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Full-waveform classification and segmentation-based signal detection of single-wavelength bathymetric LiDAR / Xue Ji in IEEE Transactions on geoscience and remote sensing, vol 60 n° 8 (August 2022)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 60 n° 8 (August 2022) . - n° 4208714 Titre : Full-waveform classification and segmentation-based signal detection of single-wavelength bathymetric LiDAR Type de document : Article/Communication Auteurs : Xue Ji, Auteur ; Bisheng Yang, Auteur ; Yuan Wang, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 4208714 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] algorithme de Levenberg-Marquardt [Termes IGN] analyse comparative [Termes IGN] apprentissage automatique [Termes IGN] classification par réseau neuronal convolutif [Termes IGN] détection du signal [Termes IGN] forme d'onde pleine [Termes IGN] Hainan (Chine) [Termes IGN] lidar bathymétrique [Termes IGN] optimisation par essaim de particules Résumé : (auteur) Single-wavelength bathymetric light detection and ranging (LiDAR) (532 nm) can provide seamless meter- and submeter-scale digital elevation model (DEMs) of both the terrestrial surface and seafloor. However, mixed terrestrial and bathymetric surfaces obtained by this sensor are challenging for full-waveform (FW) signal detection. This study addresses the issues in two FW mixed surfaces: accurate classification of terrestrial and nonterrestrial waveforms from the original waveforms without auxiliary information and flexible detection of peaks based on a new FW theoretical model. A novel FW signal detection model (FWSD) for single-wavelength bathymetric LiDAR is proposed without complex feature extraction and iterative procedure through waveform classification and segmentation. The raw FWs are divided into five categories for subsequent signal detection using a convolutional neural network that merges local descriptors with contextual information. The signal detection task is then split into FW segment recognition and peak extraction using a new FW model, which integrates a leapfrog sliding window FW segmentation, an improved extreme learning machine (ELM) algorithm for FW segment recognition, and a flexible signal detection framework. To search for the optimal initial parameters for ELM, a self-annealing particle swarm optimization (SAPSO) algorithm is introduced, and the output weight is adjusted by online sequence to improve its generalization. When combined with the Richardson–Lucy deconvolution (RLD) algorithm, FWSD can be adapted to deal with shallow water waveforms. Finally, a test demonstration with an airborne dataset shows that FWSD has higher detection efficiency and higher accuracy than Levenberg–Marquardt algorithm optimized generalized Gaussian model (LM-GGM) and RLD algorithm. Numéro de notice : A2022-661 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2022.3198168 Date de publication en ligne : 11/08/2022 En ligne : https://doi.org/10.1109/TGRS.2022.3198168 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101517 [article]

Detection of GNSS no-line of sight signals using LiDAR sensors for intelligent transportation systems / Tarek Hassan in Survey review, vol 54 n° 385 (July 2022)  

Public [article]  inSurvey review > vol 54 n° 385 (July 2022) . - pp 301 - 309 Titre : Detection of GNSS no-line of sight signals using LiDAR sensors for intelligent transportation systems Type de document : Article/Communication Auteurs : Tarek Hassan, Auteur ; Tamer Fath-Allah, Auteur ; Mohamed Elhabiby, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 301 - 309 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement du signal [Termes IGN] détection du signal [Termes IGN] données lidar [Termes IGN] positionnement ponctuel précis [Termes IGN] semis de points [Termes IGN] signal GNSS [Termes IGN] système de transport intelligent [Termes IGN] traitement de données GNSS Résumé : (auteur) The reliability and robustness of positioning systems in urban and suburban environments are intrinsic. This is obvious following the continuous increase of Intelligent Transportation Systems (ITS) applications in such challenging environments. Global Navigation Satellite Systems (GNSS) represent the primary positioning technique used for navigation purposes in these applications, which can be satisfying in open-sky areas. However, GNSS cannot provide the same level of navigation performance in urban environments. One of the main reasons for this is the No-Line of Sight (NLOS) signals. In this study, the integration of GNSS and Light Detection and Ranging (LiDAR) sensors is exploited, and a new algorithm is proposed for the detection of NLOS signals. Real field data are used to test and validate the proposed strategy and algorithm. Phase-smoothed code observations are employed to evaluate the accuracy improvement after excluding the NLOS observations. The results show that the horizontal direction's positional accuracy can be improved significantly after applying the proposed algorithm. This improvement reaches 10.403 m with a mean value of 2.162 m (62.2% improvement) over all epochs with detected NLOS signals. After analysing this improvement in the Cross-Track (CT) and Along-Track (AT) directions, it is found that the accuracy improvement reaches 8.641 m with a mean value of 1.699 m in the CT direction and 6.879 m with a mean value of 1.303 m in the AT direction. Numéro de notice : A2022-535 Affiliation des auteurs : non IGN Thématique : IMAGERIE/POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/00396265.2021.1937458 Date de publication en ligne : 10/06/2021 En ligne : https://doi.org/10.1080/00396265.2021.1937458 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101091 [article]

Detection and mitigation of GNSS spoofing via the pseudorange difference between epochs in a multicorrelator receiver / Xiangyong Shang in GPS solutions, vol 26 n° 2 (April 2022)  

Public [article]  inGPS solutions > vol 26 n° 2 (April 2022) . - n° 37 Titre : Detection and mitigation of GNSS spoofing via the pseudorange difference between epochs in a multicorrelator receiver Type de document : Article/Communication Auteurs : Xiangyong Shang, Auteur ; Fuping Sun, Auteur ; Lundong Zhang, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 37 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement du signal [Termes IGN] anti-leurrage [Termes IGN] atténuation du signal [Termes IGN] brouillage [Termes IGN] détection de leurrage [Termes IGN] détection du signal [Termes IGN] filtre de Kalman [Termes IGN] mesurage de pseudo-distance [Termes IGN] méthode du maximum de vraisemblance (estimation) [Termes IGN] qualité du signal [Termes IGN] récepteur GNSS [Termes IGN] signal GNSS Résumé : (auteur) Spoofing attacks have become an increasing threat to global navigation satellite system receivers. Existing anti-spoofing algorithms concentrate on the detection of these attacks; however, they are unable to prevent the counterfeit signal, which causes false position and timing results. Some defense techniques require the assistance of other sensors or measurement devices located at different positions. These impose many restrictions on the practical applications of anti-spoofing algorithms. In this study, the multicorrelator estimator, designed initially to prevent multipath signals, is applied to detect and mitigate spoofing. A statistic is proposed for spoofing detection based on the code phase difference between counterfeit and authentic signals. This statistic can significantly reduce the rate of false and missed alarms. Assuming there is no spoofing at the beginning, the pseudorange difference between epochs is derived for spoofing validation, allowing spoofing suppression in a single receiver. Based on this study, an estimation-validation-mitigation structure is presented. A robust extended Kalman filter is proposed to reduce gross errors in the multicorrelator measurements and improve estimation accuracy. Public-spoofing datasets recorded in real environments were used to verify the performance of different parameters. A total of 81 complex correlators were introduced in the experiments. Results show that using the proposed scheme, the position or time offsets caused by spoofing drop from 600 m to approximately 20 m, and the spoofing is mitigated considerably. The proposed method provides an effective anti-spoofing structure that requires only a single antenna and does not require additional sensors. Numéro de notice : A2022-108 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article DOI : 10.1007/s10291-022-01224-4 Date de publication en ligne : 16/01/2022 En ligne : https://doi.org/10.1007/s10291-022-01224-4 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99610 [article]

Results on GNSS spoofing mitigation using multiple receivers / Niklas Stenberg in Navigation : journal of the Institute of navigation, vol 69 n° 1 (Spring 2022)  

Public [article]  inNavigation : journal of the Institute of navigation > vol 69 n° 1 (Spring 2022) . - n° 510 Titre : Results on GNSS spoofing mitigation using multiple receivers Type de document : Article/Communication Auteurs : Niklas Stenberg, Auteur ; Erik Axell, Auteur ; Jouni Rantakokko, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 510 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement du signal [Termes IGN] atténuation du signal [Termes IGN] bruit (théorie du signal) [Termes IGN] détection de leurrage [Termes IGN] détection du signal [Termes IGN] double différence [Termes IGN] erreur de phase [Termes IGN] leurrage [Termes IGN] mesurage de pseudo-distance [Termes IGN] récepteur GNSS Résumé : (auteur) GNSS receivers are vulnerable to spoofing attacks in which false satellite signals deceive receivers to compute false position and/or time estimates. This work derives and evaluates algorithms that perform spoofing mitigation by utilizing double differences of pseudorange or carrier phase measurements from multiple receivers. The algorithms identify pseudorange and carrier-phase measurements originating from spoofing signals, and omit these from the position and time computation. The algorithms are evaluated with simulated and live-sky meaconing attacks. The simulated spoofing attacks show that mitigation using pseudoranges is possible in these tests when the receivers are separated by five meters or more. At 20 meters, the pseudorange algorithm correctly authenticates six out of seven pseudoranges within 30 seconds in the same simulator tests. Using carrier phase allows mitigation with shorter distances between receivers, but requires better time synchronization between the receivers. Evaluations with live-sky meaconing attacks show the validity of the proposed mitigation algorithms. Numéro de notice : A2022-821 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article DOI : 10.33012/navi.510 En ligne : https://doi.org/10.33012/navi.510 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101989 [article]

Impact of forest disturbance on InSAR surface displacement time series / Paula M. Bürgi in IEEE Transactions on geoscience and remote sensing, vol 59 n° 1 (January 2021)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 59 n° 1 (January 2021) . - pp 128 - 138 Titre : Impact of forest disturbance on InSAR surface displacement time series Type de document : Article/Communication Auteurs : Paula M. Bürgi, Auteur ; Rowena B. Lohman, Auteur Année de publication : 2021 Article en page(s) : pp 128 - 138 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] changement d'occupation du sol [Termes IGN] déboisement [Termes IGN] détection de changement [Termes IGN] détection du signal [Termes IGN] erreur de phase [Termes IGN] erreur systématique [Termes IGN] image ALOS [Termes IGN] image radar moirée [Termes IGN] image Sentinel-SAR [Termes IGN] retard ionosphèrique [Termes IGN] retard troposphérique [Termes IGN] série temporelle [Termes IGN] Sumatra [Termes IGN] surveillance géologique Résumé : (auteur) As interferometric synthetic aperture radar (InSAR) data improve in their global coverage and temporal sampling, studies of ground deformation using InSAR are becoming feasible even in heavily vegetated regions such as the American Pacific Northwest (PNW) and Sumatra. However, ongoing forest disturbance due to logging, wildfires, or disease can introduce time-variable signals which could be misinterpreted as ground displacements. This study constrains the error introduced into InSAR time series in the presence of time-variable forest disturbance using synthetic data. For satellite platforms with randomly distributed orbital positions in time (e.g., Sentinel-1), mid-time series forest disturbance results in random error on the order of 0.2 and 10 cm/year for 1-year secular and time-variable velocities, respectively. If the orbital positions are not randomly distributed in time (e.g., ALOS-1), a biased error on the order of 10 cm/year is introduced to the inferred secular velocity. A time series using real ALOS-1 data near Eugene, OR, USA, shows agreement with the bias estimated by synthetic models. Mitigation of time-variable land cover change effects can be achieved if their timing is known, either through independent observations of surface properties (e.g., Landsat/Sentinel-2) or through the use of more computationally expensive, nonlinear inversions with additional terms for the timing of height changes. Inclusion of these additional terms reduces the potential for misinterpretation of InSAR signals associated with land surface change as ground deformation. Numéro de notice : A2021-032 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2020.2992938 Date de publication en ligne : 18/05/2020 En ligne : https://doi.org/10.1109/TGRS.2020.2992938 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96727 [article]

Bayesian-deep-learning estimation of earthquake location from single-station observations / S. Mostafa Mousavi in IEEE Transactions on geoscience and remote sensing, vol 58 n° 11 (November 2020)  

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Improved indoor positioning based on range-free RSSI fingerprint method / Marcin Uradzinski in Journal of geodetic science, vol 10 n° 1 (January 2020)  

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Uncertainty in radar emitter classification and clustering / Guillaume Revillon (2019)  

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Automatic recognition of long period events from volcano tectonic earthquakes at Cotopaxi volcano / Román A. Lara-Cueva in IEEE Transactions on geoscience and remote sensing, vol 54 n° 9 (September 2016)  

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Signal Processing / Charles L. Byrne (2014)  

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Amélioration de la position GNSS en ville par la méthode des tranchées urbaines / M. Voyer in Géomatique expert, n° 93 (01/07/2013)

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GNSS spoofing detection: Correlating carrier phase with rapid antenna motion / Mark Psiaki in GPS world, vol 24 n° 6 (June 2013)  

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Single-receiver single-channel multi-frequency GNSS integrity: outliers, slips, and ionospheric disturbances / Peter J.G. Teunissen in Journal of geodesy, vol 87 n° 2 (February 2013)  

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A first set of techniques to detect radio frequency interferences and mitigate their impact on SMOS data / R. Castro in IEEE Transactions on geoscience and remote sensing, vol 50 n° 5 Tome 1 (May 2012)  

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GNSS antenna orientation based on modification of received signal strengths / David Eugen Grimm (2012)  

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