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Article: Impacts of BeiDou stochastic model on reliability: overall test, w-test and minimal detectable bias
Title | Impacts of BeiDou stochastic model on reliability: overall test, w-test and minimal detectable bias |
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Authors | |
Keywords | Stochastic model Hypothesis testing w-test GNSS Minimal detectable bias (MDB) Overall test Variance component estimation (VCE) Reliability |
Issue Date | 2017 |
Citation | GPS Solutions, 2017, v. 21, n. 3, p. 1095-1112 How to Cite? |
Abstract | © 2016, Springer-Verlag Berlin Heidelberg. Extensive studies have concluded that the GNSS observations are heteroscedastic and physically correlated. Typically, the observation precisions are elevation dependent and between-frequency cross-correlations and time correlations exist. The influence of these stochastic characteristics on the GNSS positioning has been numerically well understood. However, their influence on the statistic tests of reliability has been rarely studied. We will systematically study the influence of GNSS stochastic characteristics on the statistic tests involved in reliability. With BeiDou as an example, the realistic elevation-dependent model, cross-correlations and time correlations are estimated. Then their impacts on the reliability are numerically analyzed by comparing with the empirical stochastic model where the stochastic characteristics, i.e., elevation-dependent precisions, cross-correlations and time correlations, are not adequately specified. Besides the overall test and w-test, the minimal detectable bias (MDB) and the separability of two w-test statistics are examined. The results show that the realistic elevation-dependent model will reduce probabilities of both false alarm and wrong detection for both overall test and w-test. Introducing the cross-correlations and time correlations properly can obtain the realistic MDBs together with reasonable separability measures, which all are helpful for users to make objective decisions in quality control of real GNSS applications. |
Persistent Identifier | http://hdl.handle.net/10722/266776 |
ISSN | 2023 Impact Factor: 4.5 2023 SCImago Journal Rankings: 1.418 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Li, Bofeng | - |
dc.contributor.author | Zhang, Lei | - |
dc.contributor.author | Verhagen, Sandra | - |
dc.date.accessioned | 2019-01-31T07:19:33Z | - |
dc.date.available | 2019-01-31T07:19:33Z | - |
dc.date.issued | 2017 | - |
dc.identifier.citation | GPS Solutions, 2017, v. 21, n. 3, p. 1095-1112 | - |
dc.identifier.issn | 1080-5370 | - |
dc.identifier.uri | http://hdl.handle.net/10722/266776 | - |
dc.description.abstract | © 2016, Springer-Verlag Berlin Heidelberg. Extensive studies have concluded that the GNSS observations are heteroscedastic and physically correlated. Typically, the observation precisions are elevation dependent and between-frequency cross-correlations and time correlations exist. The influence of these stochastic characteristics on the GNSS positioning has been numerically well understood. However, their influence on the statistic tests of reliability has been rarely studied. We will systematically study the influence of GNSS stochastic characteristics on the statistic tests involved in reliability. With BeiDou as an example, the realistic elevation-dependent model, cross-correlations and time correlations are estimated. Then their impacts on the reliability are numerically analyzed by comparing with the empirical stochastic model where the stochastic characteristics, i.e., elevation-dependent precisions, cross-correlations and time correlations, are not adequately specified. Besides the overall test and w-test, the minimal detectable bias (MDB) and the separability of two w-test statistics are examined. The results show that the realistic elevation-dependent model will reduce probabilities of both false alarm and wrong detection for both overall test and w-test. Introducing the cross-correlations and time correlations properly can obtain the realistic MDBs together with reasonable separability measures, which all are helpful for users to make objective decisions in quality control of real GNSS applications. | - |
dc.language | eng | - |
dc.relation.ispartof | GPS Solutions | - |
dc.subject | Stochastic model | - |
dc.subject | Hypothesis testing | - |
dc.subject | w-test | - |
dc.subject | GNSS | - |
dc.subject | Minimal detectable bias (MDB) | - |
dc.subject | Overall test | - |
dc.subject | Variance component estimation (VCE) | - |
dc.subject | Reliability | - |
dc.title | Impacts of BeiDou stochastic model on reliability: overall test, w-test and minimal detectable bias | - |
dc.type | Article | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1007/s10291-016-0596-z | - |
dc.identifier.scopus | eid_2-s2.0-85007227702 | - |
dc.identifier.volume | 21 | - |
dc.identifier.issue | 3 | - |
dc.identifier.spage | 1095 | - |
dc.identifier.epage | 1112 | - |
dc.identifier.eissn | 1521-1886 | - |
dc.identifier.isi | WOS:000403949500024 | - |
dc.identifier.issnl | 1080-5370 | - |