The research is based on the double difference observations and semi-parametric model. Systematic errors are considered as the parameters to be estimated, and brought into the GPS observation equations. High precision baselines are obtained after separating systematic errors. The crucial steps are choosing regularizer and regularization parameters in processing GPS systematic errors by using the semi-parametric model. We propose a new regularizer and apply it to dealing with systematic errors. Also, we compare it with one proposed by other researchers. This comparison is done when all the regularization parameters equal to one. The computation result of the example shows that two regularizers correspond well and they can separate systematic errors successfully. Thus, we can get high precision baselines. Compared with R=QK-1Q′, our regularizer R=GTG is simple, so, the process of resolving the high precision baselines is relatively simple.
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机译:Comparison of methods for measuring and assessing carbon stocks and carbon stock changes in terrestrial carbon pools. How do the accuracy and precision of current methods compare? a systematic review protocol