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Efficient estimation of variance and covariance components : A case study for GPS stochastic model evaluation / B. Li in IEEE Transactions on geoscience and remote sensing, vol 49 n° 1 Tome 1 (January 2011)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 49 n° 1 Tome 1 (January 2011) . - pp 203 - 210 Titre : Efficient estimation of variance and covariance components : A case study for GPS stochastic model evaluation Type de document : Article/Communication Auteurs : B. Li, Auteur ; Y. Shen, Auteur ; L. Lou, Auteur Année de publication : 2011 Conférence : IGARSS 2009, International Geoscience And Remote Sensing Symposium 12/07/2009 17/07/2009 Le Cap Afrique du sud Proceedings IEEE Article en page(s) : pp 203 - 210 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie spatiale [Termes IGN] covariance [Termes IGN] matrice de covariance [Termes IGN] modèle stochastique [Termes IGN] positionnement par GPS [Termes IGN] variance Résumé : (Auteur) The variance and covariance component estimation (VCE) has been extensively investigated. However, in real application, the bottleneck problem is the huge computation burden, particularly when many variance and covariance components are involved for many heterogeneous observations. The objective of this paper is to develop a new method allowing the efficient estimation of variance and covariance components. The core of the new method is to construct an orthogonal complement matrix of the coefficient matrix in a Gauss-Markov model using only the coefficient matrix itself. Therefore, the constructed matrix and the computed discrepancies of measurements with each other, which are the essential inputs for the VCE, are invariant in the iterative procedure of computing the variance and covariance components. As a result, the computation efficiency is significantly improved. As a case study, we apply the new method to evaluate the GPS stochastic model with 15 variance and covariance components demonstrating its superior performance. Comparing with the traditional VCE method, the equivalent results are achievable, and the computation efficiency is improved by 34.2%. In the future, much more sensors will be available, and plentiful data can be acquired. Therefore, the new method will be very promising to efficiently estimate the variance and covariance components of the measurements from the different sensors and reasonably balance their contributions to the fused solution, benefiting the higher time-resolution solutions. Numéro de notice : A2011-049 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2010.2054100 Date de publication en ligne : 12/08/2010 En ligne : https://doi.org/10.1109/TGRS.2010.2054100 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=30830 [article]

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