Robustness of GNSS integer ambiguity resolution in the presence of atmospheric biases
Both the underlying model strength and biases are two crucial factors for successful integer GNSS ambiguity resolution (AR) in real applications. In some cases, the biases can be adequately parameterized and an unbiased model can be formulated. However, such parameterization will, as trade-off, redu...
| Main Authors: | , , |
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| Format: | Journal Article |
| Published: |
Springer
2014
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| Online Access: | http://hdl.handle.net/20.500.11937/23712 |
| _version_ | 1848751226238271488 |
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| author | Li, Bofeng Verhagen, S. Teunissen, Peter |
| author_facet | Li, Bofeng Verhagen, S. Teunissen, Peter |
| author_sort | Li, Bofeng |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | Both the underlying model strength and biases are two crucial factors for successful integer GNSS ambiguity resolution (AR) in real applications. In some cases, the biases can be adequately parameterized and an unbiased model can be formulated. However, such parameterization will, as trade-off, reduce the model strength as compared to the model in which the biases are ignored. The AR performance with the biased model may therefore be better than with the unbiased model, if the biases are sufficiently small. This would allow for faster AR using the biased model, after which the unbiased model can be used to estimate the remaining unknown parameters. We assess the bias-affected AR performance in the presence of tropospheric and ionospheric biases and compare it with the unbiased case. As a result, the maximum allowable biases are identified for different situations where CORS, static and kinematic baseline models are considered with different model settings. Depending on the size of the maximum allowable bias, a user may decide to use the biased model for AR or to use the unbiased model both for AR and estimating the other unknown parameters. |
| first_indexed | 2025-11-14T07:49:21Z |
| format | Journal Article |
| id | curtin-20.500.11937-23712 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T07:49:21Z |
| publishDate | 2014 |
| publisher | Springer |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-237122017-09-13T13:59:40Z Robustness of GNSS integer ambiguity resolution in the presence of atmospheric biases Li, Bofeng Verhagen, S. Teunissen, Peter Ambiguity resolution Tropospheric biases Ps-LAMBDA Ionospheric biases Bias-affected success rate Both the underlying model strength and biases are two crucial factors for successful integer GNSS ambiguity resolution (AR) in real applications. In some cases, the biases can be adequately parameterized and an unbiased model can be formulated. However, such parameterization will, as trade-off, reduce the model strength as compared to the model in which the biases are ignored. The AR performance with the biased model may therefore be better than with the unbiased model, if the biases are sufficiently small. This would allow for faster AR using the biased model, after which the unbiased model can be used to estimate the remaining unknown parameters. We assess the bias-affected AR performance in the presence of tropospheric and ionospheric biases and compare it with the unbiased case. As a result, the maximum allowable biases are identified for different situations where CORS, static and kinematic baseline models are considered with different model settings. Depending on the size of the maximum allowable bias, a user may decide to use the biased model for AR or to use the unbiased model both for AR and estimating the other unknown parameters. 2014 Journal Article http://hdl.handle.net/20.500.11937/23712 10.1007/s10291-013-0329-5 Springer restricted |
| spellingShingle | Ambiguity resolution Tropospheric biases Ps-LAMBDA Ionospheric biases Bias-affected success rate Li, Bofeng Verhagen, S. Teunissen, Peter Robustness of GNSS integer ambiguity resolution in the presence of atmospheric biases |
| title | Robustness of GNSS integer ambiguity resolution in the presence of atmospheric biases |
| title_full | Robustness of GNSS integer ambiguity resolution in the presence of atmospheric biases |
| title_fullStr | Robustness of GNSS integer ambiguity resolution in the presence of atmospheric biases |
| title_full_unstemmed | Robustness of GNSS integer ambiguity resolution in the presence of atmospheric biases |
| title_short | Robustness of GNSS integer ambiguity resolution in the presence of atmospheric biases |
| title_sort | robustness of gnss integer ambiguity resolution in the presence of atmospheric biases |
| topic | Ambiguity resolution Tropospheric biases Ps-LAMBDA Ionospheric biases Bias-affected success rate |
| url | http://hdl.handle.net/20.500.11937/23712 |