DIA-datasnooping and identifiability

Zaminpardaz, S and Teunissen, P 2018, 'DIA-datasnooping and identifiability', Journal of Geodesy, pp. 1-17.


Document type: Journal Article
Collection: Journal Articles

Title DIA-datasnooping and identifiability
Author(s) Zaminpardaz, S
Teunissen, P
Year 2018
Journal name Journal of Geodesy
Start page 1
End page 17
Total pages 17
Publisher Springer
Abstract In this contribution, we present and analyze datasnooping in the context of the DIA method. As the DIA method for the detection, identification and adaptation of mismodelling errors is concerned with estimation and testing, it is the combination of both that needs to be considered. This combination is rigorously captured by the DIA estimator. We discuss and analyze the DIA-datasnooping decision probabilities and the construction of the corresponding partitioning of misclosure space. We also investigate the circumstances under which two or more hypotheses are nonseparable in the identification step. By means of a theorem on the equivalence between the nonseparability of hypotheses and the inestimability of parameters, we demonstrate that one can forget about adapting the parameter vector for hypotheses that are nonseparable. However, as this concerns the complete vector and not necessarily functions of it, we also show that parameter functions may exist for which adaptation is still possible. It is shown how this adaptation looks like and how it changes the structure of the DIA estimator. To demonstrate the performance of the various elements of DIA-datasnooping, we apply the theory to some selected examples. We analyze how geometry changes in the measurement setup affect the testing procedure, by studying their partitioning of misclosure space, the decision probabilities and the minimal detectable and identifiable biases. The difference between these two minimal biases is highlighted by showing the difference between their corresponding contributing factors. We also show that if two alternative hypotheses, say (Formula presented.) and (Formula presented.), are nonseparable, the testing procedure may have different levels of sensitivity to (Formula presented.)-biases compared to the same (Formula presented.)-biases.
Subject Navigation and Position Fixing
Geomatic Engineering not elsewhere classified
Keyword(s) Datasnooping
Detection
identification and adaptation (DIA)
DIA estimator
Minimal detectable bias (MDB)
Minimal identifiable bias (MIB)
Misclosure space partitioning
Nonseparable hypotheses
Probability of correct identification
DOI - identifier 10.1007/s00190-018-1141-3
Copyright notice © 2018 The Author(s)
ISSN 0949-7714
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