首页|Inversion and characteristics of unmodeled errors in GNSS relative positioning
Inversion and characteristics of unmodeled errors in GNSS relative positioning
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NSTL
Elsevier
Unmodeled errors in the global navigation satellite system (GNSS) observation equations are inevitable and have an impact on parameter estimation accuracy. In this study, we focus on inverting unmodeled errors in relative positioning and analyse their characteristics to provide a theoretical foundation for processing. First, we present an inversion method for unmodeled errors and demonstrate its effectiveness using an example. Then, we systematically examine the characteristics of unmodeled errors. The findings indicate that (1) the unmodeled errors in the short baselines are eliminated more effectively, whereas the unmodeled errors in the long baselines are more significant and unpredictable; (2) the long-term components (200-2500 epochs) in unmodeled errors are significant, but the short-term components (below 100 epochs) are not; and (3) unmodeled errors between L1 and L2 frequencies have a clear correlation, with the correlation coefficient being & GE; 75%. Finally, we prove that atmospheric delays are the primary source of unmodeled errors in long baselines.
NSTL
Elsevier
