1 / 16

Least squares collocation in OCCAM 6.3

Least squares collocation in OCCAM 6.3. Oleg Titov (Geoscience Australia). IVS Analysis Workshop Meeting , Shanghai 07 March 2014. 07 September 2013. Data analysis. OCCAM 6.3 – least squares collocation method Using full variance-covariance matrix

ilar
Download Presentation

Least squares collocation in OCCAM 6.3

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Least squares collocation in OCCAM 6.3 Oleg Titov (Geoscience Australia) IVS Analysis Workshop Meeting, Shanghai07 March 2014 07 September 2013

  2. Data analysis • OCCAM 6.3 – least squares collocation method • Using full variance-covariance matrix • Mutual correlation between wet troposphere delays and hydrogen maser variations O. Titov, H. Schuh, IERS Technical Notes 28, 33-41, 2000 O. Titov, Astronomy Reports, 48 (11), 941-948, 2004 Geoscience Australia 06 March 2014

  3. LSM vs LSCM LSMLSCM

  4. The LSCM needs apriori information

  5. The LSCM needs apriori information

  6. OCCAM 6.3 For global solution three-parametrical model is applied for fit; • x – global parameters (source positions); • y – local or ‘arc’ parameters (EOP, daily station coordinates, nutation offsets, etc. • z – stochastic parameters (wet delays, clock offsets).

  7. LSCM

  8. LSCM

  9. LSCM

  10. CONT’05 troposphere

  11. CONT’05 troposphere

  12. Wet troposphere delays (Titov, Stanford, Proc of 21st EVGA Worikng Meeting, Helsinki, 2013) Geoscience Australia 06 March 2014

  13. Wet troposphere delays Mean = -4 mm wrms = 6 mm (Titov, Stanford, Proc of 21st EVGA Wiorkng Meeting, Helsinki, 2013) Geoscience Australia 06 March 2014

  14. OCCAM 6.3 • x – global parameters (source positions); • y – local or ‘arc’ parameters (EOP, daily station coordinates, nutation offsets, etc. • z – stochastic parameters (wet delays, clock offsets). • no stochastic parameters !

  15. Application • SINEX files • Plain LSM for data analysis – no piece-wise linear functions, no Kalmanfiltering, no stochastic models, no collocation! Geoscience Australia 07 September 2013

  16. Thank you for attention! Geoscience Australia 07 September 2013

More Related