12 research outputs found

    Asymptotically efficient GNSS trilateration

    Get PDF
    Localization based on the reception of radio-frequency waveforms is a crucial problem in many civilian or military applications. It is also the main objective of all Global Navigation Satellite System (GNSS). Given delayed and Doppler shifted replicas of the satellites transmitted signals, the most widespread approach consists in a suboptimal two-step procedure. First, estimate the delays and Dopplers from each satellite independently, then estimate the user position and speed thanks to a Least Square (LS) minimization. More accurate and robust techniques, such as a direct Maximum Likelihood (ML) maximization, that exploit the links in between the different channels exist but suffer from an heavy computational burden that prevent their use in real time applications. Two-steps procedures with an appropriate Weighted LS (WLS) minimization are shown to be asymptotically equivalent to the ML procedure. In this paper, we develop a closed-form expression of this WLS asymptotically efficient solution. We show that this simple expression is the sum of two terms. The first one, depending on the pseudo-ranges is the widespread used WLS solution. The second one is a Doppler-aided corrective term that should be taken into account to improve the position estimation when the observation time increases

    A New GNSS Integrity Monitoring Based on Channels Joint Characterization

    Get PDF
    Many GNSS (Global Navigation Satellites System) applications need high integrity performances. Receiver Autonomous Integrity Monitoring (RAIM), or similar method, is commonly used. Initially developed for aeronautics, RAIM techniques may not be fully adapted for terrestrial navigation, especially in urban environments. Those techniques use basically the pseudoranges to derive an integrity criterion. In this paper, we introduce a new integrity criterion based on the correlation quality of each channel. This quality assessment is computed from the correlation levels for each channel, all based on a single position and speed. Hence, as the so-called Direct Position Estimation (DPE), we exploit the joint behaviour of all channels to detect any incoherence at an upstream step of the processing. This Direct RAIM (D-RAIM) allows detecting possible integrity problems before it can be seen on a classical RAIM scheme that only exploits the outputs of each channel

    Implementation and evaluation of the Level Set method: towards efficient and accurate simulation of wet etching for microengineering applications

    Full text link
    The use of atomistic methods, such as the Continuous Cellular Automaton (CCA), is currently regarded as a computationally efficient and experimentally accurate approach for the simulation of anisotropic etching of various substrates in the manufacture of Micro-electro-mechanical Systems (MEMS). However, when the features of the chemical process are modified, a time-consuming calibration process needs to be used to transform the new macroscopic etch rates into a corresponding set of atomistic rates. Furthermore, changing the substrate requires a labor-intensive effort to reclassify most atomistic neighborhoods. In this context, the Level Set (LS) method provides an alternative approach where the macroscopic forces affecting the front evolution are directly applied at the discrete level, thus avoiding the need for reclassification and/or calibration. Correspondingly, we present a fully-operational Sparse Field Method (SFM) implementation of the LS approach, discussing in detail the algorithm and providing a thorough characterization of the computational cost and simulation accuracy, including a comparison to the performance by the most recent CCA model. We conclude that the SFM implementation achieves similar accuracy as the CCA method with less fluctuations in the etch front and requiring roughly 4 times less memory. Although SFM can be up to 2 times slower than CCA for the simulation of anisotropic etchants, it can also be up to 10 times faster than CCA for isotropic etchants. In addition, we present a parallel, GPU-based implementation (gSFM) and compare it to an optimized, multicore CPU version (cSFM), demonstrating that the SFM algorithm can be successfully parallelized and the simulation times consequently reduced, while keeping the accuracy of the simulations. Although modern multicore CPUs provide an acceptable option, the massively parallel architecture of modern GPUs is more suitable, as reflected by computational times for gSFM up to 7.4 times faster than for cSFM. (c) 2013 Elsevier B.V. All rights reserved.We thank the anonymous reviewers for their valuable comments and suggestions. This work has been supported by the Spanish FPI-MICINN BES-2011-045940 grant and the Ramon y Cajal Fellowship Program by the Spanish Ministry of Science and Innovation. Also, we acknowledge support by the JAE-Doc grant from the Junta para la Ampliacion de Estudios program co-funded by FSE and the Professor Partnership Program by NVIDIA Corporation.Montoliu Álvaro, C.; Ferrando Jódar, N.; Gosalvez, MÁ.; Cerdå Boluda, J.; Colom Palero, RJ. (2013). Implementation and evaluation of the Level Set method: towards efficient and accurate simulation of wet etching for microengineering applications. Computer Physics Communications. 184(10):2299-2309. https://doi.org/10.1016/j.cpc.2013.05.016S229923091841

    Exploitation of the GNSS signals for integrity measurement

    No full text
    Dans le cadre des systĂšmes de positionnement par satellite GNSS (« Global Navigation Satellite Systems »), l’intĂ©gritĂ©de la navigation d’un utilisateur est gĂ©rĂ©e en rĂ©ception par la dĂ©tection, l’identification voire l’exclusion de mesures depseudo-distance jugĂ©es erronĂ©es. GĂ©nĂ©ralement basĂ©s sur le concept a posteriori RAIM (« Receiver Autonomous IntegrityMonitoring »), les algorithmes de contrĂŽle autonome d’intĂ©gritĂ© fournissent de hautes performances pour l’aviation civile,dont le contexte de navigation est caractĂ©risĂ© par une forte visibilitĂ© des satellites et peu de signaux parasites captĂ©spar l’antenne rĂ©ceptrice. L’algorithme WLSR RAIM est communĂ©ment utilisĂ© dans ce cadre. NĂ©anmoins, les techniquesRAIM ne sont pas compatibles avec la navigation terrestre en milieu contraint. En effet, le contexte urbain est notammentcaractĂ©risĂ© par un masquage rĂ©current des signaux satellitaires directs ainsi que la rĂ©ception de multi-trajets gĂ©nĂ©rĂ©s parl’environnement proche du rĂ©cepteur. RAIM ne prend pas en compte l’ensemble des donnĂ©es disponibles en rĂ©ception,dĂ©gradant ainsi fortement ses performances. Il est donc nĂ©cessaire de dĂ©velopper des mĂ©thodes de contrĂŽle d’intĂ©gritĂ©compatibles avec un tel contexte de navigation. Pour cela, la thĂšse propose d’étudier l’apport d’informations GNSS a priorinon utilisĂ©es par les techniques RAIM. Deux paramĂštres principaux ont Ă©tĂ© exploitĂ©s : le signal GNSS brut reçu et lesestimations de directions d’arrivĂ©e des signaux satellitaires DOA (« Direction Of Arrival »). La premiĂšre Ă©tape a consistĂ© Ă  implĂ©menter une mĂ©thode a priori qui Ă©value la cohĂ©rence du positionnement estimĂ© par rapport au signal brut directement reçu. Cette mĂ©thode a Ă©tĂ© nommĂ©e Direct-RAIM (D-RAIM) et a dĂ©montrĂ© une forte sensibilitĂ© de dĂ©tection, permettant d’anticiper d’éventuels risques sur la navigation et de caractĂ©riser plus finement la qualitĂ© de l’environnement proche du rĂ©cepteur. Toutefois, le caractĂšre a priori de l’approche engendre de potentielles non dĂ©tection d’erreurs en cas de modĂšle de signal dĂ©fectueux. Afin de contourner cette limitation, un couplage WLSRRAIM – D-RAIM a Ă©tĂ© dĂ©veloppĂ©, nommĂ© Hybrid-RAIM (H-RAIM). Une telle approche permet de combiner robustesse etsensibilitĂ© apportĂ©es par ces techniques respectives. Le second axe de recherche a mis en Ă©vidence la contribution de l’information des DOA dans un contrĂŽle autonome d’intĂ©gritĂ©. L’intĂ©gration d’un rĂ©seau d’antennes en rĂ©ception permet d’obtenir l’estimation des DOA pour l’ensemble dela constellation visible. ThĂ©oriquement, l’évolution jointe des DOA est directement liĂ©e Ă  l’attitude du rĂ©seau. Cet aspectpermet donc de dĂ©tecter toute incohĂ©rence sur une ou plusieurs voies en cas d’estimation(s) de DOA biaisĂ©e(s), par rapportĂ  l’ensemble de la constellation. L’algorithme RANSAC (« RANdom SAmple Consensus») a Ă©tĂ© utilisĂ© afin de dĂ©tecter toutcomportement aberrant dans l’estimation des DOA, et ainsi mesurer la confiance que l’utilisateur peut placer dans chaquevoie. L’algorithme WLSR RAIM RANSAC a ainsi Ă©tĂ© implĂ©mentĂ©. L’intĂ©gration de la composante DOA permet d’ajouterun degrĂ© de libertĂ© dans le contrĂŽle autonome d’intĂ©gritĂ© cĂŽtĂ© rĂ©cepteur et ainsi d’affiner la dĂ©tection voire l’exclusiond’erreurs. Au cours de cette thĂšse, un rĂ©cepteur logiciel a Ă©tĂ© implĂ©mentĂ©, permettant de traiter des signaux Galileo, de lagĂ©nĂ©ration du signal jusqu’au positionnement puis au contrĂŽle d’intĂ©gritĂ©. Ce rĂ©cepteur a pu ĂȘtre Ă©valuĂ© Ă  partir de donnĂ©essimulĂ©es en environnement urbain.In Global Navigation Satellite Systems (GNSS) applications, integrity is managed at the reception side by detection,identification and exclusion of faulty pseudorange measurements. Usually based on the a posteriori Receiver AutonomousIntegrity Monitoring (RAIM) concept, integrity techniques provide high performances for civil aviation, with a navigationcontext defined by a clear-sky environment. WLSR RAIM is commonly used. Nevertheless, RAIM techniques are notcompatible with a terrestrial navigation in harsh environments. For instance, urban areas are characterized by a poorvisibility and the reception of many multipaths derived from the receiver closed-environment. RAIM does not consider allthe available data in the reception chain, which dramatically deteriorates the detection performances. Hence, it is necessaryto develop integrity process compatible with such a navigation context. This PhD work studies the contribution of GNSSa priori information, disused by conventional RAIM techniques. Two main parameters have been exploited : the receivedraw GNSS signal and the Directions Of Arrival (DOA) estimations.This first step was devoted to the development of an a priori method which evaluates the consistence of the estimatedPosition Velocity Time (PVT) vector of the receiver with respect to the raw GNSS signal. This method has been calledDirect-RAIM (D-RAIM) and has shown high detection sensitivity, allowing the user to anticipate navigation risks and todefine precisely the quality of the receiver closed-environment. However, the a priori aspect of this approach may lead tonavigation error missed detections if the signal model is getting flawed. In order to circumvent this limitation, a WLSRRAIM – D-RAIM coupling has been developed, called Hybrid-RAIM (H-RAIM). Such an approach merges the robustnessand the sensitivity brought by both techniques.The second research step has brought to light the contribution of the DOA information in an autonomous integritymonitoring. Using an antenna array, the user can get the DOA estimations for all satellites in view. Theoretically, the DOAjoint evolution is directly correlated with the array rotation angles. Hence, any mismatch on the DOA estimations withrespect to the global constellation can be detected. RANdom Sample Consensus (RANSAC) algorithm has been used inorder to detect any faulty DOA evolution, derived from inconsistencies in reception linked to potential navigation risks :RANSAC measures the trust that the user can place in each channel. Therefore, a WLSR RAIM RANSAC algorithmhas been developed. The integration of the DOA component adds a degree of freedom in receiver autonomous integritymonitoring, refining the error detection and exclusion.Last but not least, a software receiver has been implemented processing Galileo data, from the signal generation to positioningand integrity monitoring. This software has been evaluated by simulated data characterizing urban environments

    Mesure d’intĂ©gritĂ© par l’exploitation des signaux de navigation par satellites.

    No full text
    In Global Navigation Satellite Systems (GNSS) applications, integrity is managed at the reception side by detection, identification and exclusion of faulty pseudorange measurements. Usually based on the a posteriori Receiver Autonomous Integrity Monitoring (RAIM) concept, integrity processes provide high performances for civil aviation, with a navigation context defined by a clear-sky environment. WLSR RAIM is generally used as a reference technique. Nevertheless, RAIM techniques are not compatible with a terrestrial navigation in harsh environments. For instance, urban areas are characterized by a poor visibility and the reception of many multipaths derived from the receiver closed-environment. RAIM does not consider all the available data in the reception chain and its performances dramatically deteriorate. Hence, it is necessary to develop integrity processes compatible with such a navigation context. This PhD work studies the contribution of GNSS information, disused by conventional RAIM techniques. Two main parameters have been exploited: the received raw GNSS signal and the Directions Of Arrival (DOA) estimations.This first step was devoted to the development of an a priori method evaluation the coherence of the estimated Position Velocity Time (PVT) vector of the receiver with respect to the raw 3 GNSS signal. This method has been called Direct-RAIM (D-RAIM) and has shown high detection sensitivity, allowing the user to anticipate navigation risks and to define precisely the quality of the receiver closed-environment. However, the a priori aspect of this approach may lead to navigation error non detections if the signal model is getting flawed. In order to circumvent this limitation, a WLSR RAIM – D-RAIM coupling has been developed called Hybrid-RAIM (HRAIM). Such an approach merges the robustness and the sensitivity brought by both techniques. The second research step has brought to light the contribution of the DOA information in an autonomous integrity monitoring. Using an antenna array, the user can get the DOA estimations for all satellites in view. Theoretically, the DOA joint evolution is directly correlated with the array rotation angles. Hence, any mismatch on the DOA estimations with respect to the global constellation can be detected. RANdom Sample Consensus (RANSAC) algorithm has been used in order to detect any faulty DOA evolution, derived from inconsistencies in reception linked to potential navigation risks. Therefore, RANSAC measures the trust that the user can place in each channel. Hence, a WLSR RAIM RANSAC algorithm has been developed. The integration of the DOA component adds a degree of freedom in receiver autonomous integrity monitoring, refining the error detection and exclusion.Last but not least, a software receiver has been implemented processing Galileo data, from the signal generation to positioning and integrity monitoring. This software has been evaluated by simulated data characterizing urban environments.Dans le cadre des systĂšmes de positionnement par satellite GNSS (« Global Navigation Satellite Systems »), l’intĂ©gritĂ© de la navigation d’un utilisateur est gĂ©rĂ©e en rĂ©ception par la dĂ©tection, l’identification voire l’exclusion de mesures de pseudo-distance jugĂ©es erronĂ©es. GĂ©nĂ©ralement basĂ©s sur le concept a posteriori RAIM (« Receiver Autonomous Integrity Monitoring »), les algorithmes de contrĂŽle autonome d’intĂ©gritĂ© fournissent de hautes performances pour l’aviation civile, dont le contexte de navigation est caractĂ©risĂ© par une forte visibilitĂ© des satellites et peu de signaux parasites captĂ©s par l’antenne rĂ©ceptrice. L’algorithme WLSR RAIM est rĂ©guliĂšrement utilisĂ© en tant que technique de rĂ©fĂ©rence. NĂ©anmoins, les techniques RAIM ne sont pas compatibles avec une navigation terrestre en milieu contraint. En effet, le contexte urbain est notamment caractĂ©risĂ© par un masquage rĂ©current des signaux satellitaires directs ainsi que la rĂ©ception de multi-trajets gĂ©nĂ©rĂ©s par l’environnement proche du rĂ©cepteur. RAIM ne prend pas en compte l’ensemble des donnĂ©es disponibles en rĂ©ception, dĂ©gradant ainsi fortement ses performances. Il est donc nĂ©cessaire de dĂ©velopper des mĂ©thodes de contrĂŽle d’intĂ©gritĂ© compatibles avec un tel contexte de navigation. Pour cela, la thĂšse propose d’étudier l’apport d’informations GNSS non utilisĂ©es par les techniques RAIM. Deux paramĂštres principaux ont Ă©tĂ© exploitĂ©s : le signal GNSS brut reçu et les estimations de directions d’arrivĂ©e des signaux satellitaires DOA (« Direction Of Arrival »).La premiĂšre Ă©tape a consistĂ© Ă  implĂ©menter une mĂ©thode a priori qui Ă©value la cohĂ©rence du positionnement estimĂ© par rapport au signal brut directement reçu. Cette mĂ©thode a Ă©tĂ© nommĂ©e Direct-RAIM (D-RAIM) et a dĂ©montrĂ© une forte sensibilitĂ© de dĂ©tection, permettant d’anticiper d’éventuels risques sur la navigation et de caractĂ©riser plus finement la qualitĂ© de l’environnement proche du rĂ©cepteur. Toutefois, le caractĂšre a priori de l’approche engendre de potentielles non dĂ©tection d’erreurs de navigation en cas de modĂšle de signal dĂ©fectueux. Afin de contourner cette limitation, un couplage WLSR RAIM – D-RAIM a Ă©tĂ© dĂ©veloppĂ©, nommĂ© Hybrid-RAIM (H-RAIM). Une telle approche permet de combiner robustesse et sensibilitĂ© apportĂ©es par ces techniques respectives. Le second axe de recherche a mis en Ă©vidence la contribution de l’information des DOA dans un contrĂŽle autonome d’intĂ©gritĂ©. L’intĂ©gration d’un rĂ©seau d’antennes en rĂ©ception permet d’obtenir l’estimation des DOA pour l’ensemble de la constellation visible. ThĂ©oriquement, l’évolution jointe des DOA est directement liĂ©e Ă  l’attitude du rĂ©seau. Cet aspect permet donc de dĂ©tecter toute incohĂ©rence sur une ou plusieurs voies en cas d’estimation(s) de DOA biaisĂ©e(s), par rapport Ă  l’ensemble de la constellation. L’algorithme robuste RANSAC (« RANdom SAmple Consensus») a Ă©tĂ© utilisĂ© afin de dĂ©tecter tout comportement aberrant dans l’estimation des DOA, et ainsi mesurer la confiance que l’utilisateur peut placer dans chaque voie. L’algorithme WLSR RAIM RANSAC a ainsi Ă©tĂ© implĂ©mentĂ©. L’intĂ©gration de la composante DOA permet d’ajouter un degrĂ© de libertĂ© dans le contrĂŽle autonome d’intĂ©gritĂ© cĂŽtĂ© rĂ©cepteur et ainsi d’affiner la dĂ©tection voire l’exclusion d’erreurs.Au cours de cette thĂšse, un rĂ©cepteur logiciel a Ă©tĂ© implĂ©mentĂ©, permettant de traiter des signaux Galileo, de la gĂ©nĂ©ration du signal jusqu’au positionnement puis au contrĂŽle d’intĂ©gritĂ©. Ce rĂ©cepteur a pu ĂȘtre Ă©valuĂ© Ă  partir de donnĂ©es simulĂ©es en environnement urbain

    Bon usage du médicament par voie orale (influence des modifications de la pharmacocinétique)

    No full text
    BORDEAUX2-BU Santé (330632101) / SudocSudocFranceF

    A kinetic formulation of piezoresistance in N-type silicon: Application to non-linear effects

    No full text
    This paper is devoted to the theoretical study of the influence of the temperature and of the doping on the piezoresistance of N-type silicon. In the first step the fractional change in the resistivity caused by stresses is calculated in the framework of a multivalley model using a kinetic transport formulation based on the Boltzmann transport equation. In the second step shifts in the minima of the conduction band and the resulting shift of the Fermi level are expressed in terms of deformation potentials and of stresses. General expressions for the fundamental linear, π11 and π12, and non-linear, π111, π112, π122 and π123, piezoresistance coefficients are then derived. Plots of the non-linear piezoresistance coefficients against the reduced shift of the Fermi level or against temperature allow us to characterize the influence of doping and temperature. Finally some attempts are made to estimate the non-linearity for heavily doped semiconductor gauges
    corecore