On the probability density function of the GNSS ambiguity residuals
Integer GNSS ambiguity resolution involves estimation and validation of the unknown integer carrier phase ambiguities. A problem then is that the classical theory of linear estimation does not apply to the integer GPS model, and hence rigorous validation is not possible when use is made of the class...
| Main Authors: | , |
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| Format: | Journal Article |
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John Wiley and Sons, Inc.
2006
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| Online Access: | http://hdl.handle.net/20.500.11937/30000 |
| _version_ | 1848752961610579968 |
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| author | Verhagen, S. Teunissen, Peter |
| author_facet | Verhagen, S. Teunissen, Peter |
| author_sort | Verhagen, S. |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | Integer GNSS ambiguity resolution involves estimation and validation of the unknown integer carrier phase ambiguities. A problem then is that the classical theory of linear estimation does not apply to the integer GPS model, and hence rigorous validation is not possible when use is made of the classical results. As with the classical theory, a first step for being able to validate the integer GPS model is to make use of the residuals and their probabilistic properties. The residuals quantify the inconsistency between data and model, while their probabilistic properties can be used to measure the significance of the inconsistency. Existing validation methods are often based on incorrect assumptions with respect to the probabilistic properties of the parameters involved. In this contribution we will present and evaluate the joint probability density function (PDF) of the multivariate integer GPS carrier phase ambiguity residuals. The residuals and their properties depend on the integer estimation principle used. Since it is known that the integer least-squares estimator is the optimal choice from the class of admissible integer estimators, we will only focus on the PDF of the ambiguity residuals for this estimator. Unfortunately the PDF cannot be evaluated exactly. It will therefore be shown how to obtain a good approximation. The evaluation will be completed by some examples. |
| first_indexed | 2025-11-14T08:16:56Z |
| format | Journal Article |
| id | curtin-20.500.11937-30000 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T08:16:56Z |
| publishDate | 2006 |
| publisher | John Wiley and Sons, Inc. |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-300002017-09-13T15:53:16Z On the probability density function of the GNSS ambiguity residuals Verhagen, S. Teunissen, Peter GNSS residuals Integer GNSS ambiguity resolution involves estimation and validation of the unknown integer carrier phase ambiguities. A problem then is that the classical theory of linear estimation does not apply to the integer GPS model, and hence rigorous validation is not possible when use is made of the classical results. As with the classical theory, a first step for being able to validate the integer GPS model is to make use of the residuals and their probabilistic properties. The residuals quantify the inconsistency between data and model, while their probabilistic properties can be used to measure the significance of the inconsistency. Existing validation methods are often based on incorrect assumptions with respect to the probabilistic properties of the parameters involved. In this contribution we will present and evaluate the joint probability density function (PDF) of the multivariate integer GPS carrier phase ambiguity residuals. The residuals and their properties depend on the integer estimation principle used. Since it is known that the integer least-squares estimator is the optimal choice from the class of admissible integer estimators, we will only focus on the PDF of the ambiguity residuals for this estimator. Unfortunately the PDF cannot be evaluated exactly. It will therefore be shown how to obtain a good approximation. The evaluation will be completed by some examples. 2006 Journal Article http://hdl.handle.net/20.500.11937/30000 10.1007/s10291-005-0148-4 John Wiley and Sons, Inc. fulltext |
| spellingShingle | GNSS residuals Verhagen, S. Teunissen, Peter On the probability density function of the GNSS ambiguity residuals |
| title | On the probability density function of the GNSS ambiguity residuals |
| title_full | On the probability density function of the GNSS ambiguity residuals |
| title_fullStr | On the probability density function of the GNSS ambiguity residuals |
| title_full_unstemmed | On the probability density function of the GNSS ambiguity residuals |
| title_short | On the probability density function of the GNSS ambiguity residuals |
| title_sort | on the probability density function of the gnss ambiguity residuals |
| topic | GNSS residuals |
| url | http://hdl.handle.net/20.500.11937/30000 |