Ambiguity-Resolved Parameter Significance Test
Implementation and Performance for GNSS Model Validation
Chengyu Yin (TU Delft - Civil Engineering & Geosciences)
Peter J.G. Teunissen (Curtin University, TU Delft - Civil Engineering & Geosciences, University of Melbourne)
Christian C.J.M. Tiberius (TU Delft - Civil Engineering & Geosciences)
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Abstract
The theory of the ambiguity-resolved parameter significance (ARs) and ambiguity-resolved parameter normed (ARn) tests has been developed for global navigation satellite system mixed-integer model validation. This contribution describes how to apply these tests and evaluates their performance by analyzing their power as a function of bias magnitude and comparing them with the ambiguity-float (AF) and ambiguity-known significance tests. When testing for blunders in pseudoranges and carrier-phase cycle slips, the ARn and ARs tests perform similarly and generally outperform the AF test. When testing for ionosphere and troposphere delays, the ARs and ARn tests perform differently, and the ARs power function is spiky. We explain this behavior and show the performance of two methods in mitigating reductions in the ARs power function. This contribution demonstrates that the ARs and ARn tests can perform better the AF test, even when the ambiguity resolution success rate is not close to one.
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