Global optimization of core station networks for space geodesy: application to the referencing of the SLR EOP with respect to ITRF

Abstract

We apply global optimization in order to optimize the referencing (and consequently the stability) of the Earth Orientation Parameters (EOP) with respect to ITRF2005. These EOP are derived at a daily sampling from SLR data, simultaneously with weekly station positions. The EOP referencing is carried out with minimum constraints applied weekly to the three rotations and over core station networks. Our approach is based on a multi objective genetic algorithm, a particular stochastic global optimization method, the reference system effects being the objectives to minimize. We thus use rigorous criteria for the optimal weekly core station selection. The results evidence an improvement of 10% of the stability for Polar Motion (PM) series in comparison to the results obtained with the network specially designed for EOP referencing by the Analysis Working Group of the International Laser Ranging Service. This improvement of nearly 25 μas represents 50% of the current precision of the IERS 05 C04 PM reference series. We also test the possibility of averaging the weekly networks provided by our algorithm (the Genetically Modified Networks—GMN) over the whole time period. Although the dynamical nature of the GMN is clearly a key point of their success, we can derive such a global mean core network, which could be useful for practical applications regarding EOP referencing. Using this latter core network moreover provides more stable EOP series than the conventional network does.