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dc.date.accessioned 2019-06-21T19:03:13Z
dc.date.available 2019-06-21T19:03:13Z
dc.date.issued 2015
dc.identifier.uri http://sedici.unlp.edu.ar/handle/10915/76906
dc.description.abstract A novel Bayesian technique for the joint estimation of real and integer parameters in a linear measurement model is presented. The integer parameters take values on a finite set, and the real ones are assumed to be a Gaussian random vector. The posterior distribution of these parameters is sequentially determined as new measurements are incorporated. This is a mixed distribution with a Gaussian continuous part and a discrete one. Estimators for the integer and real parameters are derived from this posterior distribution. A Maximum A Posteriori (MAP) estimator modified with the addition of a confidence threshold is used for the integer part and a Minimum Mean Squared Error (MMSE) is used for the real parameters. Two different cases are addressed: i) both real and integer parameters are time invariant and ii) the integer parameters are time invariant but the real ones are time varying. Our technique is applied to the GNSS carrier phase ambiguity resolution problem, that is key for high precision positioning applications. The good performance of the proposed technique is illustrated through simulations in different scenarios where different kind of measurements as well as different satellite visibility conditions are considered. Comparisons with state-of-the-art ambiguity solving algorithms confirm performance improvement. The new method is shown to be useful not only in the estimation stage but also for validating the estimates ensuring a predefined success rate through proper threshold selection. en
dc.format.extent 923-933 es
dc.language en es
dc.subject Bayesian estimation, carrier phase ambiguity resolution, GNSS, integer parameter estimation en
dc.title A Bayesian Technique for Real and Integer Parameters Estimation in Linear Models and its Application to GNSS High Precision Positioning en
dc.type Articulo es
sedici.identifier.other http://hdl.handle.net/11746/2211
sedici.identifier.other https://doi.org/10.1109/TSP.2015.2500195
sedici.identifier.issn 1053-587X es
sedici.creator.person García, Javier Gonzalo es
sedici.creator.person Roncagliolo, Pedro Agustín es
sedici.creator.person Muravchik, Carlos Horacio es
sedici.subject.materias Ingeniería es
sedici.description.fulltext true es
mods.originInfo.place Facultad de Ingeniería es
sedici.subtype Articulo es
sedici.rights.license Creative Commons Attribution-NoDerivatives 4.0 International (CC BY-ND 4.0)
sedici.rights.uri http://creativecommons.org/licenses/by-nd/4.0/
sedici.description.peerReview peer-review es
sedici.relation.journalTitle IEEE Transactions on Signal Processing es
sedici.relation.journalVolumeAndIssue vol. 64, no. 4 es

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Creative Commons Attribution-NoDerivatives 4.0 International (CC BY-ND 4.0) Except where otherwise noted, this item's license is described as Creative Commons Attribution-NoDerivatives 4.0 International (CC BY-ND 4.0)