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A low-cost integrated MEMS-based INS/GPS vehicle navigation system with challenging conditions based on an optimized IT2FNN in occluded environments / Elahe S. Abdolkarimi in GPS solutions, Vol 24 n° 4 (October 2020)  

Public [article]  inGPS solutions > Vol 24 n° 4 (October 2020) . - 19 p. Titre : A low-cost integrated MEMS-based INS/GPS vehicle navigation system with challenging conditions based on an optimized IT2FNN in occluded environments Type de document : Article/Communication Auteurs : Elahe S. Abdolkarimi, Auteur ; Mohammad-Reza Mosavi, Auteur Année de publication : 2020 Article en page(s) : 19 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie spatiale [Termes IGN] centrale inertielle [Termes IGN] classification floue [Termes IGN] classification par réseau neuronal [Termes IGN] filtrage du bruit [Termes IGN] filtre de Kalman [Termes IGN] GPS-INS [Termes IGN] microsystème électromécanique [Termes IGN] modèle d'incertitude [Termes IGN] rapport signal sur bruit [Termes IGN] transformation en ondelettes Résumé : (auteur) Integration of both global positioning system (GPS) and inertial navigation system (INS) assures a continuous and accurate navigation system. In low-cost low-precision micro-electromechanical system (MEMS)-based INS/GPS integration navigation systems, one of the major concerns is high-level stochastic noise and uncertainties existing in INS sensors and complex model of real noisy data. In such uncertainty-oriented environments, an intelligence structure with extra degrees of freedom which can handle and model a high-level of uncertainties in INS sensors, and an efficient denoising technique as a precursor to the intelligence structure can be efficient solutions. Our approach to these problems is taken in different steps. First, a denoising technique based on empirical mode decomposition (EMD) is used to provide more accurate INS sensor outputs and better generalization ability. Second, an optimized interval type-2 fuzzy neural network is used to model and handle a high-level of uncertainties efficiently and estimate the positioning error of INS sensors when GPS signals are blocked, and still meet both accuracy maximization and complexity minimization. Fast learning and convergence of the algorithm and less computational complexity can be achieved by using an extended Kalman filter in the learning of algorithm and an accurate and simple type-reduction, respectively, which can be utilized in real-time applications with significant performance. The results of EMD-based denoising technique, as a preprocessing phase, verify superior performance in comparison with the discrete wavelet transform denoising method in the signal-to-noise ratio improvement for raw and noisy signals of INS sensors. To verify the effectiveness of our proposed model, we applied challenging conditions consisting of low-cost low-precision inertial sensors based on MEMS technology, long-term outages of GPS satellites, a high-speed experimental test vehicle and noisy real-world data in the real-time flight experiments. The achieved experimental accuracies are compared with the results that we have achieved in other methods, and our proposed method verifies significant improvements. Numéro de notice : A2020-521 Affiliation des auteurs : non IGN Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s10291-020-01023-9 Date de publication en ligne : 18/08/2020 En ligne : https://doi.org/10.1007/s10291-020-01023-9 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95692 [article]

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 IGN] centrale inertielle [Termes IGN] coût [Termes IGN] filtre de Kalman [Termes IGN] GPS-INS [Termes IGN] imprécision des données [Termes IGN] incertitude des données [Termes IGN] Inférence floue [Termes IGN] précision du positionnement [Termes IGN] rapport signal sur bruit [Termes IGN] transformation en ondelettes [Termes 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 Affiliation des auteurs : non IGN 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]

Geometric and statistical interpretation of correlation between fault tests in integrated GPS/INS systems / Ali Almagbile in Journal of applied geodesy, vol 13 n° 3 (July 2019)  

Public [article]  inJournal of applied geodesy > vol 13 n° 3 (July 2019) . - pp 267 – 278 Titre : Geometric and statistical interpretation of correlation between fault tests in integrated GPS/INS systems Type de document : Article/Communication Auteurs : Ali Almagbile, Auteur Année de publication : 2019 Article en page(s) : pp 267 – 278 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie spatiale [Termes IGN] coefficient de corrélation [Termes IGN] détection d'erreur [Termes IGN] données GPS [Termes IGN] erreur de positionnement [Termes IGN] fiabilité des données [Termes IGN] GPS-INS [Termes IGN] incertitude géométrique Résumé : (auteur) Fault detection and identification (FDI) in either a stand-alone GPS or in integrated GPS/INS systems is essential for improving the quality of positioning, navigation, and many other applications. The assumption that the observations include a single fault has been considered intensively in literature. However, this assumption may not necessarily be valid due to the fact that multiple faults may exist simultaneously. In this study, separability of multiple faults in GPS/INS integration systems has been analysed geometrically and statistically. This has been achieved through testing how large correlation coefficient between any pair of fault tests statistics increases the probability of faults misidentification. In addition, a new calculation procedure of correlation coefficient when four faults appear in the observations has been developed. This procedure considers calculation the correlation between a single and a punch of measurements combined together. The results show that there is a strong relationship between the value of correlation coefficient and the probability of misidentification. Furthermore, a significant relationship between the correlation and the fault test values can be found when splitting the measurements combinations into groups based on the combination similarity. Nevertheless, this relationship can be defined without splitting the measurements into groups when using a new correlation procedure for four faults case. The geometric representation shows that large correlation coefficient reflects small angle between the correlation and the x-axis; whereas the angle between the fault-test vectors and the x-axis becomes wider when a tiny correlation exist. Numéro de notice : A2019-287 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1515/jag-2019-0008 Date de publication en ligne : 05/06/2019 En ligne : https://doi.org/10.1515/jag-2019-0008 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93123 [article]

On constrained integrated total Kalman filter for integrated direct geo-referencing / Vahid Mahboub in Survey review, vol 51 n° 364 (January 2019)  

Public [article]  inSurvey review > vol 51 n° 364 (January 2019) . - pp 26 - 34 Titre : On constrained integrated total Kalman filter for integrated direct geo-referencing Type de document : Article/Communication Auteurs : Vahid Mahboub, Auteur ; Mohammad Saadatseresht, Auteur ; Alireza A. Ardalan, Auteur Année de publication : 2019 Article en page(s) : pp 26 - 34 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement du signal [Termes IGN] filtrage du bruit [Termes IGN] filtre de Kalman [Termes IGN] géoréférencement direct [Termes IGN] GPS-INS [Termes IGN] invariant [Termes IGN] matrice de covariance [Termes IGN] modèle dynamique Résumé : (Auteur) A constrained integrated total Kalman filter algorithm is developed. It considers a quadratic constraint which may appear in some problems of integrated direct geo-referencing in particular when INS data is used as system equations of a Kalman filter algorithm. In such a case one encounters with a dynamic errors-in-variables (DEIV) model for system equations, although DEIV model has been already considered for equations of the Kalman filter algorithm and a solution namely integrated total Kalman filter (ITKF) has been given to it. Also this algorithm can be simplified to unconstraint case which is useful for some problems. It considers DEIV model for both observation equations and system equations of the Kalman filter algorithm. The predicted residuals for all variables including the random noise at the first epoch, the observational noise, the random system noise and the corresponding noise of two coefficient matrixes (in the system equations and the observation equations) besides the variance matrix of the unknown parameters are obtained. In two numerical examples, integrated direct geo-referencing problem is solved for a GPS-INS system. Numéro de notice : A2019-186 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/00396265.2017.1341736 Date de publication en ligne : 30/06/2017 En ligne : https://doi.org/10.1080/00396265.2017.1341736 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92617 [article]

Design and implementation of a model predictive observer for AHRS / Jafar Keighobadi in GPS solutions, vol 22 n° 1 (January 2018)  

Public [article]  inGPS solutions > vol 22 n° 1 (January 2018) Titre : Design and implementation of a model predictive observer for AHRS Type de document : Article/Communication Auteurs : Jafar Keighobadi, Auteur ; Hamid Vosoughi, Auteur ; Javad Faraji, Auteur Année de publication : 2018 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Navigation et positionnement [Termes IGN] angle d'Euler [Termes IGN] attitude and heading reference system AHRS [Termes IGN] erreur instrumentale [Termes IGN] erreur systématique [Termes IGN] estimateur [Termes IGN] filtre de Kalman [Termes IGN] GPS-INS [Termes IGN] microsystème électromécanique [Termes IGN] véhicule Résumé : (auteur) A GPS-aided Inertial Navigation System (GAINS) is used to determine the orientation‚ position and velocity of ground and aerial vehicles. The data measured by Inertial Navigation System (INS) and GPS are commonly integrated through an Extended Kalman Filter (EKF). Since the EKF requires linearized models and complete knowledge of predefined stochastic noises‚ the estimation performance of this filter is attenuated by unmodeled nonlinearity and bias uncertainties of MEMS inertial sensors. The Attitude Heading Reference System (AHRS) is applied based on the quaternion and Euler angles methods. A moving horizon-based estimator such as Model Predictive Observer (MPO) enables us to approximate and estimate linear systems affected by unknown uncertainties. The main objective of this research is to present a new MPO method based on the duality principle between controller and observer of dynamic systems and its implementation in AHRS mode of a low-cost INS aided by a GPS. Asymptotic stability of the proposed MPO is proven by applying Lyapunov’s direct method. The field test of a GAINS is performed by a ground vehicle to assess the long-time performance of the MPO method compared with the EKF. Both the EKF and MPO estimators are applied in AHRS mode of the MEMS GAINS for the purpose of real-time performance comparison. Furthermore‚ we use flight test data of the GAINS for evaluation of the estimation filters. The proposed MPO based on both the Euler angles and quaternion methods yields better estimation performances compared to the classic EKF. Numéro de notice : A2018-017 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article DOI : 10.1007/s10291-017-0696-4 En ligne : https://doi.org/10.1007/s10291-017-0696-4 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89114 [article]

Vehicle dynamic model based navigation for small UAVs / Mehran Khaghani (2018)  

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Robust wavelet-based inertial sensor error mitigation for tightly coupled GPS/BDS/INS integration during signal outages / Jian Wang in Survey review, vol 49 n° 357 (December 2017)  

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Ionospheric and receiver DCB-constrained multi-GNSS single-frequency PPP integrated with MEMS inertial measurements / Zhouzheng Gao in Journal of geodesy, vol 91 n° 11 (November 2017)  

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Robust GPS/BDS/INS tightly coupled integration with atmospheric constraints for long-range kinematic positioning / Houzeng Han in GPS solutions, vol 21 n° 3 (July 2017)  

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Shipborne over- and under-water integrated mobile mapping system and its seamless integration of point clouds / Bo Shi in Marine geodesy, vol 40 n° 2-3 (March - June 2017)  

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Implementation of a real-time stacking algorithm in a photogrammetric digital camera for UAVs / Ahmad Audi (2017)  

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Adaptive GPS/INS integration for relative navigation / Je Young Lee in GPS solutions, vol 20 n° 1 (January 2016)  

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Entwicklung einer direkten Georeferenzierungseinheit zur Positions- und Orientierungbestimmung leichter UAVs in Eichzeit / Christian Eling (2016)

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Improving MEMS-IMU/GPS integrated systems for land vehicle navigation applications / S. Sasani in GPS solutions, vol 20 n° 1 (January 2016)  

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Structural integrity verification of cable stayed footbridge based on FEM analyses and geodetic surveying techniques / Vassilis Gikas in Survey review, vol 48 n° 346 (January 2016)  

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