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Asteroids orbit determination using INPOP19a adjusted on GAIA observations: strategy and validation.

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Since December 2013, the GAIA spacecraft (ESA) is observing the sky with an unprecedented accuracy. Gaia DR2, released in April 2018, contains the position and epoch of 14099 known solar system objects (SSOs) representing more than 2 million observations collected during the first 22 months of operation. In this presentation, we used the new released INPOP19a planetary ephemerides to perform their orbital adjustment and compare them to radar and optical ground-based observations. In order to reduce the time of computation and in anticipation of the huge amount of datas expected with future DR3, a specific solving strategy for the normal equations of the Gauss-Newton algorithm is presented, making the best use of the model design. We obtain post-fit residuals that are closed to the expected performance of GAIA and overall consistent with the values announced by the DR2 reference orbit determination (see Gaia Collaboration et al 2018). In order to disccus the reliability of the obtained orbits, a combination with radar and optical ground based observations was performed for 23 objects using two different numerical methods: a systematic exploration of the weighting scheme coupled with a residual post-fit analysis, and a Least Square Variance Component Estimation adjustment algorithm (LSVCE). Such methods can be extended to all inverse problems within the framework of least-square formalism.
Title: Asteroids orbit determination using INPOP19a adjusted on GAIA observations: strategy and validation.
Description:
Since December 2013, the GAIA spacecraft (ESA) is observing the sky with an unprecedented accuracy.
Gaia DR2, released in April 2018, contains the position and epoch of 14099 known solar system objects (SSOs) representing more than 2 million observations collected during the first 22 months of operation.
In this presentation, we used the new released INPOP19a planetary ephemerides to perform their orbital adjustment and compare them to radar and optical ground-based observations.
In order to reduce the time of computation and in anticipation of the huge amount of datas expected with future DR3, a specific solving strategy for the normal equations of the Gauss-Newton algorithm is presented, making the best use of the model design.
We obtain post-fit residuals that are closed to the expected performance of GAIA and overall consistent with the values announced by the DR2 reference orbit determination (see Gaia Collaboration et al 2018).
In order to disccus the reliability of the obtained orbits, a combination with radar and optical ground based observations was performed for 23 objects using two different numerical methods: a systematic exploration of the weighting scheme coupled with a residual post-fit analysis, and a Least Square Variance Component Estimation adjustment algorithm (LSVCE).
Such methods can be extended to all inverse problems within the framework of least-square formalism.

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