Smoothing and predicting celestial pole offsets using a Kalman filter and smoother

It has been recognized since the early days of interplanetary spaceflight that accurate navigation requires taking into account changes in the Earth’s rotation. In the 1960s, tracking anomalies during the Ranger VII and VIII lunar missions were traced to errors in the Earth orientation parameters. As a result, Earth orientation calibration methods were improved to support the Mariner IV and V planetary missions. Today, accurate Earth orientation parameters are used to track and navigate every interplanetary spaceflight mission. The approach taken at JPL (Jet Propulsion Laboratory) to provide the interplanetary spacecraft tracking and navigation teams with the UT1 and polar motion parameters that they need is based upon the use of a Kalman filter to combine past measurements of these parameters and predict their future evolution. A model was then used to provide the nutation/precession components of the Earth’s orientation. As a result, variations caused by the free core nutation were not taken into account. But for the highest accuracy, these variations must be considered. So JPL recently developed an approach based upon the use of a Kalman filter and smoother to provide smoothed and predicted celestial pole offsets (CPOs) to the interplanetary spacecraft tracking and navigation teams. The approach used at JPL to do this and an evaluation of the accuracy of the predicted CPOs is given here. For assessing the quality of JPL’s nutation predictions, we compare the time series of dX, dY provided by JPL with the predictions obtained from the IERS Rapid Service/Prediction Centre. Our results confirmed that the approach recently developed by JPL can be used for the successful nutation prediction. In particular, we show that after 90 days of prediction, the estimated errors are 43% lower for dX and 33% lower for dY than in the case of the official IERS products, and an average improvement is 19% and 22% for dX and dY, respectively.

[1]  M. Kalarus,et al.  Achievements of the Earth orientation parameters prediction comparison campaign , 2010 .

[2]  Zinovy Malkin CPO prediction: accuracy assessment and impact on UT1 intensive results , 2010 .

[3]  H. Schuh,et al.  Testing a new Free Core Nutation empirical model , 2016 .

[4]  H. Schuh,et al.  A new method to improve the prediction of the celestial pole offsets , 2018, Scientific Reports.

[5]  C. K. Shum,et al.  Fuzzy-wavelet based prediction of Earth rotation parameters , 2011, Appl. Soft Comput..

[6]  Aleksander Brzeziński,et al.  Influence Of The Atmosphere On Earth Rotation: What New Can Be Learned From The Recent Atmospheric Angular Momentum Estimates? , 2002 .

[7]  Arthur Gelb,et al.  Applied Optimal Estimation , 1974 .

[8]  C. Bizouard,et al.  The Combined Solution C04 for Earth Orientation Parameters Consistent with International Terrestrial Reference Frame 2005 , 2009 .

[9]  E. Kerins,et al.  Estimating the parameters of globular cluster M 30 (NGC 7099) from time-series photometry , 2013, 1305.3606.

[10]  Zinovy Malkin Analysis of the accuracy of prediction of the celestial pole motion , 2010 .

[11]  Jean-Yves Richard,et al.  The IERS EOP 14C04 solution for Earth orientation parameters consistent with ITRF 2014 , 2019, Journal of Geodesy.

[12]  T. M. Eubanks,et al.  The short-term prediction of universal time and length of day using atmospheric angular momentum , 1994 .

[13]  On the accuracy of the theory of precession and nutation , 2014 .

[14]  Xueqing Xu,et al.  Short-term earth orientation parameters predictions by combination of the least-squares, AR model and Kalman filter , 2012 .

[15]  Patricia Te Arapo Wallace SOFA: Standards of Fundamental Astronomy , 1998 .

[16]  Thomas A. Herring,et al.  Modeling of nutation and precession: New nutation series for nonrigid Earth and insights into the Ea , 2002 .

[17]  F. Meysman,et al.  Anthropogenic disturbance keeps the coastal seafloor biogeochemistry in a transient state , 2018, Scientific Reports.

[18]  G. Bierman Factorization methods for discrete sequential estimation , 1977 .

[19]  Harald Schuh,et al.  Prediction of Earth orientation parameters by artificial neural networks , 2002 .

[20]  Yonghong Zhou,et al.  Estimation of the free core nutation period by the sliding-window complex least-squares fit method , 2016 .

[21]  Z. Altamimi,et al.  ITRF2014: A new release of the International Terrestrial Reference Frame modeling nonlinear station motions , 2016 .

[22]  W. Kosek,et al.  Possible improvement of Earth orientation forecast using autocovariance prediction procedures , 1998 .

[23]  C. Bizouard,et al.  Remaining error sources in the nutation at the submilliarc second level , 2003 .

[24]  T. Fukushima,et al.  Construction of a New Forced Nutation Theory of the Nonrigid Earth , 2001 .

[25]  A. Brzezinski,et al.  Free core nutation: stochastic modelling versus predictability , 2004 .

[26]  Forecasting the polar motions of the deformable Earth , 2002 .

[27]  Dennis D. McCarthy,et al.  Prediction of Earth orientation , 1991 .

[28]  Nasser E. Nahi,et al.  Estimation Theory and Applications , 1969 .

[29]  Daniel P. McCarthy,et al.  The free core nutation , 2005 .

[30]  Josep M. Ferrandiz,et al.  Polar motion prediction using the combination of SSA and Copula-based analysis , 2018, Earth, Planets and Space.

[31]  T Artz,et al.  International VLBI Service for Geodesy and Astrometry: Earth orientation parameter combination methodology and quality of the combined products , 2010 .

[32]  M. Kalarus,et al.  Forecasting of the Earth orientation parameters - comparison of different algorithms , 2008 .

[33]  Hozakowski Włodzimierz Polar Motion Prediction by the Least-Squares Collocation Method , 1990 .

[34]  Z. Malkin Joint analysis of celestial pole offset and free core nutation series , 2017, Journal of Geodesy.

[35]  T. M. Chin,et al.  Modeling and forecast of the polar motion excitation functions for short-term polar motion prediction , 2004 .

[36]  Harald Schuh,et al.  Free core nutation observed by VLBI , 2013, 1401.7465.

[37]  Zinovy Malkin,et al.  Empiric models of the Earth’s free core nutation , 2007, 0908.1825.