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Article: Impacts of BeiDou stochastic model on reliability: overall test, w-test and minimal detectable bias

TitleImpacts of BeiDou stochastic model on reliability: overall test, w-test and minimal detectable bias
Authors
KeywordsStochastic model
Hypothesis testing
w-test
GNSS
Minimal detectable bias (MDB)
Overall test
Variance component estimation (VCE)
Reliability
Issue Date2017
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 Identifierhttp://hdl.handle.net/10722/266776
ISSN
2017 Impact Factor: 4.727
2015 SCImago Journal Rankings: 1.300
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorLi, Bofeng-
dc.contributor.authorZhang, Lei-
dc.contributor.authorVerhagen, Sandra-
dc.date.accessioned2019-01-31T07:19:33Z-
dc.date.available2019-01-31T07:19:33Z-
dc.date.issued2017-
dc.identifier.citationGPS Solutions, 2017, v. 21, n. 3, p. 1095-1112-
dc.identifier.issn1080-5370-
dc.identifier.urihttp://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.languageeng-
dc.relation.ispartofGPS Solutions-
dc.subjectStochastic model-
dc.subjectHypothesis testing-
dc.subjectw-test-
dc.subjectGNSS-
dc.subjectMinimal detectable bias (MDB)-
dc.subjectOverall test-
dc.subjectVariance component estimation (VCE)-
dc.subjectReliability-
dc.titleImpacts of BeiDou stochastic model on reliability: overall test, w-test and minimal detectable bias-
dc.typeArticle-
dc.description.natureLink_to_subscribed_fulltext-
dc.identifier.doi10.1007/s10291-016-0596-z-
dc.identifier.scopuseid_2-s2.0-85007227702-
dc.identifier.volume21-
dc.identifier.issue3-
dc.identifier.spage1095-
dc.identifier.epage1112-
dc.identifier.eissn1521-1886-
dc.identifier.isiWOS:000403949500024-

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