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Integer-estimable GLONASS FDMA model as applied to Kalman-filter-based short- to long-baseline RTK positioning / Pengyu Hou in GPS solutions, Vol 24 n° 4 (October 2020)  

Public [article]  inGPS solutions > Vol 24 n° 4 (October 2020) . - 14 p. Titre : Integer-estimable GLONASS FDMA model as applied to Kalman-filter-based short- to long-baseline RTK positioning Type de document : Article/Communication Auteurs : Pengyu Hou, Auteur ; Baocheng Zhang, Auteur ; Teng Liu, Auteur Année de publication : 2020 Article en page(s) : 14 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie spatiale [Termes descripteurs IGN] compensation Lambda [Termes descripteurs IGN] données GLONASS [Termes descripteurs IGN] données GPS [Termes descripteurs IGN] filtre de Kalman [Termes descripteurs IGN] ionosphère [Termes descripteurs IGN] ligne de base [Termes descripteurs IGN] positionnement cinématique en temps réel [Termes descripteurs IGN] positionnement par GLONASS [Termes descripteurs IGN] résolution d'ambiguïté [Termes descripteurs IGN] signal GLONASS Résumé : (auteur) Fast ambiguity resolution is a major challenge for GLONASS phase-based applications. The integer-estimable frequency-division multiple-access (IE-FDMA) model succeeds in formulating a set of estimable GLONASS phase ambiguities and preserving the integer property, to which the classical integer ambiguity resolution, typically the least-squares ambiguity decorrelation adjustment (LAMBDA), becomes readily applicable. The initial assessment of the IE-FDMA model demonstrated instantaneous ambiguity resolution capability in case of short-baseline real-time kinematic (RTK) positioning based on ionosphere-fixed formulation, in which the data processing strategy is window (batch)-based least-squares estimation with window length ranging from one to a few epochs. Here, we extend the applicability of the IE-FDMA model to Kalman-filter-based, ionosphere-fixed, ionosphere-weighted, and ionosphere-free cases, which are, respectively, adoptable for short-, medium-, and long-baseline RTK positioning. To adapt the IE-FDMA model to the Kalman filter, we estimate, at each epoch, first the estimable ambiguities, then transform them into integer-estimable ones, and finally resolve them into correct integers. This enables the rigorous integer ambiguity resolution and, at the same time, eases the recursive construction of integer-estimable ambiguities. We analyze global positioning system (GPS) and GLONASS data of nine baselines with lengths varying from several meters to more than one hundred kilometers. The results demonstrate the feasibility of fast ambiguity resolution not only for the GLONASS phase-only short-baseline RTK positioning, but for the GPS + GLONASS medium- and long-baseline RTK positioning as well. In all cases, the fixed solution with faster (several-minutes) convergence and higher (centimeter-level) precision indicates the benefits from GLONASS ambiguity resolution as compared to the float solution. Moreover, the dual-system solution with decreased ambiguity dilution of precision (ADOP) and improved positioning precision confirms the advantages of integrating GLONASS with GPS in contrast to the GPS-only situation. Numéro de notice : A2020-524 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s10291-020-01008-8 date de publication en ligne : 11/07/2020 En ligne : https://doi.org/10.1007/s10291-020-01008-8 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95699 [article]

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 descripteurs IGN] centrale inertielle [Termes descripteurs IGN] classification floue [Termes descripteurs IGN] classification par réseau neuronal [Termes descripteurs IGN] filtrage du bruit [Termes descripteurs IGN] filtre de Kalman [Termes descripteurs IGN] GPS-INS [Termes descripteurs IGN] microsystème électromécanique [Termes descripteurs IGN] modèle d'incertitude [Termes descripteurs IGN] rapport signal sur bruit [Termes descripteurs 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]

Performance of BDS triple-frequency positioning based on the modified TCAR method / Yijun Tian in Survey review, vol 52 n° 374 (August 2020)  

Public [article]  inSurvey review > vol 52 n° 374 (August 2020) . - pp 415 - 422 Titre : Performance of BDS triple-frequency positioning based on the modified TCAR method Type de document : Article/Communication Auteurs : Yijun Tian, Auteur ; Lifen Sui, Auteur ; Dongqing Zhao, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 415 - 422 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie spatiale [Termes descripteurs IGN] compensation Lambda [Termes descripteurs IGN] filtre de Kalman [Termes descripteurs IGN] positionnement par BeiDou [Termes descripteurs IGN] précision du positionnement [Termes descripteurs IGN] résolution d'ambiguïté [Termes descripteurs IGN] retard ionosphèrique [Termes descripteurs IGN] triple différence Résumé : (auteur) A modified TCAR method to improve the NL ambiguity resolution over medium-long baseline is presented. The estimated DD ionospheric delay derived from the Kalman-filter floating solution is adopted to modify the floating NL ambiguities. Modified by the smooth DD ionospheric delay, the NL ambiguity residuals are mostly within 0.5 cycles over medium-long baselines, showing a significant improvement in contrast to the classical TCAR method. The positioning performances of the modified method are even better than the LAMBDA method over 72 and 634 km baselines. As the ambiguity can be correctly fixed just after several epochs, high-precision positioning can be achieved in a very short time. Numéro de notice : A2020-517 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/00396265.2019.1627507 date de publication en ligne : 12/06/2019 En ligne : https://doi.org/10.1080/00396265.2019.1627507 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95677 [article]

A robust total Kalman filter algorithm with numerical evaluation / Sida Li in Survey review, vol 52 n° 373 (July 2020)  

Public [article]  inSurvey review > vol 52 n° 373 (July 2020) . - pp 309 - 316 Titre : A robust total Kalman filter algorithm with numerical evaluation Type de document : Article/Communication Auteurs : Sida Li, Auteur ; Lintao Liu, Auteur ; Zhiping Liu, Auteur ; Guocheng Wang, Auteur Année de publication : 2020 Article en page(s) : pp 309 - 316 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Navigation et positionnement [Termes descripteurs IGN] filtre de Kalman [Termes descripteurs IGN] matrice [Termes descripteurs IGN] méthode des moindres carrés [Termes descripteurs IGN] méthode robuste [Termes descripteurs IGN] modèle d'erreur [Termes descripteurs IGN] précision du positionnement [Termes descripteurs IGN] valeur aberrante Résumé : (auteur) In this study, the observation model of Kalman Filter (KF) is extended to an errors-in-variables (EIV) model because the observations may exist in the design matrix of the observation model. Then, a robust total least squares method (RTLS) is introduced into the KF, and a robust total Kalman filter (RTKF) algorithm is derived. The RTKF is a simple, flexible and effective algorithm. It is simple because its computational formulae are similar to the computational formulae of a standard KF; it is flexible because it can be used in a wide range of applications; it is effective because the influence of outliers on estimated results is weakened. Finally, the simulated example of the indoor location and the empirical example of pseudorange differential positioning are used to demonstrate the performance of the RTKF algorithm. The results prove the validity, robustness, and reliability of the RTKF in dealing with the outliers that exist in both observation vector and design matrix of the EIV model. Furthermore, the results of the empirical example show that the RTKF improves the precision of a pseudorange differential positioning compared with KF and robust Kalman filter (RKF) algorithms regardless the observation model has outliers or not in this empirical example. Numéro de notice : A2020-457 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/00396265.2018.1563392 date de publication en ligne : 08/01/2019 En ligne : https://doi.org/10.1080/00396265.2018.1563392 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95556 [article]

Impact of temperature stabilization on the strapdown airborne gravimetry: a case study in Central Turkey / Mehmet Simav in Journal of geodesy, vol 94 n°4 (April 2020)  

Public [article]  inJournal of geodesy > vol 94 n°4 (April 2020) Titre : Impact of temperature stabilization on the strapdown airborne gravimetry: a case study in Central Turkey Type de document : Article/Communication Auteurs : Mehmet Simav, Auteur ; David Becker, Auteur ; Hasan Yildiz, Auteur ; Matthias Hoss, Auteur Année de publication : 2020 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie physique [Termes descripteurs IGN] accéléromètre [Termes descripteurs IGN] centrale inertielle à composants liés [Termes descripteurs IGN] contrôle thermique [Termes descripteurs IGN] étalonnage d'instrument [Termes descripteurs IGN] filtre de Kalman [Termes descripteurs IGN] gravimétrie aérienne [Termes descripteurs IGN] réalité de terrain [Termes descripteurs IGN] température [Termes descripteurs IGN] Turquie Résumé : (auteur) Airborne gravimetry with strapdown inertial sensors has been a valuable tool for many years to fill in the gravity data gaps on the areas not accessible by land. Accuracies of 1 mGal level with off-the-shelf navigation-grade inertial measurement units (IMU) can only be achieved provided that the accelerometer drifts mainly caused by the temperature variations inside the IMU housing are separated from the gravity signal. Although there are several strategies proposed in the literature to deal with this inseparability problem, we use a thermal stabilization system (iTempStab) added on an iNAT-RQH navigation-grade IMU and investigate its performance over a test region in central Turkey with moderate topography and highly qualified ground truth gravity data. Two test flights were performed in 2017 and 2018 with and without iTempStab add-on following almost the same flight trajectories. During the first flight in 2017 with iNAT-RQH only, which lasted almost 5.5 h, there were considerable temperature variations inside the IMU housing from 39.1 to 46.0 °C. A simple thermal correction based on a laboratory calibration done before the flight was applied to the vertical Z-accelerometer in the pre-processing stage. However, temperature changes were within 0.1 °C during the second test flight in 2018 with TempStab add-on. The temperature stabilization gained by the iTempStab add-on produced better cross-over statistics. While the RMSE of the non-adjusted cross-over residuals was about 2.6 mGal, it reduced by 50% with iTempStab add-on. The adjusted cross-over differences of the 2018 flight yielded an RMSE of about 0.5 mGal, which is a remarkable precision for the strapdown gravimetry. The comparison with upward continued ground gravity data at flight altitudes suggests that the thermal stabilization system shows also remarkable improvements in the residual statistics. The range of the residuals decreases from ± 10 to ± 5 mGal, the standard deviation decreases from 2.19 to 0.94 mGal, and the RMSE decreases from 2.24 to 1.48 mGal, respectively, with the iTempStab add-on. It can be concluded that the thermal stabilization system significantly improves the accelerometer stability and therefore the precision and accuracy of the strapdown airborne gravity estimates. Numéro de notice : A2020-158 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s00190-020-01369-5 date de publication en ligne : 17/03/2020 En ligne : https://doi.org/10.1007/s00190-020-01369-5 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94812 [article]

Performance of real-time undifferenced precise positioning assisted by remote IGS multi-GNSS stations / Zhiqiang Liu in GPS solutions, vol 24 n° 2 (April 2020)  

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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)  

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A sequential Monte Carlo framework for noise filtering in InSAR time series / Mehdi Khaki in IEEE Transactions on geoscience and remote sensing, vol 58 n° 3 (March 2020)  

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Smoothing and predicting celestial pole offsets using a Kalman filter and smoother / Jolanta Nastula in Journal of geodesy, Vol 94 n°3 (March 2020)  

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Assessment of inner reliability in the Gauss-Helmert model / Andreas Ettlinger in Journal of applied geodesy, vol 14 n° 1 (January 2020)  

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INS/GNSS integration using recurrent fuzzy wavelet neural networks / Parisa Doostdar in GPS solutions, vol 24 n° 1 (January 2020)  

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Kalman-filter-based undifferenced cycle slip estimation in real-time precise point positioning / Pan Li in GPS solutions, vol 23 n° 4 (October 2019)  

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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)  

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Robust M–M unscented Kalman filtering for GPS/IMU navigation / Cheng Yang in Journal of geodesy, vol 93 n° 8 (August 2019)  

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On the detectability of mis-modeled biases in the network-derived positioning corrections and their user impact / Amir Khodabandeh in GPS solutions, vol 23 n° 3 (July 2019)  

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