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An analytic expression for the phase noise of the goldstein–werner filter / Scott Hensley in IEEE Transactions on geoscience and remote sensing, vol 57 n° 9 (September 2019)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 57 n° 9 (September 2019) . - pp 6499 - 6516 Titre : An analytic expression for the phase noise of the goldstein–werner filter Type de document : Article/Communication Auteurs : Scott Hensley, Auteur Année de publication : 2019 Article en page(s) : pp 6499 - 6516 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes descripteurs IGN] bruit thermique [Termes descripteurs IGN] corrélation temporelle [Termes descripteurs IGN] densité spectrale de puissance [Termes descripteurs IGN] filtrage du bruit [Termes descripteurs IGN] filtre de Goldstein [Termes descripteurs IGN] image radar moirée [Termes descripteurs IGN] interféromètrie par radar à antenne synthétique [Termes descripteurs IGN] phase [Termes descripteurs IGN] pouvoir de résolution spectrale [Termes descripteurs IGN] rapport signal sur bruit [Termes descripteurs IGN] transformation de Fourier Résumé : (auteur) Interferogram filtering for noise reduction is a key to many radar interferometric applications. Repeat pass radar interferometry often uses data with less than ideal correlation levels resulting from either long spatial or temporal baselines or changes between observations leading to high levels of temporal correlation. To maximize the utility of such pairs filtering the interferogram to get maximal noise reduction is often needed. One technique that has proved quite useful in the geophysical community is power spectral or Goldstein–Werner filtering of the interferogram whereby a power-weighted version of the Fourier transform is used to enhance fringe visibility. Although this paper defining the filter briefly touched upon the spatial resolution and noise reduction induced by the filter, it did not provide a useful formula for predicting the phase noise after filtering. This paper derives a formula for the phase noise obtained from power spectral filtering albeit under the restriction of several simplifying assumptions to make the problem analytically tractable. In particular, it is assumed that the interferometric phase is locally well approximated by a linear phase ramp with nonlinear phase perturbations small in a spectral energy sense compared to the linear term. Numéro de notice : A2019-343 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2019.2906549 date de publication en ligne : 25/04/2019 En ligne : http://doi.org/10.1109/TGRS.2019.2906549 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93378 [article]

Decomposition of geodetic time series: A combined simulated annealing algorithm and Kalman filter approach / Feng Ming in Advances in space research, vol 64 n°5 (1 September 2019)  

Public [article]  inAdvances in space research > vol 64 n°5 (1 September 2019) . - pp Titre : Decomposition of geodetic time series: A combined simulated annealing algorithm and Kalman filter approach Type de document : Article/Communication Auteurs : Feng Ming, Auteur ; Yuanxi Yang, Auteur ; Anmin Zeng, Auteur ; Bin Zhao, Auteur Année de publication : 2019 Article en page(s) : pp Langues : Anglais (eng) Descripteur : [Termes descripteurs IGN] algorithme du recuit simulé [Termes descripteurs IGN] bruit (théorie du signal) [Termes descripteurs IGN] bruit blanc [Termes descripteurs IGN] bruit rose [Termes descripteurs IGN] données GPS [Termes descripteurs IGN] filtre de Kalman [Termes descripteurs IGN] méthode du maximum de vraisemblance (estimation) [Termes descripteurs IGN] série temporelle [Termes descripteurs IGN] variation saisonnière [Vedettes matières IGN] Traitement de données GNSS Numéro de notice : A2019-399 Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.asr.2019.05.049 date de publication en ligne : 10/06/2019 En ligne : https://doi.org/10.1016/j.asr.2019.05.049 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93519 [article]

Investigation of the noise properties at low frequencies in long GNSS time series / Xiaoxing He in Journal of geodesy, vol 93 n° 9 (September 2019)  

Public [article]  inJournal of geodesy > vol 93 n° 9 (September 2019) . - pp 1271 - 1282 Titre : Investigation of the noise properties at low frequencies in long GNSS time series Type de document : Article/Communication Auteurs : Xiaoxing He, Auteur ; Machiel Bos, Auteur ; Jean-Philippe Montillet, Auteur ; Rui Fernandes, Auteur Année de publication : 2019 Article en page(s) : pp 1271 - 1282 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement du signal [Termes descripteurs IGN] bruit (théorie du signal) [Termes descripteurs IGN] bruit blanc [Termes descripteurs IGN] bruit rose [Termes descripteurs IGN] données GNSS [Termes descripteurs IGN] modèle physique [Termes descripteurs IGN] série temporelle Résumé : (Auteur) The accuracy by which velocities can be estimated from GNSS time series is mainly determined by the low-frequency noise, below 0.2–0.1 cpy, which are normally described by a power-law model. As GNSS observations have now been recorded for over two decades, new information about the noise at these low frequencies has become available and we investigate whether alternative noise models should be considered using the log-likelihood, Akaike and Bayesian information criteria. Using 110 globally distributed IGS stations with at least 12 years of observations, we find that for 80–90% of them the preferred noise models are still the power law or flicker noise with white noise. For around 6% of the stations, we found the presence of random-walk noise, which increases the linear trend uncertainty when taken into account in the stochastic noise model of the time series by about a factor of 1.5 to 8.4, in agreement with previous studies. Next, the Generalised Gauss–Markov with white noise model describes the stochastic properties better for 4% and 5% of the stations for the East and North component, respectively, and 13% for the vertical component. For these stations, the uncertainty associated with the tectonic rate is about 2 times smaller compared to the case when the standard power-law plus white noise model is used. Numéro de notice : A2019-503 Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s00190-019-01244-y date de publication en ligne : 14/03/2019 En ligne : https://doi.org/10.1007/s00190-019-01244-y Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93785 [article]

On the application of Monte Carlo singular spectrum analysis to GPS position time series / Seyed Mohsen Khazraei in Journal of geodesy, vol 93 n° 9 (September 2019)  

Public [article]  inJournal of geodesy > vol 93 n° 9 (September 2019) . - pp 1401 - 1418 Titre : On the application of Monte Carlo singular spectrum analysis to GPS position time series Type de document : Article/Communication Auteurs : Seyed Mohsen Khazraei, Auteur ; AliReza Amiri-Simkooei, Auteur Année de publication : 2019 Article en page(s) : pp 1401 - 1418 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement du signal [Termes descripteurs IGN] algorithme de Cholesky [Termes descripteurs IGN] analyse de spectre singulier [Termes descripteurs IGN] bruit (théorie du signal) [Termes descripteurs IGN] bruit blanc [Termes descripteurs IGN] bruit rose [Termes descripteurs IGN] coordonnées GPS [Termes descripteurs IGN] méthode de Monte-Carlo [Termes descripteurs IGN] méthode des moindres carrés [Termes descripteurs IGN] positionnement par GPS [Termes descripteurs IGN] série temporelle Résumé : (Auteur) Singular spectrum analysis (SSA) has recently been applied to various geodetic time series studies. As a data-adaptive method, SSA is capable of extracting signals with non-constant phase and amplitudes. Although SSA is a competent method in the presence of white noise, the contribution of colored noise, having semi-periodic behavior, degrades its performance. Parts of colored noise can be absorbed in the SSA eigenmodes, which specifies signals and hence resulting in spurious modulation or losing significant signals. Signals and colored noise are thus to be discriminated in the signal identification procedure. Monte Carlo SSA (MCSSA) in its original formulation, providing a significance test against the AR(1) noise null hypothesis, can be misinterpreted when other colored noise structures contribute to the series. We propose an algorithm for MCSSA that is not limited to the AR(1) noise hypothesis. It estimates the noise model parameters using LS-VCE and generates the surrogate data using the Cholesky decomposition. The algorithm is adapted to GPS position time series where the underlying noise is a combination of white noise and flicker noise. GPS position time series, postulated real situation, are first simulated to include annual and semiannual signals plus white and flicker noise. The results indicate that MCSSA can extract the annual and semiannual signals with 2.11 and 1.25 mm amplitudes (the global mean values) from 20-year-long time series, with 95% confidence level, if flicker noise is less than 17 and 13 mm/year1/4mm/year1/4, respectively. The longer the time series or the stronger the signals are, the higher these thresholds will be. This conclusion is also verified when applying MCSSA to the up component of GPS position time series of 347 JPL stations. Numéro de notice : A2019-505 Thématique : MATHEMATIQUE/POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s00190-019-01253-x date de publication en ligne : 08/04/2019 En ligne : https://doi.org/10.1007/s00190-019-01253-x Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93788 [article]

Influence of stochastic modeling for inter-system biases on multi-GNSS undifferenced and uncombined precise point positioning / Feng Zhou in GPS solutions, vol 23 n° 3 (July 2019)  

Public [article]  inGPS solutions > vol 23 n° 3 (July 2019) Titre : Influence of stochastic modeling for inter-system biases on multi-GNSS undifferenced and uncombined precise point positioning Type de document : Article/Communication Auteurs : Feng Zhou, Auteur ; Danan Dong, Auteur ; Xin Li, Auteur ; Harald Schuh, Auteur Année de publication : 2019 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Navigation et positionnement [Termes descripteurs IGN] bruit blanc [Termes descripteurs IGN] décalage d'horloge [Termes descripteurs IGN] erreur systématique inter-systèmes [Termes descripteurs IGN] estimation statistique [Termes descripteurs IGN] modèle stochastique [Termes descripteurs IGN] positionnement par GNSS [Termes descripteurs IGN] positionnement ponctuel précis Résumé : (auteur) The focus of this study is on proper modeling of the dynamics for inter-system biases (ISBs) in multi-constellation Global Navigation Satellite System (GNSS) precise point positioning (PPP) processing. First, the theoretical derivation demonstrates that the ISBs originate from not only the receiver-dependent hardware delay differences among different GNSSs but also the receiver-independent time differences caused by the different clock datum constraints among different GNSS satellite clock products. Afterward, a comprehensive evaluation of the influence of ISB stochastic modeling on undifferenced and uncombined PPP performance is conducted, i.e., random constant, random walk process, and white noise process are considered. We use data based on a 1-month period (September 2017) Multi-GNSS Experiment (MGEX) precise orbit and clock products from four analysis centers (CODE, GFZ, CNES, and WHU) and 160 MGEX tracking stations. The results demonstrate that generally, the positioning performance of PPP in terms of convergence time and positioning accuracy with the final products from CODE, CNES, and WHU is comparable among the three ISB handling schemes. However, estimating ISBs as random walk process or white noise process outperforms that as the random constant when using the GFZ products. These results indicate that the traditional estimation of ISBs as the random constant may not always be reasonable in multi-GNSS PPP processing. To achieve more reliable positioning results, it is highly recommended to consider the ISBs as random walk process or white noise process in multi-GNSS PPP processing. Numéro de notice : A2019-199 Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s10291-019-0852-0 date de publication en ligne : 09/04/2019 En ligne : https://doi.org/10.1007/s10291-019-0852-0 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92654 [article]

Signaux et systèmes / André Quinquis (2019)

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Bruit de scintillation dans les séries temporelles de positions GNSS / Paul Rebischung (2018) 

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Characterizing noise in daily GPS position time series with overlapping Hadamard variance and maximum likelihood estimation / Chang Xu in Survey review, vol 49 n° 355 (October 2017)  

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Denoising of natural images through robust wavelet thresholding and genetic programming / Asem Khmag in The Visual Computer, vol 33 n°9 (September 2017)  

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GPS coordinate time series measurements in Ontario and Quebec, Canada / Hadis Samadi Alinia in Journal of geodesy, vol 91 n° 6 (June 2017)  

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Multivariate analysis of GPS position time series of JPL second reprocessing campaign / AliReza Amiri-Simkooei in Journal of geodesy, vol 91 n° 6 (June 2017)  

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Modified residual method for the estimation of noise in hyperspectral images / Asad Mahmood in IEEE Transactions on geoscience and remote sensing, vol 55 n° 3 (March 2017)  

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Study of the effects on GPS coordinate time series caused by higher-order ionospheric corrections calculated using the DIPOLE model / Liansheng Deng in Geodesy and Geodynamics, vol 8 n° 2 (March 2017)  

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Dictionary learning for promoting structured sparsity in hyperspectral compressive sensing / Lei Zhang in IEEE Transactions on geoscience and remote sensing, vol 54 n° 12 (December 2016)  

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On the spectral combination of satellite gravity model, terrestrial and airborne gravity data for local gravimetric geoid computation / Tao Jian in Journal of geodesy, vol 90 n° 12 (December 2016)  

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