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Airborne LaCoste & Romberg gravimetry: a space domain approach / M. Abbasi in Journal of geodesy, vol 81 n° 4 (April 2007)
[article]
Titre : Airborne LaCoste & Romberg gravimetry: a space domain approach Type de document : Article/Communication Auteurs : M. Abbasi, Auteur ; Jean-Pierre Barriot, Auteur ; Jérome Verdun , Auteur Année de publication : 2007 Article en page(s) : pp 269 - 283 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie physique
[Termes IGN] équation différentielle
[Termes IGN] équation intégrale
[Termes IGN] filtre passe-bas
[Termes IGN] gravimétrie aérienne
[Termes IGN] levé gravimétrique
[Termes IGN] matrice de covariance
[Termes IGN] méthode des moindres carrés
[Termes IGN] modèle de géopotentielRésumé : (Auteur) This paper introduces a new approach to reduce the airborne gravity data acquired by a LaCoste & Romberg (L&R) air/sea gravimeter, or other similar gravimeters. The acceleration exerted on the gravimeter is the sum of gravity and the vertical and Eötvös accelerations of the aircraft. The L&R gravimeter outputs are: (1) the beam position, (2) the spring tension and (3) the cross coupling. Vertical and Eötvös accelerations are computed from GPS-derived aircraft positions. However, the vertical perturbing acceleration sensed by the gravimeter is not the same as the one sensed by the aircraft (via GPS). A determination of the aircraft-to-sensor transfer function is necessary. The second-order differential equation of the motion of the gravimeter’s beam mixes all the input and output parameters of the gravimeter. Conventionally, low-pass filtering in the frequency domain is used to extract the gravity signal, the filter being applied to each flight-line individually. By transforming the differential equation into an integral equation and by introducing related covariance matrices, we develop a new filtering method based on a least-squares approach that is able to take into account, in one stage, the data corresponding to all flight-lines. The a posteriori covariance matrix of the estimated gravity signal is an internal criterion of the precision of the method. As an example, we estimate the gravity values along the flight-lines from an airborne gravity survey over the Alps and introduce an a priori covariance matrix of the gravity disturbances from a global geopotential model. This matrix is used to regularize the ill-posed Fredholm integral equation introduced in this paper. Copyright Springer Numéro de notice : A2007-187 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s00190-006-0107-z En ligne : https://doi.org/10.1007/s00190-006-0107-z Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28550
in Journal of geodesy > vol 81 n° 4 (April 2007) . - pp 269 - 283[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 266-07041 RAB Revue Centre de documentation En réserve L003 Disponible 266-07042 RAB Revue Centre de documentation En réserve L003 Disponible An integrated approach for modelling and global registration of point clouds / T. Rabbani in ISPRS Journal of photogrammetry and remote sensing, vol 61 n° 6 (February 2007)
[article]
Titre : An integrated approach for modelling and global registration of point clouds Type de document : Article/Communication Auteurs : T. Rabbani, Auteur ; S. Dijkam, Auteur ; et al., Auteur Année de publication : 2007 Article en page(s) : pp 355 - 370 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] base de connaissances
[Termes IGN] bâtiment industriel
[Termes IGN] données laser
[Termes IGN] jeu de données localisées
[Termes IGN] lasergrammétrie
[Termes IGN] matrice de covariance
[Termes IGN] méthode des moindres carrés
[Termes IGN] modélisation 3D
[Termes IGN] reconstruction 3D du bâti
[Termes IGN] semis de points
[Termes IGN] superposition de données
[Termes IGN] transformation de coordonnéesRésumé : (Auteur) Point cloud acquisition by using laser scanners provides an efficient way for 3D as-built modelling of industrial installations. Covering such an installation with point cloud data often requires data acquisition from multiple standpoints. Before the actual modelling can start the transformation parameters of all scans need to be determined. Two methods to register point clouds of industrial scenes with different coordinate definitions are presented. Corresponding object models in different scans are used to determine the translation and rotation parameters of the scans. The first method, called Indirect method, is a two-step approach as object fitting and registration of the scenes is done separately. The second method, called Direct method simultaneously determines the shape and pose parameters of the objects as well as the registration parameters. Both methods are designed such that optimal use can be made of the knowledge of shapes present in industrial environments. Compared to ICP the presented approach combines registration and modelling and thus avoids the accumulation of errors. Furthermore, the simultaneous registration of multiple scans is possible. The presented approaches are based on non-linear least squares and provide quality measures in the form of covariance matrix of the estimated parameters, which can be used to decide if more scans are needed, and how and where they should be captured. Results are presented on some point cloud data-sets from actual industrial sites, where registration was done without using any artificial targets. Copyright ISPRS Numéro de notice : A2007-063 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2006.09.006 En ligne : https://doi.org/10.1016/j.isprsjprs.2006.09.006 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28428
in ISPRS Journal of photogrammetry and remote sensing > vol 61 n° 6 (February 2007) . - pp 355 - 370[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-07021 SL Revue Centre de documentation Revues en salle Disponible Building facade interpretation from uncalibrated wide-baseline image sequences / Helmut Mayer in ISPRS Journal of photogrammetry and remote sensing, vol 61 n° 6 (February 2007)
[article]
Titre : Building facade interpretation from uncalibrated wide-baseline image sequences Type de document : Article/Communication Auteurs : Helmut Mayer, Auteur ; S. Reznik, Auteur Année de publication : 2007 Article en page(s) : pp 371 - 380 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] apprentissage dirigé
[Termes IGN] bâtiment
[Termes IGN] chaîne de Markov
[Termes IGN] façade
[Termes IGN] interprétation automatique
[Termes IGN] mesure géométrique
[Termes IGN] méthode de Monte-Carlo
[Termes IGN] méthode des moindres carrés
[Termes IGN] méthode robuste
[Termes IGN] morphologie mathématique
[Termes IGN] photogrammétrie terrestre
[Termes IGN] reconstruction 3D du bâtiRésumé : (Auteur) We propose an approach for building facade interpretation ranging from uncalibrated wide-baseline image sequences to the extraction of windows. The approach comprises several novel features, such as determination of the facade planes by robust least squares matching, learning of implicit shape models for objects, particularly windows, and the determination of the latter by means of Markov Chain Monte Carlo (MCMC) employing an abstraction hierarchy generated via mathematical morphology. Results for the fully automatic approach show its potential and shortcomings. Copyright ISPRS Numéro de notice : A2007-064 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2006.10.007 En ligne : https://doi.org/10.1016/j.isprsjprs.2006.10.007 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28429
in ISPRS Journal of photogrammetry and remote sensing > vol 61 n° 6 (February 2007) . - pp 371 - 380[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-07021 SL Revue Centre de documentation Revues en salle Disponible Efficiency of carrier-phase integer ambiguity resolution for precise GPS positioning in noisy environments / L. Zhu in Journal of geodesy, vol 81 n° 2 (February 2007)
[article]
Titre : Efficiency of carrier-phase integer ambiguity resolution for precise GPS positioning in noisy environments Type de document : Article/Communication Auteurs : L. Zhu, Auteur ; Y.C. Lai, Auteur ; M. Shah, Auteur ; et al., Auteur Année de publication : 2007 Article en page(s) : pp 149 - 156 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie spatiale
[Termes IGN] ambiguïté entière
[Termes IGN] brouillage
[Termes IGN] bruit (théorie du signal)
[Termes IGN] méthode des moindres carrés
[Termes IGN] phase GPS
[Termes IGN] positionnement par GPS
[Termes IGN] résolution d'ambiguïtéRésumé : (Auteur) Precise GPS positioning relies on tracking the carrier-phase. The fractional part of carrier-phase can be measured directly using a standard phase-locked loop, but the integer part is ambiguous and the ambiguity must be resolved based on sequential carrier-phase measurements to ensure the required positioning precision. In the presence of large phase-measurement noise, as can be expected in a jamming environment for example, the amount of data required to resolve the integer ambiguity can be large, which requires a long time for any generic integer parameter estimation algorithm to converge. A key question of interest in significant applications of GPS where fast and accurate positioning is desired is then how the convergence time depends on the noise amplitude. Here we address this question by investigating integer least-squares estimation algorithms. Our theoretical derivation and numerical experiments indicate that the convergence time increases linearly with the noise variance, suggesting a less stringent requirement for the convergence time than intuitively expected, even in a jamming environment where the phase noise amplitude is large. This finding can be useful for practical design of GPS-based systems in a jamming environment, for which the ambiguity resolution time for precise positioning may be critical. Copyright Springer Numéro de notice : A2007-048 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s00190-006-0096-y En ligne : https://doi.org/10.1007/s00190-006-0096-y Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28413
in Journal of geodesy > vol 81 n° 2 (February 2007) . - pp 149 - 156[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 266-07021 RAB Revue Centre de documentation En réserve L003 Disponible 266-07022 RAB Revue Centre de documentation En réserve L003 Disponible
Titre : Least-square variance component estimation : Theory and GPS applications Type de document : Thèse/HDR Auteurs : Ali Reza Amiri-Simkooei, Auteur Editeur : Delft : Netherlands Geodetic Commission NGC Année de publication : 2007 Collection : Netherlands Geodetic Commission Publications on Geodesy, ISSN 0165-1706 num. 64 Importance : 208 p. Format : 17 x 24 cm ISBN/ISSN/EAN : 978-90-6132-301-3 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie spatiale
[Termes IGN] analyse de variance
[Termes IGN] analyse multivariée
[Termes IGN] bruit blanc
[Termes IGN] bruit rose
[Termes IGN] coordonnées GPS
[Termes IGN] estimation statistique
[Termes IGN] matrice de covariance
[Termes IGN] méthode des moindres carrés
[Termes IGN] modèle stochastique
[Termes IGN] série temporelle
[Termes IGN] signal GPS
[Termes IGN] varianceIndex. décimale : 30.61 Systèmes de Positionnement par Satellites du GNSS Résumé : (Auteur) Data processing in geodetic applications often relies on the least-squares method, for which one needs a proper stochastic model of the observables. Such a realistic covariance matrix allows one first to obtain the best (minimum variance) linear unbiased estimator of the unknown parameters; second, to determine a realistic precision description of the unknowns; and, third, along with the distribution of the data, to correctly perform hypothesis testing and assess quality control measures such as reliability. In many practical applications the covariance matrix is only partly known. The covariance matrix is then usually written as an unknown linear combination of known cofactor matrices. The estimation of the unknown (co)variance components is generally referred to as variance component estimation (VCE). In this thesis we study the method of least-squares variance component estimation (LSVCE) and elaborate on theoretical and practical aspects of the method. We show that LS-VCE is a simple, flexible, and attractive VCE-method. The LS-VCE method is simple because it is based on the well-known principle of least-squares. With this method the estimation of the (co)variance components is based on a linear model of observation equations. The method is flexible since it works with a user-defined weight matrix. Different weight matrix classes can be defined which all automatically lead to unbiased estimators of (co)variance components. LS-VCE is attractive since it allows one to apply the existing body of knowledge of least-squares theory to the problem of (co)variance component estimation. With this method, one can 1) obtain measures of discrepancies in the stochastic model, 2) determine the covariance matrix of the (co)variance components, 3) obtain the minimum variance estimator of (co)variance components by choosing the weight matrix as the inverse of the covariance matrix, 4) take the a-priori information on the (co)variance component into account, 5) solve for a nonlinear (co)variance component model, 6) apply the idea of robust estimation to (co)variance components, 7) evaluate the estimability of the (co)variance components, and 8) avoid the problem of obtaining negative variance components. LS-VCE is capable of unifying many of the existing VCE-methods such as MINQUE, BIQUE, and REML, which can be recovered by making appropriate choices for the weight matrix. An important feature of the LS-VCE method is the capability of applying hypothesis testing to the stochastic model, for which we rely on the w-test, v-test, and overall model test. We aim to find an appropriate structure for the stochastic model which includes the relevant noise components into the covariance matrix. The w-test statistic is introduced to see whether or not a certain noise component is likely to be present in the observations, which consequently can be included in the stochastic model. Based on the normal distribution of the original observables we determine the mean and the variance of the w-test statistic, which are zero and one, respectively. The distribution is a linear combination of mutually independent central chi-square distributions each with one degree of freedom. This distribution can be approximated by the standard normal distribution for some special cases. An equivalent expression for the w-test is given by introducing the v-test statistic. The goal is to decrease the number of (co)variance components of the stochastic model by testing the significance of the components. The overall model test is introduced to generally test the appropriateness of a proposed stochastic model. We also apply LS-VCE to real data of two GPS applications. LS-VCE is applied to the GPS geometry-free model. We present the functional and stochastic model of the GPS observables. The variance components of different observation types, satellite elevation dependence of GPS observables’ precision, and correlation between different observation types are estimated by LS-VCE. We show that the precision of the GPS observables clearly depends on the elevation angle of satellites. Also, significant correlation between observation types is found. For the second application we assess the noise characteristics of time series of daily coordinates for permanent GPS stations. We apply LS-VCE to estimate white noise and power-law noise (flicker noise and random walk noise) amplitudes in these time series. The results confirm that the time series are highly time correlated. We also use the w-test statistic to find an appropriate stochastic model of GPS time series. A combination of white noise, autoregressive noise, and flicker noise in general best characterizes the noise in all three position components. Unmodelled periodic effects in the data are then captured by a set of harmonic functions, for which we rely on least-squares harmonic estimation (LS-HE) developed in the same framework as LS-VCE. The results confirm the presence of annual and semiannual signals, as well as other significant periodic patterns in the series. To avoid the biased estimation of the variance components, such sinusoidal signals should be included in the functional part of the model before applying LS-VCE. Note de contenu : 1. Introduction
2. Least-Squares Estimation and Validation
3. Variance Component Estimation: A Review
4. Least-Squares Variance Component Estimation
5. Detection and Validation in Stochastic Model
6. Multivariate Variance-Covariance Analysis
7. GPS Geometry-Free Model
8. GPS Coordinate Time Series
9. Conclusions and Recommendations
A. Mathematical Background
B. Derivation of Equations
C. Moments of Normally Distributed Data
D. Mixed model with hard constraints
BibliographyNuméro de notice : 15303 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Thèse étrangère DOI : sans En ligne : https://www.ncgeo.nl/downloads/71Memarzadeh.pdf Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=62689 Réservation
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