A Bayesian Technique for Real and Integer Parameters Estimation in Linear Models and its Application to GNSS High Precision Positioning

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 sequentia...

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Detalles Bibliográficos
Autores principales:	García, Javier Gonzalo, Roncagliolo, Pedro Agustín, Muravchik, Carlos Horacio
Formato:	Articulo
Lenguaje:	Inglés
Publicado:	2015
Materias:	Ingeniería Bayesian estimation, carrier phase ambiguity resolution, GNSS, integer parameter estimation
Acceso en línea:	http://sedici.unlp.edu.ar/handle/10915/76906
Aporte de:	SEDICI (UNLP) de Universidad Nacional de La Plata

id	I19-R120-10915-76906
record_format	dspace
institution	Universidad Nacional de La Plata
institution_str	I-19
repository_str	R-120
collection	SEDICI (UNLP)
language	Inglés
topic	Ingeniería Bayesian estimation, carrier phase ambiguity resolution, GNSS, integer parameter estimation
spellingShingle	Ingeniería Bayesian estimation, carrier phase ambiguity resolution, GNSS, integer parameter estimation García, Javier Gonzalo Roncagliolo, Pedro Agustín Muravchik, Carlos Horacio A Bayesian Technique for Real and Integer Parameters Estimation in Linear Models and its Application to GNSS High Precision Positioning
topic_facet	Ingeniería Bayesian estimation, carrier phase ambiguity resolution, GNSS, integer parameter estimation
description	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.
format	Articulo Articulo
author	García, Javier Gonzalo Roncagliolo, Pedro Agustín Muravchik, Carlos Horacio
author_facet	García, Javier Gonzalo Roncagliolo, Pedro Agustín Muravchik, Carlos Horacio
author_sort	García, Javier Gonzalo
title	A Bayesian Technique for Real and Integer Parameters Estimation in Linear Models and its Application to GNSS High Precision Positioning
title_short	A Bayesian Technique for Real and Integer Parameters Estimation in Linear Models and its Application to GNSS High Precision Positioning
title_full	A Bayesian Technique for Real and Integer Parameters Estimation in Linear Models and its Application to GNSS High Precision Positioning
title_fullStr	A Bayesian Technique for Real and Integer Parameters Estimation in Linear Models and its Application to GNSS High Precision Positioning
title_full_unstemmed	A Bayesian Technique for Real and Integer Parameters Estimation in Linear Models and its Application to GNSS High Precision Positioning
title_sort	bayesian technique for real and integer parameters estimation in linear models and its application to gnss high precision positioning
publishDate	2015
url	http://sedici.unlp.edu.ar/handle/10915/76906
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A Bayesian Technique for Real and Integer Parameters Estimation in Linear Models and its Application to GNSS High Precision Positioning

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