Applied Mathematics and Computer Science, Klimis Ntalianis (edt), AIP, Melville, New York, 1836(1) (2017), 020084-1–020084-5 http://doi.org/10.1063/1.4982024

One of the major challenges in processing high-accurate long baselines is the presence of un-modelled ionospheric and tropospheric delays. There are effective mitigation strategies for ionospheric biases, such as the ionosphere-free linear combination of L1 and L2 carrier-phase, which can remove about 98% of the first-order ionospheric biases. With few exceptions this was the solution found by LGO for the 11760 baselines processed in this research. Therefore, for successful results, the appropriated approach to the mitigation of biases due to tropospheric delays is vital. The main aim of the investigations presented in this work was to evaluate the improvements, or not, of the rate of baselines successfully produced by adopting an advanced tropospheric bias mitigation strategy as opposed to a sample tropospheric bias mitigation approach. In both cases LGO uses as a priori tropospheric model the simplified Hopfield model, improved in the first case with a zenith tropospheric scale factor per station. Being aware that 1D and 2D present different behaviors, both cases are analyzed individually with each strategy.

CEMAT - Center for Computational and Stochastic Mathematics