# Contribution of Etalon Observation to Earth Rotation Parameters under a New Observation Scenario
## 2 Data and Methods
### Methodology  
The SLR data of the LAGEOS-1/2 and Etalon-1/2 satellites were processed with Bernese GNSS Software 5.2 [33], which was modified by the National Time Service Center (NTSC), Chinese Academy of Sciences (CAS) for SLR data processing. The SLR observations of the LAGEOS-1/2 and Etalon-1/2 satellites were jointly processed at the observation level using a 7-day interval, similar to the standard ASC solutions. According to the principle of SLR observation, the measured range between the corner cubes in the satellite and the reference point on the earth is defined as  
\[P=\rho+\sigma_{trp}+\sigma_{rel}+\sigma_{rb}+\sigma_{com}+\varepsilon \tag{1}\]  
where \(P\) represents observed range between satellite and the receiver, \(\rho\) represents the geometric distance, \(\sigma_{trp}\) is troposphere signal delay, \(\sigma_{rel}\) is the general relativistic correc \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Site ID** & **DOMES** & **Location** & **Country** & **X (m)** & **Y (m)** & **Z (m)** \\ \hline
1868 & 12341S001 & Komsomsolsk-na-Amure & Russia & \(-\)2,948,545.553 & 2,774,312.979 & 4,912,302.412 \\
1873 & 12337S003 & Simeiz & Ukraine & 3,783,902.151 & 2,551,405.114 & 4,441,257.548 \\
1874 & 12309S003 & Mendeleevo & Russia & 2,844,591.622 & 2,161,111.992 & 5,266,356.882 \\
1879 & 12372S001 & Altay & Russia & 543,405.811 & 3,955,302.296 & 4,957,821.036 \\
1884 & 12302S002 & Riga & Latvia & 3,183,895.637 & 1,421,497.208 & 5,322,803.793 \\
1886 & 12373S001 & Arkhyz & Russia & 3,466,773.366 & 3,059,757.881 & 4,381,456.800 \\
1887 & 25603S001 & Baikonur & Kazakhstan & 2,001,873.318 & 3,987,633.388 & 4,542,477.667 \\
1888 & 12350S002 & Svede & Russia & 2,730,138.911 & 1,562,328.755 & 5,529,896.665 \\
1889 & 12351S002 & Zelenchukskya & Russia & 3,451,185.973 & 3,060,335.220 & 4,391,970.306 \\
1891 & 12313S007 & Irkutsk & Russia & \(-\)968,340.229 & 3,794,415.115 & 5,018,178.124 \\
1893 & 12337S006 & Katzively & Ukraine & 3,785,944.345 & 2,550,780.789 & 4,439,461.397 \\
7090 & 50107M001 & Yarragadee & Australia & \(-\)2,389,007.534 & 5,043,329.448 & \(-\)3,078,524.223 \\
7105 & 40451M105 & Greenbelt & America & 1,130,719.438 & \(-\)4,831,350.580 & 3,994,106.573 \\
7110 & 40497M001 & Monument Peak & America & \(-\)2,386,278.627 & \(-\)4,802,353.816 & 3,444,881.772 \\
7124 & 92201M007 & Tahiti & French Polynesia & \(-\)2,546,407.299 & \(-\)3,077,284.309 & \(-\)1,913,813.757 \\
7237 & 21611S001 & Changchun & China & \(-\)2,674,387.081 & 3,757,189.194 & 4,391,508.287 \\
7249 & 21601S004 & Beijing & China & \(-\)2,148,760.760 & 4,426,759.548 & 4,044,509.606 \\
7394 & 23907S002 & Sejong City & Republic of Korea & \(-\)3,110,108.284 & 4,082,170.384 & 3,774,911.853 \\
7407 & 48081S001 & Brasilia & Brazil & 4,119,502.121 & \(-\)4,553,595.202 & \(-\)1,722,855.131 \\
7501 & 30302M003 & Hartebeesthoek & South Africa & 5,085,401.092 & 2,668,330.330 & \(-\)2,768,688.650 \\
7503 & 30301S010 & Hartebeesthoek & South Africa & 5,085,428.440 & 2,668,340.694 & \(-\)2,768,641.399 \\
7810 & 14001S007 & Zimmerwald & Switzerland & 4,331,283.485 & 567,549.979 & 4,633,140.413 \\
7811 & 12205S001 & Borowiec & Poland & 3,738,332.592 & 1,148,246.687 & 5,021,816.135 \\
7819 & 21609S004 & Kunming & China & \(-\)1,281,301.323 & 5,640,724.593 & 2,682,905.687 \\
7821 & 21605S010 & Shanghai & China & \(-\)2,830,744.597 & 4,676,580.229 & 3,275,072.784 \\
7825 & 50119S003 & Mt Stromlo & Australia & \(-\)4,467,064.778 & 2,683,034.887 & \(-\)3,667,007.319 \\
7827 & 14201S045 & Wettzell & Germany & 4,075,530.996 & 931,781.927 & 4,801,620.007 \\
7839 & 11001S002 & Graz & Austria & 4,194,426.293 & 1,162,694.265 & 4,647,246.785 \\
7840 & 13212S001 & Herstmonceux & United Kingdom & 4,033,463.542 & 23,662.700 & 4,924,305.303 \\
7841 & 14106S011 & Potsdam & Germany & 3,800,432.096 & 881,692.172 & 5,029,030.173 \\
7941 & 12734S008 & Matera & Italy & 4,641,978.617 & 1,393,067.723 & 4,133,249.623 \\
8834 & 14201S018 & Wettzell & Germany & 4,075,576.651 & 931,785.679 & 4,801,583.698 \\ \hline \hline \end{tabular}
\end{table}