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Parallel computing for fast spatiotemporal weighted regression / Xiang Que in Computers & geosciences, vol 150 (May 2021)  

Public [article]  inComputers & geosciences > vol 150 (May 2021) . - n° 104723 Titre : Parallel computing for fast spatiotemporal weighted regression Type de document : Article/Communication Auteurs : Xiang Que, Auteur ; Chao Ma, Auteur ; Xiaogang Ma, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 104723 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] calcul matriciel [Termes IGN] étalonnage de modèle [Termes IGN] modèle de régression [Termes IGN] modélisation spatio-temporelle [Termes IGN] régression géographiquement pondérée [Termes IGN] traitement parallèle Résumé : (auteur) The Spatiotemporal Weighted Regression (STWR) model is an extension of the Geographically Weighted Regression (GWR) model for exploring the heterogeneity of spatiotemporal processes. A key feature of STWR is that it utilizes the data points observed at previous time stages to make better fit and prediction at the latest time stage. Because the temporal bandwidths and a few other parameters need to be optimized in STWR, the model calibration is computationally intensive. In particular, when the data amount is large, the calibration of STWR becomes heavily time-consuming. For example, with 10,000 points in 10 time stages, it takes about 2307 s for a single-core PC to process the calibration of STWR. Both the distance and the weighted matrix in STWR are memory intensive, which may easily cause memory insufficiency as data amount increases. To improve the efficiency of computing, we developed a parallel computing method for STWR by employing the Message Passing Interface (MPI). A cache in the MPI processing approach was proposed for the calibration routine. Also, a matrix splitting strategy was designed to address the problem of memory insufficiency. We named the overall design as Fast STWR (F-STWR). In the experiment, we tested F-STWR in a High-Performance Computing (HPC) environment with a total number of 204,611 observations in 19 years. The results show that F-STWR can significantly improve STWR's capability of processing large-scale spatiotemporal data. Numéro de notice : A2021-300 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/MATHEMATIQUE Nature : Article DOI : 10.1016/j.cageo.2021.104723 Date de publication en ligne : 05/03/2021 En ligne : https://doi.org/10.1016/j.cageo.2021.104723 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97413 [article]

Effects of a navigation spoofing signal on a receiver loop and a UAV spoofing approach / Chao Ma in GPS solutions, Vol 24 n° 3 (July 2020)  

Public [article]  inGPS solutions > Vol 24 n° 3 (July 2020) Titre : Effects of a navigation spoofing signal on a receiver loop and a UAV spoofing approach Type de document : Article/Communication Auteurs : Chao Ma, Auteur ; Jun Yang, Auteur ; Jianyun Chen, Auteur ; et al., Auteur Année de publication : 2020 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement du signal [Termes IGN] amplitude [Termes IGN] atténuation du signal [Termes IGN] autocorrélation [Termes IGN] drone [Termes IGN] erreur de phase [Termes IGN] interférence [Termes IGN] leurrage [Termes IGN] récepteur Doppler [Termes IGN] utilisateur civil Résumé : (auteur) A civil navigation signal is vulnerable to interference and tampering owing to its open interface and low signal power. We focus on navigation spoofing. First, using a piecewise function, we quantitatively analyze the effects of the navigation spoofing signal on the receiver tracking loop. For a phase-locked loop, the spoofing signal extends the pull-in range of the discriminator. The autocorrelation gain of the spoofing signal has a different effect on the slope of the discriminator, depending on whether the discriminator is related to the signal amplitude. For the delay-locked loop, taking the non-coherent early minus late power method as an example, the unlocking condition and interval are analyzed quantitatively using the spoofing amplitude gain and the initial phase cosine of the spoofing and authentic carriers. A carrier frequency difference between the spoofing signal and authentic signal causes a phase jump and attenuation of the amplitude gain. Second, in luring an unmanned aerial vehicle (UAV) to a designated location, we assume a UAV model and provide a spoofing strategy. Experimental results show that it is feasible to lure a civilian quadrotor UAV to a designated location about 50 m from where the UAV believes it is located. Numéro de notice : A2020-326 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueNat DOI : 10.1007/s10291-020-00986-z Date de publication en ligne : 09/05/2020 En ligne : https://doi.org/10.1007/s10291-020-00986-z Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95207 [article]

Adaptive correlation filters with long-term and short-term memory for object tracking / Chao Ma in International journal of computer vision, vol 126 n° 8 (August 2018)  

Public [article]  inInternational journal of computer vision > vol 126 n° 8 (August 2018) . - pp 771 - 796 Titre : Adaptive correlation filters with long-term and short-term memory for object tracking Type de document : Article/Communication Auteurs : Chao Ma, Auteur ; Jia-Bin Huang, Auteur ; Xiaokang Yang, Auteur ; Ming-Hsuan Yang, Auteur Année de publication : 2018 Article en page(s) : pp 771 - 796 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image [Termes IGN] détection d'objet [Termes IGN] filtre adaptatif [Termes IGN] méthode fondée sur le noyau [Termes IGN] méthode robuste [Termes IGN] poursuite de cible Résumé : (Auteur) Object tracking is challenging as target objects often undergo drastic appearance changes over time. Recently, adaptive correlation filters have been successfully applied to object tracking. However, tracking algorithms relying on highly adaptive correlation filters are prone to drift due to noisy updates. Moreover, as these algorithms do not maintain long-term memory of target appearance, they cannot recover from tracking failures caused by heavy occlusion or target disappearance in the camera view. In this paper, we propose to learn multiple adaptive correlation filters with both long-term and short-term memory of target appearance for robust object tracking. First, we learn a kernelized correlation filter with an aggressive learning rate for locating target objects precisely. We take into account the appropriate size of surrounding context and the feature representations. Second, we learn a correlation filter over a feature pyramid centered at the estimated target position for predicting scale changes. Third, we learn a complementary correlation filter with a conservative learning rate to maintain long-term memory of target appearance. We use the output responses of this long-term filter to determine if tracking failure occurs. In the case of tracking failures, we apply an incrementally learned detector to recover the target position in a sliding window fashion. Extensive experimental results on large-scale benchmark datasets demonstrate that the proposed algorithm performs favorably against the state-of-the-art methods in terms of efficiency, accuracy, and robustness. Numéro de notice : A2018-414 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s11263-018-1076-4 Date de publication en ligne : 16/03/2018 En ligne : https://doi.org/10.1007/s11263-018-1076-4 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90897 [article]

The impact of solid Earth-tide model error on tropospheric zenith delay estimates and GPS coordinate time series / Fei Li in Survey review, vol 50 n° 361 (July 2018)  

Public [article]  inSurvey review > vol 50 n° 361 (July 2018) . - pp 355 - 363 Titre : The impact of solid Earth-tide model error on tropospheric zenith delay estimates and GPS coordinate time series Type de document : Article/Communication Auteurs : Fei Li, Auteur ; Jintao Lei, Auteur ; Chao Ma, Auteur ; Weifeng Hao, Auteur ; et al., Auteur Année de publication : 2018 Article en page(s) : pp 355 - 363 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie physique [Termes IGN] coordonnées GPS [Termes IGN] erreur de modèle [Termes IGN] marée terrestre [Termes IGN] propagation du signal [Termes IGN] retard troposphérique zénithal [Termes IGN] série temporelle Résumé : (Auteur) Any unmodelled or mismodelled subdaily signals left in the model may not only affect the instantaneous site positions and the associated estimates, but also propagate into spurious seasonal signals, contaminating the daily coordinate time series. To demonstrate how subdaily ‘error’ in the modelling of the solid Earth-tide affects the estimates of tropospheric zenith total delay (ZTD) and how it propagates into long-period signal in the daily GPS time series, we analyse GPS observations collected between 2009 and 2013 for 13 sites in the coastal regions of Antarctica using the GAMIT/GLOBK 10.6 software. We find that ZTD differenced time series, with amplitude at 2 mm level, have inverse correlation with the input K1 correction, and the corresponding admittances range from 6% to 14%; Propagated spurious annual signals are evident in the vertical component of coordinate differenced time series, with amplitudes at the mm level and admittances of around 2–11%. Numéro de notice : A2018-444 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/00396265.2016.1277657 Date de publication en ligne : 12/01/2017 En ligne : https://doi.org/10.1080/00396265.2016.1277657 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91018 [article]