A new ambiguity acceptance test threshold determination method with controllable failure rate
Author(s) -
Lei Wang,
Sandra Verhagen
Publication year - 2014
Publication title -
journal of geodesy
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.78
H-Index - 95
eISSN - 1432-1394
pISSN - 0949-7714
DOI - 10.1007/s00190-014-0780-2
Subject(s) - function (biology) , computer science , algorithm , integer (computer science) , threshold model , ambiguity , mathematical optimization , mathematics , statistics , evolutionary biology , biology , programming language
The ambiguity acceptance test is an important quality control procedure in high precision GNSS data processing. Although the ambiguity acceptance test methods have been extensively investigated, its threshold determine method is still not well understood. Currently, the threshold is determined with the empirical approach or the fixed failure rate (FF-) approach. The empirical approach is simple but lacking in theoretical basis, while the FF-approach is theoretical rigorous but computationally demanding. Hence, the key of the threshold determination problem is how to efficiently determine the threshold in a reasonable way. In this study, a new threshold determination method named threshold function method is proposed to reduce the complexity of the FF-approach. The threshold function method simplifies the FF-approach by a modeling procedure and an approximation procedure. The modeling procedure uses a rational function model to describe the relationship between the FF-difference test threshold and the integer least-squares (ILS) success rate. The approximation procedure replaces the ILS success rate with the easy-to-calculate integer bootstrapping (IB) success rate. Corresponding modeling error and approximation error are analysed with simulation data to avoid nuisance biases and unrealistic stochastic model impact. The results indicate the proposed method can greatly simplify the FF-approach without introducing significant modeling error. The threshold function method makes the fixed failure rate threshold determination method feasible for real-time applications
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