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This article is dedicated to the estimation of the amplitudes of GNSS satellites signals and, consequently, to their Signal to Noise Ratio. The in-phase component calculated by a one bit quantization receiver is a direct observation of the amplitude. In this article we propose a linear model that links 1 ms rate observations of the in-phase component of a GNSS receiver with the amplitudes of the received satellites signals. This model integrates the CDMA code and the carrier of the signals of all the satellites in view, thus considering the signals cross-correlations. A Kalman filter is designed in order to estimate the amplitudes of these signals at high rate.The proposed amplitude estimator is applied to GNSS-Reflectometry for retrieving the reflection coefficient of Earth surfaces. A set of experiments have been conducted for estimating a variety of sand moistures on a beach. It is shown that the proposed high-rate amplitude estimator can be of particular importance for kinematic GNSS-R setups.

One of the main problem in maneuver detection in angle-only observation applications is the model change during the maneuver that creates a peak in the estimate error. We propose in this paper to estimate a vehicle’s heading using a Circular IMM defined in the bayesian framework and using the von Mises distribution. The performances of this novel filter is compared with a circular filter and a classical Kalman Filter in a Y shape road.

Lock-in amplification (LIA) is an effective approach for recovery of weak signal buried in noise. Determination of the input signal amplitude in a classical dual-phase LIA is based on incoherent detection which leads to a biased estimation at low signal-to-noise ratio. This article presents, for the first time to our knowledge, a new architecture of LIA involving phase estimation with a linear-circular regression for coherent detection. The proposed phase delay estimate, between the input signal and a reference, is defined as the maximum-likelihood of a set of observations distributed according to a von Mises distribution. In our implementation this maximum is obtained with a Newton Raphson algorithm. We show that the proposed LIA architecture provides an unbiased estimate of the input signal amplitude. Theoretical simulations with synthetic data demonstrate that the classical LIA estimates are biased for SNR of the input signal lower than −20 dB, while the proposed LIA is able to accurately recover the weak signal amplitude. The novel approach is applied to an optical sensor for accurate measurement of NO 2 concentrations at the sub-ppbv level in the atmosphere. Side-by-side intercomparison measurements with a commercial LIA (SR830, Stanford Research Inc., Sunnyvale, CA, USA ) demonstrate that the proposed LIA has an identical performance in terms of measurement accuracy and precision but with simplified hardware architecture.

This article is dedicated to the design of a linear-circular regression technique and to its application to ground-based GNSS-Reflectometry (GNSS-R) altimetry. The altimetric estimation is based on the observation of the phase delay between a GNSS signal sensed directly and after a reflection off of the Earth’s surface. This delay evolves linearly with the sine of the emitting satellite elevation, with a slope proportional to the height between the reflecting surface and the receiving antenna. However, GNSS-R phase delay observations are angular and affected by a noise assumed to follow the von Mises distribution. In order to estimate the phase delay slope, a linear-circular regression estimator is thus defined in the maximum likelihood sense. The proposed estimator is able to fuse phase observations obtained from several satellite signals. Moreover, unlike the usual unwrapping approach, the proposed estimator allows the sea-surface height to be estimated from datasets with large data gaps. The proposed regression technique and altimeter performances are studied theoretically, with further assessment on both synthetic and real data.

This study concerns the implementation of an underwater positioning system in shallow water environment. Shallow water localization of the beacon is done by using the propagation of acoustic signals in water. The experiment is based on the use of a boat equipped with two hydrophones and an emitting beacon. The signal received on each sensors are processed to compute the difference in time arrival between them (TDOA) and to derive the boat location. In this paper a close loop architecture is proposed to process the signal. This architecture based on a Kalman filter allows to track the peaks of correlation in a delay Doppler map. Underwater tests are done to validate the method. They lead to a precision of about one meter.

In this article, we propose a circular change-point detector for on-line processing of the phase and the frequency of a GPS-L1 signal. The aims of this processing are to get an accurate estimation of the phase and to use it to get centimeter precise position estimates every millisecond. We propose to track the phase of the GPS signal in an open loop and the frequency in a semi-open loop. In an open loop, the phase delay evolves as a circular random variable. Furthermore, the phase is subject to cycle slips. These abrupt changes must be detected and repaired. We propose a circular generalized likelihood test for the on-line detection of changes in the phase measurements. With the estimation and detection being non-linear, we propose a particle filter defined according to the circular von Mises distribution for the estimation of the phase and frequency. The proposed architecture is assessed using synthetic and real data.

This article presents the implementation of an indoor localization approach that combines map matching and a circular particle filter defined in a Bayesian framework. The technique relies only on velocity and heading observations coupled with a map of the road network. No prior knowledge of the initial position is given. A circular distribution is used to match the vehicle's heading with the roads direction. This allows to detect turns and provide a more accurate position estimate. The algorithm is assessed with a synthetic dataset in a real context.

This article presents a new estimator of the pseudorange between a global navigation satellite systems (GNSS) satellite and a stand-alone receiver, and its application to GNSS-reflectometry (GNSS-R) altimetry. In our approach, we use as independent observations the difference between the code delay provided by successive acquisitions of the GNSS signal and the code delay truncated using the phase and Doppler information. We show that the mean value of these observations is an estimate of the first pseudorange of the observed time series. The ability of the proposed estimator to provide the centimeter accuracy is theoretically evaluated. In ground-based altimetry applications using GNSS signals, the direct pseudorange and the pseudorange associated to the reflected signal can be assumed to have the same dynamic evolution. Based on this assumption, the proposed estimate uses as observations the difference between the code delays obtained by successive acquisitions of both signals, without using phase measurement. The assessment of the method for ground-based GNSS-R is realized with real data.

GNSS-R techniques use direct and reflected signals coming from GNSS satellites to characterize the reflecting surface. In altimetry applications, the height of the surface is derived from the path difference between these two signals. The aim of this article is to propose a receiver architecture for high rate estimation of this path difference using an Interference Pattern Technique. An original receiver front-end architecture is presented, aiming at providing noisy observations of a non-linear function of the height. In order to invert this non-linear observation function and to smooth the height estimation, a particle filter is used. The proposed approach is assessed on synthetic data.

Classical GPS/Acoustic positioning techniques using ranging position location in low depth environment suffer from the bad system geometry. The aim of this article is to propose a new hyperbolic position location technique that takes into account the system geometry. In our approach we process the position with the normal distribution of the beacon location defined as a sum of uniform distributions. A uniform distribution is derived from the surface of possible beacon localizations obtained with approximations of the hyperbolic approach in the case of noisy observations and for two boat positions. These surfaces increase when the geometry of the system is degraded and the probability in these cases decreases. These lower probabilities allow to minimize the influence of the bad geometry configuration in the finale estimation process. The proposed method is assessed on synthetic data and compared to the classical ranging approach.

We present in this article a Bayesian estimation method for the joint segmentation of a set of piecewise stationary processes. The estimate we propose is based on the maximization of the posterior distribution of the change instants conditionally to the process parameter estimation. It is defined as a penalized contrast function with a first term related to the fit to the observation and a second term of penalty. The expression of the contrast function is deduced from the log-likelihood of the parametric distribution that models the statistic evolution of processes in the stationary segments. In the case of joint segmentation the penalty term is deduced from the prior law of change instants. It is composed of parameters that guide the number and the position of changes and of parameters that will bring prior information on the joint behavior of processes. This work is applied to the estimation of wind statistics parameters. We use data available from a cup anemometer and a wind vane, supposed to be piecewise stationary. The contrast function is deduced from the circular Von Mises distribution for the wind direction and from the log-normal distribution for the speed. The feasibility and the contribution of our method are shown on synthetic and real data.

The works presented in this paper deals with the design of a navigation system which is based on the fusion of information coming from a multi-frequencies GPS receiver, an odometer and a gyroscope. We present the design of a tracking fusion filter for the future multi-carrier G.P.S signal. This filter is an hybrid GPS/dead-reckoning fusion system that overcome the problem of reduced satellite visibility. In this system the estimation of the distance and speed between the satellite and the vehicle is realized with a Kalman track fusion algorithm. This algorithm is inspired from the modified track-to-track algorithm, the observations of pseudo distances are merged with a measurement fusion algorithm and the measurements of distances and speeds are fused with a state vector fusion Kalman filter. The simulation results obtained on synthetic data show the feasibility of the method and the contribution of the fusion over the accuracy and continuity of the localization.

The works presented in this paper deals with the design of a tracking fusion filter for the future multi-carrier G.P.S signal. The estimation of the distance and speed between the satellite and the G.P.S receiver is realized with a Kalman track fusion algorithm. In this system, inspired from the modified track-to-track algorithm, the observations are merged with a measurement fusion algorithm and the estimates are fused with a state vector fusion Kalman filter. This hybrid model can fuse the measurement obtained from the three frequencies of the future G.P.S. system. It can also fuse the state vectors that describe distances and speed which are supposed to come from different sensors. The simulation results obtained on synthetic data show the feasibility of the method and the contribution of the fusion over the localization accuracy.

Global Navigation Satellite Systems signals can be used in bi-static radar systems in order to get altimetric measurements. With a single classic GNSS ground-based receiver processing the combination of the signals coming directly and after one reflection to the receiving antennas, the Interference Pattern Technique allows the computation of the height of the reflecting surface. In this case, the observed parameter is the Signal to Noise Ratio of the received composite signal, which oscillates at a frequency proportional to this height. However, the signal recordings are generally very long since the accuracy of the SNR frequency estimation is proportional to the variation of the satellite elevation during the observation interval. In this article, we propose a calibration technique that allows reducing the observation duration while keeping a centimeter accuracy performance. The proposed technique is tested on both synthetic and real data.

In many multi-sensor applications, noisy angular data are modeled as random variables which are commonly defined on the linear domain while the ''classical fusion and filtering'' are used to process their realizations. Weighted sum and Kalman filter are indeed the common approaches used to fuse and filter the data in most cases. These approaches are limited by the periodic nature of the angular data. In this article, the error of angular measurements is assumed to follow a von Mises distribution. Under this assumption, a multi-sensor fusion operator is proposed. Under the same assumption, a recursive circular filter that provides estimates of the parameters of a model state is proposed. The proposed methodology is assessed using both synthetic and real data. The real data are obtained from a magnetometer and a gyroscope.

It is well known that reflected signals from Global Navigation Satellite Systems (GNSS) can be used for altimetry applications, such as monitoring of water levels and determining snow height. Due to the interference of these reflected signals and the motion of satellites in space, the signal-to-noise ratio (SNR) measured at the receiver slowly oscillates. The oscillation rate is proportional to the change in the propagation path difference between the direct and reflected signals, which depends on the satellite elevation angle. Assuming a known receiver position, it is possible to compute the distance between the antenna and the surface of reflection from the measured oscillation rate. This technique is usually known as the interference pattern technique (IPT). In this paper, we propose to normalize the measurements in order to derive an alternative model of the SNR variations. From this model, we define a maximum likelihood estimate of the antenna height that reduces the estimation time to a fraction of one period of the SNR variation. We also derive the Cramer–Rao lower bound for the IPT and use it to assess the sensitivity of different parameters to the estimation of the antenna height. Finally, we propose an experimental framework, and we use it to assess our approach with real GPS L1 C/A signals.

Map matching is the process of finding a match for each GPS point in a vehicle's trajectory to roads on a digital map. Extensive research has been conducted during the last years yielding many algorithms based on different approaches. One of the challenges that face those algorithms is the interruption of GPS signals that occurs specially in dense urban environments. In these cases on-board sensors like odometers and accelerometers can be used temporarily for positioning, however due to the poor accuracy of these methods, the quality of map matching decreases significantly. In this paper, we propose a method that improves the quality of map matching when GPS signals are not available. This method is based on a particle filter using heading and velocity measurement. We evaluate this method through its integration with an existing topological map matching algorithm. We compare the performances when this algorithm is used alone and when associated with the particle filter.

In this article we propose to process the code and phase delay of a dataless GNSS signal in open and semi-open loops. The aims of this processing are to get an accurate estimate of the phase and code delays by integration of the GNSS signal. We show that in an open loop the code delay evolution is a piecewise stationary process and we propose to model the phase delay as a circular random variable distributed according to a von Mises distribution. In this context the code tracking is realised on the GNSS signal by estimating the abrupt changes in the code discriminator values. We propose a Bayesian modeling of the problem in order to define the change point estimator. The proposed estimator involves in its definition the inaccurate prior information of Doppler and signal to noise density ratio provided by the phase delay tracking loop. Furthermore we propose a circular Bayesian modeling of the observations provided by the phase open loop. From this model, we derive a circular recursive filter for the estimation of phase delay and frequency of the carrier. The proposed tools are assessed using synthetic and real data. Highlights? We propose a Delay Semi Open Loop for the tracking of the code of a GNSS signal. ? We propose a Bayesian change point detector for this code tracking loop. ? We propose a Phase Open Loop for the tracking of the phase of a GNSS signal. ? We propose a Bayesian circular filter for this phase tracking loop. ? The proposed methods are assessed on synthetic and real data.

Soil moisture can be processed with the difference of power between a direct and a nadir GNSS signal reflected by the soil. The estimate carrier to noise ratio C/N 0 is a classical measure of power for the GNSS signals. We show in this paper that the classical estimate of C/N 0 processed for one satellite depends on the carriers, code and phase delay of the visible satellites. This dependence decreases the reproducibility of the measurements. In this paper we propose a non-linear model that links the power of the satellites with the observations of correlation obtained for the in phase component of the prompt local code. This expression takes into account the parameters of the GNSS signal and allows to improve the reproducibility of measurements. Unfortunately the expression is non linear and a particle filter is used to recover the signals amplitudes from the observations of correlation. In the experimentation the proposed approach is assessed on synthetic signals in the dynamic and static case.

This paper proposes circular data processing tools dedicated to the tracking of the phase of GNSS signals in a Phase Open Loop, particularly in case of multi-channel signal structure. The objective of processing the phase in an open loop is to avoid time-correlation between two successive measurements. This allows the use of loop filters in order to smooth the measurements without producing unwanted oscillations in the phase estimations. In order to process the angular values produced by the Phase Open Loop, the choice had been made to develop a filter and a fusion operator in a Bayesian framework with circular statistics distributions. The proposed tools are assessed on synthetic and real data.

A hierarchical Bayesian model is applied to off-line segmentation of the GPS signal discriminator. The purpose of this work is to estimate the code delay of the receiving GPS CDMA code in order to retime the local receiver code and to estimate the pseudorange satellite receiver. The goal of our approach is to obtain a high-rate accurate positioning in the dynamic navigation case. We show that the behaviour of the coherent discriminator of a GPS pilot channel can be modelized by a piecewise stationary process. In our approach the discriminator behaviour in each stationary segment is approximated by a constant acceleration model, and the code delay at each end of the segments is known. The interest of this approach is that we use the coherent values of the discriminator in each segment to estimate the change instants of the process and to get in this case an accurate estimation of the code delays. In this context, a simultaneous estimation of the change instants is considered. We define the a posteriori distribution which integrates in its expression the signal change instants and the parameters of its statistical model. The proposed model leads after marginalization to a penalized contrast function that we minimize to estimate the discriminator change instants. The interest of the proposed model is that we can integrate in our estimate prior information on the roughly known values of the signal-to-noise ratio and relative speed satellite receiver. The potential of the proposed method is shown on experimentations realized on synthetic and real data for millisecond receiver localization.

New GNSS signals broadcast at different carrier frequencies include, most of them, a pilot and data channels. In this article we propose to fuse the information of code and phase delay provided by the two channels in order to improve the position accuracy and to extract the message of navigation. The proposed system is composed of a change point estimate of the slope of discriminator variations and of a circular recursive filter for the estimation and fusion of the carrier phase delay. The contribution of this work is the definition of a recursive change point estimate that fuse the discriminator values and integrate prior information for the detection. The proposed architecture that uses a circular filter enables to fuse the phase delays and to extract the message of navigation. The method is assessed on synthetic data in the experimentation.

Many practical application in the field of robotic and perception are using angular data. In this work we present a multi-sensor multi-temporal data fusion filter for angular data. Most of the time, statistic filters, are designed on linear domain. In this work we propose a recursive filter defined on the circular domain with a von Mises distribution. In our application we consider a set of measurement taking at different instants and provided by different sensors. The sequential implementation of the recursive fusion filter we propose is deduced from the a posteriori distribution of the state vector, containing the angular direction and velocity. Temporal measurements are coming from several sensors. The feasibility and the contribution of our method are shown on synthetic data.

Mean wind speeds and mean wind directions are important input parameters for environmental models and applications. In many practical cases, anemometer sensor provides measurements of direction and wind speed, supposed to be Gaussian and piecewise stationary. In this work we use a von Mises distribution and a Log-normal distribution in order to model sensor data with distributions having a physical reality. We derive from these distributions an “on-line” recursive estimate of the change point in the wind speed and direction processes. We present numerical results obtained using synthetic and real data to demonstrate the ability of these estimates.

In this work we investigate the potential for sensing beach soil moisture with the L band GPS bistatic radar concept. Characterisation of sediment surface (properties like humidity) is indeed important to better understand morphodynamic activity of intertidal part of beaches. In our approach we compare the direct GPS Signal to Noise Ratio with the reflected one in order to measure the soil moisture. We use a bit grabber to digitize and store the GPS L1 carrier (1.5 Ghz) samples. In this context the signal processing is off-line. In this work we proposed a model of the received signal after demodulation and demultiplexing. We deduce from this model a MAP estimate of the navigation message and of the signal SNR. In our case the signal model is a piecewise stationary process with change instants at bit edge position. We present preliminary SNR measurement with this technique for the discrimination of water and humid sand.

This paper presents a Bayesian off-line fusion segmentation method, applied to the code tracking in a multi-carrier GPS receiver. The tracking is realized with discriminator values obtained on the different carrier frequencies. We suppose that the evolution of the pseudo-ranges satellites-receiver is piecewise linear. We propose a Bayesian method for the fusion of change detection models in the discriminators evolution. In this context, we construct a penalized contrast function to estimate the model parameters. The contrast function is deduced from log-likelihood of the parametric distribution that models the discriminators statistic evolution. We deduced the penalty term from the prior law of change instants. It is composed of parameters that guide the number of changes and of parameters that will bring prior information on the ionospheric delays between the GPS signals on the different carrier frequencies. We show on synthetic and real data the feasibility and the contribution of our method.

We present in this article an off-line Bayesian estimation method for the segmentation of piecewise linear processes. The estimation is defined as a penalized contrast function with a first term related to the observations and a term of penalty deduced from the prior law of change instants. This technique is used for the distance estimation between a satellite and a navigation receiver. The distance determination is performed by the delay measure of a signal propagation time emitted by the satellite. For the delay evaluation, a discriminator signal is calculated from the correlation between a code contained in the signal and the same code generated by the receiver at the same instant. The method we propose is applied to these discriminator measurements. It makes possible to precisely reconstitute the delay evolution rather than providing it sequentially. Our work's contribution is shown on synthetic and real data.

In this article we describe a new approach of brooking stationary detection in a noisy signal. We consider the signal corrupted by an additive stationary noise, whose form of the density of probability is none. This new approach leans on the detection and the analysis of the transitions of the signal. The extraction of transition in the signal associates, to each sample in the transition, a constant value equal to the surface of the signal in the transition. The application of this operator to the gradient of the signal gives us the value of the transitions dynamics in the signal. The dynamics transitions density probability modelization by a parametric curve allows us to deduce the level of noise in the signal. It is from the level of noise that we determine a threshold on the height of the transitions. Then we consider the transitions smaller than the threshold as transitions of the noise and the transitions higher than the threshold as the variations of the signal without noise. THis technique of rupture detection is entirely automatic and self adapted to the level of noise in the signal. We present the study and the implementation of this global approach for the detection of roof and step edges in range images. We detect roof and step edge in the image with the signals of transition extracted in two orthogonal directions.

The long-term neuropsychological and psychiatric sequelae of herpes simplex virus encephalitis (HSVE) and their relationship to the volume of temporal lesions and to amygdala and hippocampus damage remain undefined. We have conducted a prospective study of long-term sequelae in 11 patients with clinically presumed HSVE and detection of HSV DNA in the cerebrospinal fluid by polymerase chain reaction. Six months after encephalitis, patients underwent neuropsychological and language assessment. At the same stage, single photon emission computed tomography (SPECT) evaluated the occurrence of hypoperfusion with an index of asymmetry. MRI was used for the measurement of amygdala, hippocampus and cerebral lesions by two blind neurologists. The volume of the amygdala and hippocampus was compared with those of five controls, matched for age and level of education. Long-term memory disorders were seen in 6 patients, associated with the larger lesions and damage of at least two structures. Long-term behavioural changes with emotionalism, irritability, anxiety or depression were prominent in 7. Left prefrontal hypoperfusion appeared in 8 patients, associated with psychiatric disorders in 7 and left amygdala damage in 6. The reduction of amygdala and hippocampus volume was correlated with the overall volume of lesions. Different patterns of mesial temporal lobe damage occurred, involving either amygdala alone, or amygdala and hippocampus, but never hippocampus alone. MRI volumetric measurements in HSVE could be a good indicator of long-term prognosis. Persistant behavioural changes could be related to an amygdala and frontal dysfunction.

The problem of the choice of slices angles, at the time of diagnosis of brain fetal malformations, is linked to the position of the fetus inside the uterus. The 3D reconstruction of intern parts of the brain and especially the callosus corpus can help to detect some malformations. This kind of reconstruction pass by several steps that depend all on the initial segmentation step. The main difficulties of the segmentation are linked on the one hand to the inherent noise of ultrasound imaging and on the other hand to the matching of views of the 2D sequence to process. The 3D reconstruction stage require the definition of a marker in the sequence of process. In agreement with physicians, we have used the cranial contour as reference on the one hand because it is considered as invariable and fixed and on the other hand because of its more pronounced contrast (due to the fact of its cartilaginous nature) than the other structures. Nevertheless, the classic techniques of segmentations have remained without effect (open contour, too noisy). Therefore, we have developed an algorithm allowing to define automatically the ellipse. This method is based on a parametrically deformable model using elliptic FOURIER decomposition.© (1995) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

A new method for automatically reconstructing a three dimensional object from a serial cross section is presented in this paper. The method combines the technical chaining contour and the sampling method to construct an object. In the proposed method the initial description of the object is formed by a serial continuous contour. First we sample each cross section to determine the nods that constitute the vertices of the triangles used for the reconstruction, then we determine the tangent in these nods and we assign to each one of them a code depending on the tangent direction. For triangulation there is nothing left to do but collect the nods of two adjacent contours the code of which is identical.© (1994) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

**J,p PRUVO, ***Jp DUBUS* Laboratoire instrumentation du signal, de l'image et des reseaux de Calais*** Laboratoire de mesure automatique de Lille** Laboratoire de neuroradiologie de LilleKEY WORDS : segmentation, modelization, volumic quantification, Nuclear Magnetic Resonance Imaging.SUMMARYWe are suggesting a new approach to NMR image segmentation for multiple scleroses volume quantification. Thechoice of a segmentation technique is conditioned by whatis known in NMR acquisition artefacts. This research has beenconducted in collaboration with the Lille Neuroradiology Laboratory leading to the implementation of a disease developmentindex.

Several regional augmentation GNSS systems (like SBAS) are already fully operational and other are under development with new frequencies and signals on the way. Therefore, it becomes imperative to guarantee for all GNSS users the compatibility, interoperability and interchangeability between all these systems. The goal is to ensure that the user's multi-mode receiver can choose and mix signals from different GNSS and SBAS systems to achieve more availability, accuracy and robustness. Attaining that objective will require agreements on frequency plans and signal designs, as well as other details including means to ensure interoperability of system times and geodetic reference systems. This paper suggests a Universal-SBAS (U-SBAS) standard, compatible with all the existing and planned regional GNSS systems (and their evolutions) in the world, like IRNSS, QZSS, PCW, BEIDOU-1, WAAS, EGNOS, SDCM, GAGAN, MSAS. The proposed worldwide multimodal U-SBAS standard carries additional channels (signals and messages) to cover the non-aeronautical specific Safety-of-Life (SoL) services, and also High Precision Positioning Services (HPPS), Position Velocity Time (PVT), authentication services, safety services, scientific application services, High Precision Timing Services (HPTS), etc. U-SBAS is designed to be fully interoperable with the current SBAS standards and to allow significant performance and service improvements in operational, scientific and/or security areas. Finally usage examples of the proposed standard are given for different types of applications such as science, aviation, precise point positioning, timing, security, robust positioning, maritime and reflectometry.

The works presented in this paper deals with the design of a tracking fusion filter for the future multi-carrier G.P.S signal. The estimation of the distance and speed between the satellite and the G.P.S receiver is realised with a Kalman track fusion algorithm. In this system, inspired from the modified track-to-track algorithm, the observations of the same type are merged with a measurement fusion algorithm and the measurements of different types are fused with a state vector fusion Kalman filter. This hybrid model can fuse the measurement obtained from the three frequencies of the future G.P.S. system. It can also fuse the state vectors that describe distances and speed which are supposed to come from different sensors. The simulation result obtained on synthetic data show the feasibility of the method and the contribution of the fusion over the accuracy of the localization.

In this thesis we carry out the study of an SBL (Short BaseLine) localization system of an underwater transmitting beacon. The objective of this work is to propose a simple and easily deployable device. The tracking system is made of four hydrophones positioned on a small boat. The hydrophones are georeferenced with a GPS receiver and a magnetic compass positioned on the boat. The beacon provides the positioning system with its depth obtained using a pressure sensor. The considered marine environment is shallow water (the Channel, ports, canals, etc.). The targeted applications are the location of divers, fishing traps, drones and measuring instruments. It is shown in the bibliography that for synchronized TDOA measurements (obtained from a reference hydrophone) there are direct estimators of the position. In our approach, the TDOA measurements are provided by two pairs of hydrophones that are not synchronized with each other. In this case it is shown in the bibliography that the estimators of the position are indirect. They require the knowledge of an initial position to converge towards the real position. The aim of this thesis is to propose methods for calculating the initial position. The first contribution of the thesis is to propose an estimator of the 3D position in the case of a static beacon. For each TDOA measurement, the set of possible positions of the beacon is located on a hyperbola. In our approach, we propose to approximate the hyperbola by its two asymptotic lines in order to calculate the initial position. With two TDOA measurements we obtain four possible positions (at the intersections of the asymptotes) which are ambiguous because only one of them corresponds to the position of the beacon.We propose an algorithm and a criterion to be minimized to calculate the 3D position and remove the ambiguity on the initial position. The second contribution of the thesis is to propose an estimator of the dynamic 3D position of an underwater object. In the dynamic case, two TDOA measurements are available, ie four possible initial positions for each position of the boat. It is proposed to classify the initial positions obtained in four sets as the boat moves. The classification is carried out by a data association method and a criterion is proposed to resolve the ambiguity on the four sets of positions. The proposed estimation processis based on four parallel Kalman filters and on the GNN (Global Nearest Neighbor) data association method. The proposed methods have been evaluated in simulation for the positioning of an underwater object in the static and dynamic case. In this simulation we consider a distance between the hydrophones of 2 m. The positioning error is shown to be metric for noise on TDOA measurements of standard deviation 1 cm. The accuracy remains metric for a distance between the tracking system and the beacon of less than 30 m.We show that in the presence of noises on the positioning system (50 cm on the GPS position and 1o on the magnetic compass) the precision remains metric. Finally, it is shown that the proposed estimator is more precise than the direct weighted least squares benchmark estimator., Dans cette thèse on réalise l’étude d’un système de localisation SBL (Short BaseLine) d’une balise émettrice sous-Marine.L’objectif de ce travail est de proposer un dispositif simple et facilement déployable. Le système de localisation est composé de quatre hydrophones positionnés sur un bateau de petite taille. Les hydrophones sont géoréférencés avec un récepteur GPS et un compas magnétique positionnés sur le bateau.La balise fournit au système de positionnement sa profondeur obtenue à l’aide d’un capteur de pression. L’environnement marin considéré est un environnement en eaux peu profondes (la Manche, les ports, les canaux,... ). Les applications visées sont la localisation de plongeurs, de casiers de pêche, de drones et d’instruments de mesure. On montre dans la bibliographie que pour des mesures de TDOA synchronisées (obtenues à partir d’un hydrophone de référence) il existe des estimateurs directs de la position. Dans notre approche les mesures de TDOA sont fournies par deux couples d’hydrophones non-synchronisés entre eux. Dans ce cas on montre dans la bibliographie que les estimateurs de la position sont indirects. Ils nécessitent la connaissance d’une position initiale pour converger vers la position réelle. Le but de cette thèse est de proposer des méthodes de calcul de la position initiale. Le premier apport de la thèse est de proposer un estimateur de la position 3D dans le cas d’une balise statique. Pour chaque mesure de TDOA l’ensemble des positions possibles de la balise se situe sur une hyperbole. Dans notre approche on propose d’approximer l’hyperbole par ses deux droites asymptotes pour calculer la position initiale. Avec deux mesures de TDOA on obtient quatre positions possibles (aux intersections des asymptotes) qui sont ambigües car une seule d’entre-elles correspond à la position de la balise. Nous proposons un algorithme et un critère à minimiser pour calculer la position 3D et lever l’ambiguïté sur la position initiale. Le second apport de la thèse est de proposer un estimateur de la position 3D dynamique d’un objet sous-marin. Dans le cas dynamique on dispose de deux mesures de TDOA, soit quatre positions initiales possibles pour chaque position du bateau. On propose de classer les positions initiales obtenues dans quatre ensembles au fur et à mesure du déplacement du bateau. Le classement est réalisé par une méthode d’association de données et on propose un critère pour lever l’ambiguïté sur les quatre ensembles de positions. Le processus d’estimation proposé s’appuie sur quatre filtres de Kalman parallèles et sur la méthode d’association de données GNN (Global Nearest Neighbor). Les méthodes proposées ont été évaluées en simulation pour le positionnement d’un objet sous-marin dans les cas statique et dynamique. Dans cette simulation on considère une distance entre les hydrophones de 2 m. On montre que l’erreur de positionnement est métrique pour un bruit sur les mesures de TDOA d’écart-type 1 cm. La précision reste métrique pour une distance entre le système de localisation et la balise inférieure à 30 m. On montre qu’en présence de bruits sur le système de positionnement (50 cm sur la position GPS et 1o sur le compas magnétique) la précision reste métrique. Enfin on montre que l’estimateur proposé est plus précis que l’estimateur direct de référence des moindres carrés pondérés.

The purpose of that thesis work is the research and implementation of a compact and simple underwater localization system that aim to be used in ports, coastal areas and other low-depth environments. Our system is SBL (Small Distance Baseline), with a small number of transceivers (only one emitter and two hydrophones). Due to the system's geometric configuration not being optimal (both hydrophones are close to one another), the precision obtained using classical approaches is poor. We therefore propose a new localization approach that will improve it. The emitter we wish to localize emit a spread spectrum signal. The time difference of arrival (TDOA) between the two hydrophones is then determined using correlations methods. We propose in our work two tracking loops that will estimate both the delay and the doppler frequency between the signals. Using a Kalman filter , those methods are implemented respectively in open and close loop. From each TDOA measurement, we can calculatea hyperbolic area of possible emitter location. We thus use a statistical model which takes into account the local geometry of our measurements system in order to create a probable localization area around each hyperbole. By using the measurements at several different boat positions, we create a probability density whose maximum will be centered around the emitter's position. We show that, on simulated data, it is possible to localize the beacon with a precision beneath a meter with a realistic noise level. Experimental work and real data collection confirm that the method can in that context achieve the same result with a precision of a few meters.; Le but de cette thèse est l'étude et la mise en oeuvre d'un système de localisation sous-marine compact et simple à mettre en place pour une utilisation en zones portuaires, côtières et environnements peu profonds. Nous proposons un système SBL (Small Distance Baseline) avec un nombre réduit de transducteurs (une balise d'émission et deux hydrophones). La configuration géométrique du système étant contraignante (hydrophones proches) la précision du positionnement obtenue par les méthodes classiques est faible. Nous proposons une nouvelle méthode de localisation améliorant la précision. La balise à localiser émet un signal à étalement de spectre. La différence de distance entre les trajets des signaux des hydrophones est mesurée par corrélation. Nous proposons deux boucles de poursuites pour l'estimation conjointe de la fréquence Doppler et du délai entre les signaux reçus. Ces techniques de poursuite basées sur un filtre de Kalman sont implémentées en boucle fermée et ouverte. Les observations TDOA (Time Difference Of Arrival) conduisent à utiliser une technique de localisation hyperbolique. Nous proposons une représentation statistique qui exploite la géométrie de notre système de mesure pour déterminer une zone de localisation probable autour de chaque hyperbole. En utilisant des positions de bateau successives, on construit une densité de probabilité dont le maximum définit la position de la balise. On montre sur données synthétiquesque pour un bruit de mesure réaliste, il est possible de déterminer la position de la balise avec une précision submétrique. Les expérimentations réelles confirment la faisabilité du système et la précision obtenue est dans ce cas métrique.

The Global Navigation Satellite Systems Reflectometry (GNSS-R) is an Earth observation technique. It is based on a passive bi-static radar system using the L-band signal coming directly from a GNSS satellite and this same signal reflected by the Earth surface. The aim of the presented work is to develop signal processing methods for altimetry measurements using ground based GNSS-R. The altitude is derived from the difference of path between the direct and reflected signals. We propose three estimators for GNSS-R altimetry measurement using respectively the code observations, the carrier-to-noise ratio C/N₀ observations, and the phase observations obtained by a mono-frequency receiver. Firstly, we define a pseudo-range estimator using under-sampling code delay observations aided by phase measurements. We show that the proposed estimator allows avoiding accuracy limitations due to the receiver resolution. Secondly, a calibration method has been developed for the Interference Pattern Technique, for normalizing the C/N₀ of the combination of the direct and reflected signals. The Cramèr-Rao Lower Bound of this estimation technique is studied. We show that the proposed estimator allows reducing the observation duration while keeping the centimeter accuracy. Thirdly, a last method is proposed in order to evaluate the difference of path between the direct and reflected signals using phase measurement.The phase measurement is an angular data evolving linearly with the satellite elevation. In this context, we propose two estimators based on a circular-linear regression and the von Mises distribution. Experimentation on real data conclude this manuscript and show the feasibility of these methods. The centimeter accuracy is reached.; La réflectométrie GNSS (GNSS-R) est une technique d'observation de la Terre reposant sur un système radar bi-statique passif qui utilise, comme signaux d'opportunité, les signaux GNSS en bande L. Les travaux présentés dans ce manuscrit de thèse ont pour but de développer des méthodes de traitement du signal dédiées à l'altimétrie au sol par GNSS-R. L'altitude entre le récepteur GNSS-R et la surface de réflexion est déduite de la différence de chemin entre les signaux direct et réfléchi. On propose trois méthodes d'estimation dédiées à l'altimétrie par GNSS-R, pour un récepteur mono-fréquence, utilisant respectivement les observables de code, de puissance (carrier-to-noise ratio C/N₀) et de phase des signaux GNSS observés. Nous proposons un estimateur de la pseudo-distance qui utilise la mesure de délais de code sous-échantilloné aidée par la mesure de phase. On montre que l'estimateur sub-résolution proposé permet d'obtenir une précision qui est inférieure à la résolution en délai de code. Le deuxième estimateur s'appuie sur une méthode de calibration qui normalise la puissance de la somme des signaux direct et réfléchi (Interférence Pattern Technique). On montre par l'étude des bornes de Cramèr-Rao que l'estimateur proposé permet de réduire le temps de mesure et de conserver une précision centimétrique. La mesure de phase est une grandeur circulaire qui évolue linéairement avec l'élévation du satellite. Dans ce contexte, nous proposons deux estimateurs qui s'appuient sur un modèle de régression circulaire et la distribution circulaire de von Mises. Des expérimentations sur données réelles viennent conclure ce manuscrit de thèse et montrent la faisabilité des trois méthodes d'estimation proposées. La précision centimétrique est atteinte.

The Global Navigation Satellite Systems Reflectometry (GNSS-R) is an Earth observation technique. It is based on a passive bi-static radar system using the L-band signal coming directly from a GNSS satellite and this same signal reflected by the Earth surface. The aim of the presented work is to develop signal processing methods for altimetry measurements using ground based GNSS-R. The altitude is derived from the difference of path between the direct and reflected signals. We propose three estimators for GNSS-R altimetry measurement using respectively the code observations, the carrier-to-noise ratio C/N₀ observations, and the phase observations obtained by a mono-frequency receiver. Firstly, we define a pseudo-range estimator using under-sampling code delay observations aided by phase measurements. We show that the proposed estimator allows avoiding accuracy limitations due to the receiver resolution. Secondly, a calibration method has been developed for the Interference Pattern Technique, for normalizing the C/N₀ of the combination of the direct and reflected signals. The Cramèr-Rao Lower Bound of this estimation technique is studied. We show that the proposed estimator allows reducing the observation duration while keeping the centimeter accuracy. Thirdly, a last method is proposed in order to evaluate the difference of path between the direct and reflected signals using phase measurement.The phase measurement is an angular data evolving linearly with the satellite elevation. In this context, we propose two estimators based on a circular-linear regression and the von Mises distribution. Experimentation on real data conclude this manuscript and show the feasibility of these methods. The centimeter accuracy is reached., La réflectométrie GNSS (GNSS-R) est une technique d'observation de la Terre reposant sur un système radar bi-statique passif qui utilise, comme signaux d'opportunité, les signaux GNSS en bande L. Les travaux présentés dans ce manuscrit de thèse ont pour but de développer des méthodes de traitement du signal dédiées à l'altimétrie au sol par GNSS-R. L'altitude entre le récepteur GNSS-R et la surface de réflexion est déduite de la différence de chemin entre les signaux direct et réfléchi. On propose trois méthodes d'estimation dédiées à l'altimétrie par GNSS-R, pour un récepteur mono-fréquence, utilisant respectivement les observables de code, de puissance (carrier-to-noise ratio C/N₀) et de phase des signaux GNSS observés. Nous proposons un estimateur de la pseudo-distance qui utilise la mesure de délais de code sous-échantilloné aidée par la mesure de phase. On montre que l'estimateur sub-résolution proposé permet d'obtenir une précision qui est inférieure à la résolution en délai de code. Le deuxième estimateur s'appuie sur une méthode de calibration qui normalise la puissance de la somme des signaux direct et réfléchi (Interférence Pattern Technique). On montre par l'étude des bornes de Cramèr-Rao que l'estimateur proposé permet de réduire le temps de mesure et de conserver une précision centimétrique. La mesure de phase est une grandeur circulaire qui évolue linéairement avec l'élévation du satellite. Dans ce contexte, nous proposons deux estimateurs qui s'appuient sur un modèle de régression circulaire et la distribution circulaire de von Mises. Des expérimentations sur données réelles viennent conclure ce manuscrit de thèse et montrent la faisabilité des trois méthodes d'estimation proposées. La précision centimétrique est atteinte.

A gps signal es modulated by a carrier and is spreaded by a pseudo random code. Its power, which is carried below the level of noise, can't be directly measured. Conventional estimators literature using the statistical parameters of the maximum of the correlation, obtained after despreading of the signal to measure the received signal strength. These estimators require a long period of integration to be precise. Moreover, they do not take into account the effect of the Doppler frequency and the number of visible satellites on the statistical maximum of the correlation. These disruptive effects falsify the estimated value of C/N0 and limit the applications of the reflectometry. This thesis proposes an estimator of the signal to noise ratio own to each satellite, from a GPS L1 signal. To present this estimator, we have adopted a two-step approach. it is assumed in the first stage that the GPS signal is digitized on 1 bit, and sets a function relating the amplitude of the signal received to maximum correlation knowing the parameters of the GPS signal which are : the Doppler frequency and the phase shift of the received signal. indeed, the signal to noise ratio is a relative measure, and to estimate the signal amplitude is assumed that the noise is white, Gaussian, centered and unit variance. The proposed function is highly non-linear. We propose in a second step a dynamic estimator of the signal amplitude, which uses the non-linear state filter and the observations of the maximum correlation. Two filters are assessed in this case the Unscented Kalman filter and a particle filter., Un signal GPS est modulé par une porteuse et est étalé par un code pseudo aléatoire. Sa puissance, qui est portée en dessous du niveau du bruit, ne peut pas être directement mesurée. Les estimateurs classiques de la littérature utilisent les paramètres statistiques du maximum de la corrélation, obtenus après le désétalement du signal pour mesurer la puissance du signal reçu. Ces estimateurs nécessitent une longue période d'intégration pour être précis. De plus, ils ne tiennent pas compte de l'effet de la fréquence Doppler et du nombre de satellites visibles sur la statistique du maximum de la corrélation. Ces effets perturbateurs faussent l'estimation de la valeur C/N0 et limitent les applications qui utilisent cette grandeur telle que la réflectométrie des signaux GNSS. Ce travail de thèse propose un estimateur du rapport signal à bruit propre à chaque satellite, à partir d'un signal GPS L1. Pour présenter cet estimateur, nous avons adopté une approche en deux étapes. On suppose dans la première étape que le signal GPS est numérisé sur 1 bit, et on établit une fonction reliant l'amplitude du signal reçu au maximum de corrélation. Cette fonction non linéaire est déduite de l'architecture radio du récepteur GPS et des paramètres du signal qui sont : la fréquence Doppler et le déphasage du signal reçu. En effet, le rapport signal à bruit est une mesure relative, et pour pouvoir estimer l'amplitude du signal, on suppose que le bruit est blanc, gaussien, centré et de variance unitaire. La fonction proposée étant fortement non linéaire, nous proposons dans une deuxième étape, un estimateur dynamique de l'amplitude du signal, qui utilise le filtrage d'état non linéaire et les observations du maximum de la corrélation. Deux filtres sont évalués à cet effet ; le friltrage de Kalman sans parfum et le filtrage particulaire.

Navigation in constrained areas such as ports or dense urban environments is often exposed to theproblem of non-line-of-sight to GPS satellites. In this case, proprioceptive sensors are generally used totemporarily localize the vehicle on a map. However, the drift of these sensors quickly cause the navigationsystem to fail. To localize the vehicle, a magnetometer is used in this thesis for heading measurementunder an absolute reference together with a velocity sensor and a digital map of the road network.In this context, the first contribution of this work is to provide a matching of the vehicle’s headingwith the digital map (map matching) to localize the vehicle. The proposed technique uses a particle filterdefined in the circular domain and a circular pre-filtering on the heading measurements. It is shown thatthis technique is more efficient than a conventional topological map matching algorithm, particularly inambiguous cases like a Y-shape road junction. The second contribution of this work is to propose a circularmultiple model filter CIMM defined in a Bayesian framwork from the von Mises circular distribution.It is shown that the integration of this new approach in the pre-filtering and analysis of the heading observationsimproves the robustness of the heading’s estimation during cornering and increases the mapmatching’s quality through a better propagation of the particles on the road network. The performancesof the proposed methods are evaluated on synthetic and real data., La navigation dans les environnements contraints tels que les zones portuaires ou les zones urbainesdenses est souvent exposée au problème du masquage des satellites GPS. Dans ce cas, le recours auxcapteurs proprioceptifs est généralement la solution envisagée pour localiser temporairement le véhiculesur une carte. Cependant, la dérive de ces capteurs met rapidement en défaut le système de navigation.Pour localiser le véhicule, on utilise dans cette thèse, un magnétomètre pour la mesure du cap dans unrepère absolu, un capteur de vitesse et une carte numérique du réseau de routes.Dans ce contexte, le premier apport de ce travail est de proposer la mise en correspondance desmesures de cap avec la carte numérique (map matching) pour localiser le véhicule. La technique proposéefait appel à un filtre particulaire défini dans le domaine circulaire et à un préfiltrage circulairedes mesures de cap. On montre que cette technique est plus performante qu’un algorithme de map matchingtopologique classique et notamment dans le cas problématique d’une jonction de route en Y. Ledeuxième apport de ce travail est de proposer un filtre circulaire multi-modèles CIMM défini dans uncadre bayésien à partir de la distribution circulaire de von Mises. On montre que l’intégration de cettenouvelle approche dans le préfiltrage et l’analyse des mesures de cap permet d’améliorer la robustesse del’estimation de la direction pendant les virages ainsi que d’augmenter la qualité du map matching grâce àune meilleure propagation des particules du filtre sur le réseau de routes. Les performances des méthodesproposées sont évaluées sur des données synthétiques et réelles.

When a value is observed by a temporal series of periodic measurements, such as angle measurements, the statistic tools of the linear domain are no longer adapted to the estimation of the statistical parameters of this series. We propose several filters and a fusion operator adapted to angular random variables estimation. They are developed in a Bayesian framework with the von Mises circular normal distribution. Moreover, we propose a Global Likelihood Ratio circular change estimator which relies on a particle filter defined in the circular domain. GNSS signal procedding traditionnaly relies on the recursive estimation of three parameters in lock loops : the code delay, the phase and the frequency of the received signal carrier. We show in this thesis that the phase and frequency estimations, when realized in a lock loop, cause imprecisions and additional perturbations. We proposea new approach for the estimation of these parameters in an open loop. in this context, the phase measurements are angles defined between ‒π et π. They can be modeled using the von Mises distribution, thus we use the developed circular estimation tools in order to process them. We show the benefit of the proposed approach for positioning and for height estimation using the GNSS-Reflectometry technique. The obtained precision is of the centimeter order, for integration times of one millisecond. We also propose a phase ambiguity resolution technique which can be used in a mono-receiver , mono-frequency approach., Lorsqu'une grandeur est observée par une série temporelle de mesures périodiques, telles que des mesures d'angles, les outils statistiques du domaine linéaire ne sont plus adaptés à l'estimation des paramètres statistiques de cette série. Nous proposons des filtres et un opérateur de fusion adaptés aux grandeurs aléatoires circulaires. Ils sont développés dans un cadre bayésien avec la distribution circulaire normale de von Mises. De plus, on propose un estimateur circulaire GLR (Global Likehood Ratio) de ruptures dans un signal angulaire s'appuyant sur un filtre particulaire défini dans le domaine circulaire. Le traitement des signaux GNSS repose traditionnellement sur l'estimation récursive, en boucles fermées, de trois paramètres : le délai de code, la phase et la fréquence porteuse du signal reçu. On montre dans cette thèse que l'estimation de la phase et de la fréquence en boucle fermée est à l'origine d'imprécisions et de perturbations additionnelles. On propose une nouvelle approche pour l'estimation de ces paramètres en boule ouverte. Dans ce cas, les mesures de phase sont des angles, définis entre ‒π et π. Statistiquement, elles peuvent être modélisées par la distribution circulaire de von Mises et l'on utilise donc les outils d'estimation circulaire développés dans cette thèse pour les traiter. On montre l'intérêt de l'approche proposée pour le positionnement et pour l'altimétrie par réflectométrie des signaux GNSS. La précision obtenue est de l'ordre du centimètre, pour des durées d'intégrationd'une milliseconde. On propose également une technique de résolution de l'ambiguïté de phase, utilisable dans une approche mono-récepteur et mono-fréquence.

The new GPS L2C signal carry on the same carrier a pilot channel and a data channel. We propose non-linear fusion operators to estimate the code and phase delays that are obtained on both channels. Moreover, we propose a new tracking architecture based on open loops including joint estimators and jump detectors. Indeed, we show that the evolution of the code delay discriminator obtained with an open loop is piecewise linear. In that case, we propose a one-line change point estimate that includes a new non-linear fusion operator, using prior information on the parameter to estimate. This prior information allows decreasing the correlation between the different observations and as a consequence to decrease the mean square error of the fused measurements. The phase delay tracking open loop provides angular measurements of the received GPS signal. In this context, we have extended the fusion and Bayesian filtering techniques from linear statistics to circular statistics to estimate the phase delay. We propose a new angular fusion operator, a circular recursive filter and a change point estimator for piecewise stationary circular process. The proposed methods allow to process long time integration of the coherent discriminator values and so to improve the high rate localization of a mobile receptor compute every millisecond., Le nouveau signal GPS L2C contient sur une même porteuse une voie pilote et une voie de données. Il est proposé dans cette thèse des opérateurs de fusion non-linéaire, pour estimer les décalages du code et les informations de retard de phase obtenus sur ces deux voies. De plus nous proposons une nouvelle architecture de poursuite basée sur des boucles ouvertes intégrant des estimateurs et détecteurs de ruptures conjoints. En effet, l'évolution du discriminant obtenu par une boucle de poursuite du code ouverte, est linéaire par morceaux. Nous proposons dans ce cas un estimateur de ruptures intégrant un nouvel opérateur de fusion non-linéaire qui utilise une information a priori sur le paramètre à estimer. Cette information a priori permet de diminuer la corrélation entre les différentes observations et ainsi de diminuer l'erreur quadratique moyenne des mesures fusionnées. La boucle de poursuite ouverte du retard de phase, fournit une mesure angulaire du déphasage du signal GPS reçu. Dans ce contexte nous avons étendu les techniques de fusion et de filtrage d'état Bayésien de la statistique linéaire à l'analyse des données circulaires pour l'estimation du déphasage. Nous proposons un nouvel opérateur de fusion angulaire, un filtre récursif circulaire et un estimateur de rupture de moyennes dans un processus circulaire stationnaire par morceaux. Les algorithmes proposés permettent de réaliser une intégration longue des valeurs cohérentes du discriminant et d'améliorer ainsi la localisation à la milliseconde d'un récepteur mobile.

The new GPS L2C signal carry on the same carrier a pilot channel and a data channel. We propose non-linear fusion operators to estimate the code and phase delays that are obtained on both channels. Moreover, we propose a new tracking architecture based on open loops including joint estimators and jump detectors. Indeed, we show that the evolution of the code delay discriminator obtained with an open loop is piecewise linear. In that case, we propose a one-line change point estimate that includes a new non-linear fusion operator, using prior information on the parameter to estimate. This prior information allows decreasing the correlation between the different observations and as a consequence to decrease the mean square error of the fused measurements. The phase delay tracking open loop provides angular measurements of the received GPS signal. In this context, we have extended the fusion and Bayesian filtering techniques from linear statistics to circular statistics to estimate the phase delay. We propose a new angular fusion operator, a circular recursive filter and a change point estimator for piecewise stationary circular process. The proposed methods allow to process long time integration of the coherent discriminator values and so to improve the high rate localization of a mobile receptor compute every millisecond.; Le nouveau signal GPS L2C contient sur une même porteuse une voie pilote et une voie de données. Il est proposé dans cette thèse des opérateurs de fusion non-linéaire, pour estimer les décalages du code et les informations de retard de phase obtenus sur ces deux voies. De plus nous proposons une nouvelle architecture de poursuite basée sur des boucles ouvertes intégrant des estimateurs et détecteurs de ruptures conjoints. En effet, l'évolution du discriminant obtenu par une boucle de poursuite du code ouverte, est linéaire par morceaux. Nous proposons dans ce cas un estimateur de ruptures intégrant un nouvel opérateur de fusion non-linéaire qui utilise une information a priori sur le paramètre à estimer. Cette information a priori permet de diminuer la corrélation entre les différentes observations et ainsi de diminuer l'erreur quadratique moyenne des mesures fusionnées. La boucle de poursuite ouverte du retard de phase, fournit une mesure angulaire du déphasage du signal GPS reçu. Dans ce contexte nous avons étendu les techniques de fusion et de filtrage d'état Bayésien de la statistique linéaire à l'analyse des données circulaires pour l'estimation du déphasage. Nous proposons un nouvel opérateur de fusion angulaire, un filtre récursif circulaire et un estimateur de rupture de moyennes dans un processus circulaire stationnaire par morceaux. Les algorithmes proposés permettent de réaliser une intégration longue des valeurs cohérentes du discriminant et d'améliorer ainsi la localisation à la milliseconde d'un récepteur mobile.

The GPS (Global Positioning System) allows any user to calculate his position on Earth. A receiver measures the transit time of electromagnetic waves emitted by a satellites constellation. The transit time is estimated with discriminator values calculate with correlation of codes contained in the signals and generated by the receiver. Actually, the GPS signal is emitted on a single carrier frequency for a civil use. With the future GPS evolution, as well as the future European system Galileo, several frequencies and so several discriminator measurements will be available. The purpose of this thesis is the study and the implementation of fusion methods for off-line segmentation of code discriminators. In this context, we examine several bayesian segmentation approaches. We propose a first hybrid fusion technique that permits to determine a stationary change on several signals. The second off-line fusion method permits to determine the linear multi-changes on a multi-carrier GPS signals. This method is based on the minimisation of a penalized contrast function. These methods are evaluated for the estimation of the distance between a satellite and a receiver, and for the position calculation of a receiver, on real data, every millisecond., Le système de positionnement GPS (Global Positioning System) permet à tout utilisateur de déterminer sa position sur la Terre. Un récepteur calcule les temps de propagation que mettent des ondes électromagnétiques émises par une constellation de satellites pour lui parvenir. L'estimation de ce temps de propagation est obtenue grâce à un signal discriminant, construit à partir de la corrélation des codes du signal reçu avec les codes générés par le récepteur. Actuellement, ces ondes ne sont émises que sur une unique fréquence porteuse pour une utilisation civile. Avec l'évolution future du système GPS, ainsi que la mise en place du système européen Galileo, plusieurs fréquences et donc plusieurs mesures de discriminants seront disponibles. Le travail présenté dans cette thèse a pour objet l'étude et la mise en oeuvre de méthodes de fusion appliquées à la segmentation hors-ligne des discriminants de code. Pour cela, plusieurs approches de segmentations bayésiennes sont étudiées. Une première technique de fusion hybride permet de déterminer la présence d'une rupture de stationnarité dans une fenêtre d'observation et sur plusieurs signaux. La seconde méthode de fusion, hors-ligne et multi-ruptures, permet de déterminer les ruptures de linéarités de signaux grâce à la minimisation d'une fonction de contraste pénalisée. Ces méthodes sont ensuite appliquées à l'estimation de la distance entre un satellite et un récepteur, et évaluées sur signaux réels pour le calcul de la position d'un récepteur toutes les millisecondes.

The works presented in this thesis is devoted to the study and the implementation of the information fusion methods for the 3D localization of a terrestrial vehicle in a dense urban environment. The studied approach is based on the fusion of the measurements provided by the multi-frequencies GPS absolute navigation system and the dead-reckoning navigation sensors (odometer and gyrometer). These measurements are hybridizate using recursive filters to estimate the position. We carry out the study of the position estimator in two stages. The first stage concerns the study and the implementation of an estimator for the phase and code observables fusion for the GPS multi-carrying. The experimentation on synthetic and real data shows that the proposed system allows to increase the measurement precision when the noise power, in each of the carrying, is in the same magnitude order. The second stage concerns the tight hybridization system which provides an estimate of the vehicle direction and the pseudo-ranges satellite-receiver, even without GPS measurements.Within the framework, we propose a recursive circular filter which allows the estimation of the vehicle direction. The hybridization filter produces a centralized fusion of the corrected pseudo-ranges measurements and a distributed fusion of the phase observables with the gyrometric and odometric measurements.The experimentation carried out in a synthetic and real context shows that the proposed system is at least as precise as the releases hybridization system usually used in practice., Le travail présenté dans ce mémoire de thèse concerne l'étude et la mise en oeuvre de méthodes de fusion d'informations pour la localisation 3D d'un véhicule terrestre en environnement urbain dense. L'approche étudiée est la fusion des mesures fournies par le système de navigation absolue GPS multi-porteuses et les capteurs de navigation estimes odomètre et gyromètre. Ces mesures sont hybridées à l'aide de filtres récursifs pour l'estimation de la position. On réalise l'étude de l'estimateur de position en deux étapes. La première étape concerne l'étude et la mise en oeuvre d'un estimateur pour la fusion des observables de code et de phase du GPS multi-porteuses. L'expérimentation sur données synthétiques et réelles montre que le système proposé permet d'augmenter la précision des mesures lorsque la puissance du bruit sur chaque porteuse est du même ordre de grandeur. La deuxième étape concerne le système d'hybridation serrée qui fournit une estimation de la direction du véhicule et des pseudo-distances satellite-récepteur, même en absence de mesures GPS. Dans ce cadre, nous proposons un filtre circulaire récursif qui permet d'estimer la direction du véhicule. Le filtre d'hybridation réalise la fusion centralisée des mesures de pseudo-distances corrigées et la fusion distribuée des observables de phase avec les mesures gyrométriques et odométriques. L'expérimentation réalisée dans un contexte synthétique et réel montre que le système proposé est au moins aussi précis que le système d'hybridation lâche habituellement utilisé en pratique.

When a value is observed by a temporal series of periodic measurements, such as angle measurements, the statistic tools of the linear domain are no longer adapted to the estimation of the statistical parameters of this series. We propose several filters and a fusion operator adapted to angular random variables estimation. They are developed in a Bayesian framework with the von Mises circular normal distribution. Moreover, we propose a Global Likelihood Ratio circular change estimator which relies on a particle filter defined in the circular domain. GNSS signal procedding traditionnaly relies on the recursive estimation of three parameters in lock loops : the code delay, the phase and the frequency of the received signal carrier. We show in this thesis that the phase and frequency estimations, when realized in a lock loop, cause imprecisions and additional perturbations. We proposea new approach for the estimation of these parameters in an open loop. in this context, the phase measurements are angles defined between ‒π et π. They can be modeled using the von Mises distribution, thus we use the developed circular estimation tools in order to process them. We show the benefit of the proposed approach for positioning and for height estimation using the GNSS-Reflectometry technique. The obtained precision is of the centimeter order, for integration times of one millisecond. We also propose a phase ambiguity resolution technique which can be used in a mono-receiver , mono-frequency approach.; Lorsqu'une grandeur est observée par une série temporelle de mesures périodiques, telles que des mesures d'angles, les outils statistiques du domaine linéaire ne sont plus adaptés à l'estimation des paramètres statistiques de cette série. Nous proposons des filtres et un opérateur de fusion adaptés aux grandeurs aléatoires circulaires. Ils sont développés dans un cadre bayésien avec la distribution circulaire normale de von Mises. De plus, on propose un estimateur circulaire GLR (Global Likehood Ratio) de ruptures dans un signal angulaire s'appuyant sur un filtre particulaire défini dans le domaine circulaire. Le traitement des signaux GNSS repose traditionnellement sur l'estimation récursive, en boucles fermées, de trois paramètres : le délai de code, la phase et la fréquence porteuse du signal reçu. On montre dans cette thèse que l'estimation de la phase et de la fréquence en boucle fermée est à l'origine d'imprécisions et de perturbations additionnelles. On propose une nouvelle approche pour l'estimation de ces paramètres en boule ouverte. Dans ce cas, les mesures de phase sont des angles, définis entre ‒π et π. Statistiquement, elles peuvent être modélisées par la distribution circulaire de von Mises et l'on utilise donc les outils d'estimation circulaire développés dans cette thèse pour les traiter. On montre l'intérêt de l'approche proposée pour le positionnement et pour l'altimétrie par réflectométrie des signaux GNSS. La précision obtenue est de l'ordre du centimètre, pour des durées d'intégrationd'une milliseconde. On propose également une technique de résolution de l'ambiguïté de phase, utilisable dans une approche mono-récepteur et mono-fréquence.