

Neural Network

x, y EOPC04 pole coordinates

data

x, y LS model

Page 4: Prediction of Earth orientation parameters by artificial neural networks Kalarus Maciej and Kosek Wiesław Space Research Centre, Polish Academy of Sciences

Polar motion modelPolar motion model

linear trend linear trend Chandler oscillation Chandler oscillation annual oscillationannual oscillation

x

Anx

Anx

Anx

Chx

Chx

ChxxtAtAbtatx sinsin

yAn

yAn

yAn

yCh

yCh

yChyy

tAtAbtaty sinsin

-0.20

0.2

00.2

0.4

1960

1965

1970

1975

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1985

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2005

x [arcsec]

Polar motion (IERS)

y [arcsec]

year

s

-0.20

0.2

00.2

0.4

1960

1965

1970

1975

1980

1985

1990

1995

2000

2005

x [arcsec]

Polar motion (Model)

y [arcsec]

year

s

-0.20

0.2

00.2

0.4

1960

1965

1970

1975

1980

1985

1990

1995

2000

2005

x [arcsec]

Residuals

y [arcsec]

year

s

Page 5: Prediction of Earth orientation parameters by artificial neural networks Kalarus Maciej and Kosek Wiesław Space Research Centre, Polish Academy of Sciences

Prediction of the x, y pole coordinates data by combination of the LS extrapolation and the NN prediction

1984 1986 1988 1990 1992 1994 1996 1998 2000 20020

60

120

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360

0 .00

0 .01

0 .02

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1984 1986 1988 1990 1992 1994 1996 1998 2000 2002years

0

60

120

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300

360

day

s in

th

e fu

ture

x

y

Fig. 10. The absolute values of the difference between x, y pole coordinates data and their prediction being the combination of the LS extrapolation and the NN prediction of the LS extrapolation residuals computed at different starting prediction epochs.

Page 6: Prediction of Earth orientation parameters by artificial neural networks Kalarus Maciej and Kosek Wiesław Space Research Centre, Polish Academy of Sciences

0.00 60.00 120.00 180.00 240.00 300.00 360.00days in the future

0.00

0.01

0.02

0.03

arcs

ec

LS+ NN

USNOxy

xy

Fig. 11. The mean prediction error in 1984 - 2003.6 of the x, y pole coordinates data computed from combination of the LS extrapolation and the NN prediction of the LS extrapolation residuals as well as of the IERS Sub-Bureau for Rapid Service and Prediction.

The mean prediction error