Centre dedocumentation
scientifique

Wavelet-adaptive neural subtractive clustering fuzzy inference system to enhance low-cost and high-speed INS/GPS navigation system / Elahe S. Abdolkarimi in GPS solutions, vol 24 n° 2 (April 2020)  

Public [article]  inGPS solutions > vol 24 n° 2 (April 2020) Titre : Wavelet-adaptive neural subtractive clustering fuzzy inference system to enhance low-cost and high-speed INS/GPS navigation system Type de document : Article/Communication Auteurs : Elahe S. Abdolkarimi, Auteur ; Mohammad-Reza Mosavi, Auteur Année de publication : 2020 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Navigation et positionnement [Termes descripteurs IGN] centrale inertielle [Termes descripteurs IGN] coût [Termes descripteurs IGN] filtre de Kalman [Termes descripteurs IGN] GPS-INS [Termes descripteurs IGN] imprécision des données [Termes descripteurs IGN] incertitude des données [Termes descripteurs IGN] Inférence floue [Termes descripteurs IGN] précision du positionnement [Termes descripteurs IGN] rapport signal sur bruit [Termes descripteurs IGN] transformation en ondelettes [Termes descripteurs IGN] vitesse de déplacement Résumé : (auteur) The combined navigation system consisting of Global Positioning System (GPS) and Inertial Navigation System in a complementary mode assures an accurate, reliable, and continuous positioning capability in the navigation system. Because of problems such as dealing with a low-cost MEMS-based inertial sensors having a high level of uncertainty and imprecision, stochastic noise, a high-speed vehicle, high noisy real data, and long-term GPS signal outage during the real-time flight test, the advantage is taken for some approaches in different steps: (1) utilizing discrete wavelet transform technique to enhance the signal-to-noise ratio in raw and noisy inertial sensor signals and attenuate high-frequency noise as a preprocessing phase to prepare more accurate data for the proposed model and (2) employing adaptive neural subtractive clustering fuzzy inference system (ANSCFIS) which combines and extracts the best feature of adaptive neuro-fuzzy inference system (ANFIS), and the subtractive clustering algorithm with fewer rules than the ANFIS method, aiming to improve a more efficient, accurate, and especially a faster method which enhances the prediction accuracy and speeds up the positioning system. The achieved accuracies for the proposed model are discussed and compared with the extended Kalman filter (EKF), ANFIS, and ANSCFIS which are implemented and tested experimentally using a high-speed vehicle in three GPS blockages. The proposed model shows considerable improvements in high-speed navigation using low-cost MEMS-based inertial sensors in case of long-term GPS blockage. Numéro de notice : A2020-084 Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s10291-020-0951-y date de publication en ligne : 11/01/2020 En ligne : https://doi.org/10.1007/s10291-020-0951-y Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94654 [article]

Wavelet and non-parametric statistical based approach for long term land cover trend analysis using time series EVI data / Niraj Priyadarshi in Geocarto international, vol 35 n° 5 ([01/04/2020])  

Public [article]  inGeocarto international > vol 35 n° 5 [01/04/2020] . - pp 512 - 534 Titre : Wavelet and non-parametric statistical based approach for long term land cover trend analysis using time series EVI data Type de document : Article/Communication Auteurs : Niraj Priyadarshi, Auteur ; V.M. Chowdary, Auteur ; Iswar Chandra Das, Auteur ; Jeganathan Chockalingam, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 512 - 534 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image [Termes descripteurs IGN] changement d'occupation du sol [Termes descripteurs IGN] Enhanced vegetation index [Termes descripteurs IGN] filtrage du bruit [Termes descripteurs IGN] image MODIS [Termes descripteurs IGN] série temporelle [Termes descripteurs IGN] transformation en ondelettes Résumé : (auteur) Land cover change analysis was carried out using Moderate Resolution Imaging Spectroradiometer (MODIS) Enhanced Vegetation Index (EVI) time series data for the period 2005–2014. MODIS EVI data coupled with Quality Assessment Science Data Sets (QASDS) was de-noised with Savitzky–Golay filter while enhancing quality and preserving the temporal profile of EVI. Wavelet transform (WT) based approach along with Sen slope’s method was used for land cover change and trend analysis. The WT based approach is useful for studying multiscale and non-stationary processes. Mann–Kendall test was performed to confirm the significance of the identified trends. Proposed approach identified 358 locations as change points, where 285 (79.6%) and 73 (20.4%) locations were detected as ‘Change’ and ‘False Change’ with respect to high resolution images. The proposed approach is useful for monitoring land cover changes that provide vital inputs for sustainable management of land resources. Numéro de notice : A2020-143 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2018.1520925 date de publication en ligne : 24/10/2018 En ligne : https://doi.org/10.1080/10106049.2018.1520925 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94769 [article]

Robust acquisition at GPS receivers in unsafe locations using complex wavelet transform / M. Moazedi in Survey review, vol 51 n° 369 (November 2019)  

Public [article]  inSurvey review > vol 51 n° 369 (November 2019) . - pp 514 - 524 Titre : Robust acquisition at GPS receivers in unsafe locations using complex wavelet transform Type de document : Article/Communication Auteurs : M. Moazedi, Auteur ; Mohammad-Reza Mosavi, Auteur ; A. Sadr, Auteur Année de publication : 2019 Article en page(s) : pp 514 - 524 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie spatiale [Termes descripteurs IGN] anti-leurrage [Termes descripteurs IGN] interférence [Termes descripteurs IGN] méthode robuste [Termes descripteurs IGN] récepteur GPS [Termes descripteurs IGN] signal GPS [Termes descripteurs IGN] transformation en ondelettes Résumé : (auteur) Growing importance of Global Positioning System (GPS) applications in various fields, leads many researches to the security of GPS systems and investigation of eventual perturbations in them. One of the most important intentional interferences is spoofing. This work presents an anti-spoofing method based on complex wavelet transform (CWT). Fake satellites are omitted and then understrength satellites due to spoofing are identified. The results of investigation suggest that the proposed CWT based estimation and extraction method is better than relatively simple wavelet transform. The suggested filter is applied in the Intermediate Frequency signal. Cross-validation technique is used for automatically identifying wavelet signal layers. The proposed method has been implemented on different collected datasets. Software GPS Receiver has been used to implement and validate the developed anti-spoofing technique because it is more flexible and economical compared with usual hardware receivers. Numéro de notice : A2019-573 Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/00396265.2018.1483597 date de publication en ligne : 18/06/2018 En ligne : https://doi.org/10.1080/00396265.2018.1483597 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94449 [article]

Traffic signal detection from in-vehicle GPS speed profiles using functional data analysis and machine learning / Yann Méneroux in International Journal of Data Science and Analytics JDSA, vol inconnu ([01/10/2019])  

Public [article]  inInternational Journal of Data Science and Analytics JDSA > vol inconnu [01/10/2019] Titre : Traffic signal detection from in-vehicle GPS speed profiles using functional data analysis and machine learning Type de document : Article/Communication Auteurs : Yann Méneroux , Auteur ; Arnaud Le Guilcher , Auteur ; Guillaume Saint Pierre, Auteur ; Mohammad Ghasemi Hamed, Auteur ; Sébastien Mustière , Auteur ; O. Orfila, Auteur Année de publication : 2019 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes descripteurs IGN] analyse fonctionnelle (mathématiques) [Termes descripteurs IGN] apprentissage profond [Termes descripteurs IGN] carte routière [Termes descripteurs IGN] classification par forêts aléatoires [Termes descripteurs IGN] contenu généré par les utilisateurs [Termes descripteurs IGN] détection d'objet [Termes descripteurs IGN] données routières [Termes descripteurs IGN] feu de circulation [Termes descripteurs IGN] inférence [Termes descripteurs IGN] reconnaissance de formes [Termes descripteurs IGN] signalisation routière [Termes descripteurs IGN] trace GPS [Termes descripteurs IGN] trafic routier [Termes descripteurs IGN] transformation en ondelettes [Termes descripteurs IGN] vitesse Résumé : (auteur) The increasing availability of large-scale global positioning system data stemming from in-vehicle-embedded terminal devices enables the design of methods deriving road network cartographic information from drivers’ recorded traces. Some machine learning approaches have been proposed in the past to train automatic road network map inference, and recently this approach has been successfully extended to infer road attributes as well, such as speed limitation or number of lanes. In this paper, we address the problem of detecting traffic signals from a set of vehicle speed profiles, under a classification perspective. Each data instance is a speed versus distance plot depicting over a hundred profiles on a 100-m-long road span. We proposed three different ways of deriving features: The first one relies on the raw speed measurements; the second one uses image recognition techniques; and the third one is based on functional data analysis. We input them into most commonly used classification algorithms, and a comparative analysis demonstrated that a functional description of speed profiles with wavelet transforms seems to outperform the other approaches with most of the tested classifiers. It also highlighted that random forests yield an accurate detection of traffic signals, regardless of the chosen feature extraction method, while keeping a remarkably low confusion rate with stop signs. Numéro de notice : A2019-497 Thématique : GEOMATIQUE Nature : Article DOI : 10.1007/s41060-019-00197-x date de publication en ligne : 04/10/2019 En ligne : https://doi.org/10.1007/s41060-019-00197-x Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93755 [article]

Geospatial data organization methods with emphasis on aperture-3 hexagonal discrete global grid systems / Ali Mahdavi Amiri in Cartographica, vol 54 n° 1 (spring 2019)  

Public [article]  inCartographica > vol 54 n° 1 (spring 2019) . - pp 30 - 50 Titre : Geospatial data organization methods with emphasis on aperture-3 hexagonal discrete global grid systems Type de document : Article/Communication Auteurs : Ali Mahdavi Amiri, Auteur ; Troy Alderson, Auteur ; Faramarz Samavati, Auteur Année de publication : 2019 Article en page(s) : pp 30 - 50 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes descripteurs IGN] arbre de décision [Termes descripteurs IGN] données vectorielles [Termes descripteurs IGN] méthode des moindres carrés [Termes descripteurs IGN] ondelette de Haar [Termes descripteurs IGN] régression [Termes descripteurs IGN] système de grille globale discrète [Termes descripteurs IGN] transformation en ondelettes Résumé : (Auteur) Digital Earth frameworks deal with data sets of different types collected from various sources. To effectively store, retrieve, and transmit these data sets, efficient multi-scale data representations that are compatible with the underlying structure of the Digital Earth framework are required. In this article, we describe several such techniques and their properties: namely, how to represent data in the multi-scale cell hierarchy of a discrete global grid system (DGGS) or in the multi-scale hierarchy of a customized wavelet transform. We also discuss how these techniques can be tuned to be applicable to the A3H DGGS. Numéro de notice : A2019-435 Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3138/cart.54.1.2018-0010 En ligne : https://doi.org/10.3138/cart.54.1.2018-0010 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92761 [article]

Réservation

Réserver ce document

Exemplaires (2)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
031-2019012	SL	Revue	Centre de documentation	Revues en salle	Disponible
031-2019011	SL	Revue	Centre de documentation	Revues en salle	Disponible

A new waveform decomposition method for multispectral LiDAR / Shalei Song in ISPRS Journal of photogrammetry and remote sensing, vol 149 (March 2019)  

Permalink

Sea level estimation from SNR data of geodetic receivers using wavelet analysis / Xiaolei Wang in GPS solutions, vol 23 n° 1 (January 2019)  

Permalink

Least-squares cross-wavelet analysis and its applications in geophysical time series / Ebrahim Ghaderpour in Journal of geodesy, vol 92 n° 10 (October 2018)  

Permalink

Spectral-spatial classification of hyperspectral images using wavelet transform and hidden Markov random fields / Elham Kordi Ghasrodashti in Geocarto international, vol 33 n° 8 (August 2018)  

Permalink

Exploring image fusion of ALOS/PALSAR data and LANDSAT data to differentiate forest area / Saygin Abdikan in Geocarto international, vol 33 n° 1 (January 2018)  

Permalink

A wavelet decomposition and polynomial fitting-based method for the estimation of time-varying residual motion error in airborne interferometric SAR / Hai Qiang Fu in IEEE Transactions on geoscience and remote sensing, vol 56 n° 1 (January 2018)  

Permalink

WREP : A wavelet-based technique for extracting the red edge position from reflectance spectra for estimating leaf and canopy chlorophyll contents of cereal crops / Dong Li in ISPRS Journal of photogrammetry and remote sensing, vol 129 (July 2017)  

Permalink

Regression wavelet analysis for lossless coding of remote-sensing data / Naoufal Amrani in IEEE Transactions on geoscience and remote sensing, vol 54 n° 9 (September 2016)  

Permalink

A new method for specular and diffuse pseudorange multipath error extraction using wavelet analysis / Giovanni Pugliano in GPS solutions, vol 20 n° 3 (July 2016)  

Permalink

Characterization of ionospheric variability in TEC using EOF and wavelets over low-latitude GNSS stations / J.R.K. Kumar Dabbakuti in Advances in space research, vol 57 n° 12 (June 2016)  

Permalink