This paper deals with the detection of mechanical load faults in induction motors during speed transients. The detection strategy is based on stator current analysis. Mechanical load faults generally lead to load torque oscillations at specific frequencies related to the mechanical rotor speed. The torque oscillations produce a characteristic sinusoidal phase modulation of the stator current. Speed transients result in time-varying supply frequencies that prevent the use of classical, Fourier transform-based spectral estimation. This paper proposes the use of a time-frequency distribution, the Wigner Distribution, for stator current analysis. Fault indicators are extracted from the distribution for on-line condition monitoring. The proposed methods are implemented on a low-cost digital signal processor. Experimental results in a steady-state and during transients with load torque oscillations and load imbalance are presented.

For GNSS civil aviation applications, it is necessary to be able to guarantee the required level of performance specified by ICAO during a given phase of flight. The use of several GNSS components such as various signals, constellations or augmentation systems, sometimes redundant, helps monitoring the system robustness against several sources of perturbations like ionosphere or jammers for instance. In case of perturbation preventing one of the needed components to meet the phase of flight required performance, it is necessary to be able to switch to another available component in order to try to maintain if possible the level of performance in terms of continuity, integrity, availability and accuracy. But, to this end, future combined receivers must be capable of detecting the largest number of degradations that should lead to the loss of one GNSS component. Among the perturbations, one can note atmospheric disturbances, multipath, cycle slips, interferences. It is consequently necessary to identify and test degradation detection means that will enable if possible the receiver to maintain the level of performance requirement during an aircraft flight. Because of the interests in civil aviation and the restrictive requirements associated, it is interesting to focus on the degradation detection during LPV phases of flight. The interference is among the most feared events in civil aviation use of GNSS. Detection, estimation and removal remain an open issue and may affect pseudoranges measurements accuracy as well as integrity, continuity and even availability of those measurements. In literature, many different interference detection algorithms have been proposed at the front-end level of the receiver. For instance making chi-square tests at the ADC level, as in nominal conditions, the ADC bins distribution is Gaussian. Other non exhaustive means are to study the design of the receiver antenna or to make a spectral selectivity using filters. However, detection within tracking loops is not widely studied to our knowledge that is why it is an interesting investigation way that may complete other detection means, as proposed in [Bastide, 2001]. The goal of this paper is to estimate the performance of detection algorithm of Carrier Waves and Narrow Bands interferences. The main results are missed detection probability and the non-detected tracking error induced by interferences. Indeed, those types of interferences may affect powerful GPS L1 C/A or Galileo E1 code spectrum lines and may produce Misleading Information. It is consequently important to study the effects of such interferences on different spectrum lines and with different settings, varying the amplitude and for Narrow Bands, the bandwidth of this perturbation. The detection algorithms used are based on multi correlator receiver outputs to detect the I and Q correlation distortions due to interferences. The paper starts with the presentation of the detection technique. Performance analysis is then conducted taking into account required continuity during LPV phase of flight, to determine a threshold on the interference detection criteria (FFT of the correlator outputs). Interference missed detection probability is then estimated and finally the algorithm integrity performances are discussed. To comply with actual conditions, as the receiver is supposed onboard a flying aircraft, tests were conducted under multipath conditions modelled with the DLR Aeronautical Channel, taking into account the ground reflection and fuselage echoes during LPV. In addition, simulations were performed under all kinds of dynamics, complying with DO 229 d specifications and interim Galileo MOPS. The results indicate these techniques are good detection means under actual conditions, and do not require a too large number of calculations. The inclusion of the proposed algorithms before Receiver Autonomous Integrity Monitoring algorithms and combined integrity results are discussed. Further studies should provide results on the accuracy of interference estimation and repair algorithms.

In contrast with ground applications the GNSS constellations are not optimized for space applications. Moreover, the different types of mission, i.e. Low Earth Orbit (LEO), Medium Earth Orbit (MEO), Geosynchronous Earth Orbit (GEO), have all specific requirements. Our motivation is to define an «Ubiquitous GNSS receiver (UGNSS)», i.e. a single receiver able to cope with all types of mission. The analyze of the different types of mission shows that the UGNSS receiver should deal with both GPS and GALILEO signals as well as other future GNSS systems. It should also be able to have fast synchronization and robust tracking with extremely wide Doppler range(LEO mission)or be able to cope with very weak signals (GEO mission).In order to fulfill those requirements, we define the specifications of a reconfigurable decoder that allows to allocate the hardware resources to the type of processing required by the mission. In this paper we consider the algorithm which aims to acquire GNSS signals. This algorithm is based on two IP cores which perform a 8 points FFT and a 2048 points FFT. These two cores are configured to achieve GNSS signal acquisition in any space mission, by taking into account the signal structure (BPSK(1)or BOC(1,1))and the signal features(C/No ratio, Doppler span and Doppler rate).

In high frequency bands (Ka and above), multimedia satellite communication systems may suffer from deep fading caused by atmospheric phenomena. Unfortunately, those deep atmospheric losses can no longer be overcome by a static link margin. Fade Mitigation Techniques (FMT) are then used to counteract those fades by enabling link adaptation according to propagation conditions. Without sacrificing bit error rate, FMT provide high average spectral efficiency by transmitting at high speeds under favorable channels conditions and by reducing throughput as the channel degrades. This capacity variation causes some difficulties to define resource management mechanisms, in particular the Connection Admission Control (CAC). Indeed a CAC function, which only uses current capacity information, may lead to intolerable dropping of admitted connection, and thus breaches the QoS guarantees made upon connection acceptance. This thesis focuses, then, on CAC mechanisms suitable for satellite systems with varying capacity. In those kinds of systems, CAC functions should estimate the possible evolution of the capacity. Therefore connections will only be admitted if the CAC function supposes the required capacity to be available for a long period of time. This kind of CAC is called as adaptive CAC. This work deals with the variation of the capacity by analyzing the different climatic phenomena and their prediction. The current study made on attenuation spatio-temporal models and their prediction showed their unsuitability for an adaptive CAC function. In fact, either they act over a very short period of time, typically some seconds, or they are too complex to be used within the context of a real system. Therefore, a simplified approach is argued in this study. It consists in separating the configuration where the Gateway/NCC is facing atmospheric impairments from the one where some user terminals face directly rain cells. For the admission policy, one could use one of the two CAC defined in this document, according to the way the system capacity varies in comparison with the connections duration : an optimistic CAC and a pessimistic CAC. This latter supposes the variation of the channel quality to be faster than connections duration. Therefore, the system capacity, on which connection admission decisions are based, corresponds to the case when the deepest fades occur. The optimistic policy is defined in the favorable case when channel quality varies slowly w.r.t to connections duration. The system capacity is, then, supposed to remain constant during connections lifetime. Thus, connection admission decision is made upon the current system capacity and the actual transmission condition faced by any of the user terminals.

The aim of this paper was to propose a way of improving the positioning performance of the GPS system through hybridization with distance measurements derived from GSM power measurements. Both GPS and GSM measurements were generated using simulation models. The algorithm chosen to perform the hybridization is a particle filter. Simulations showed that while accuracy can only be slightly improved, a position solution can be obtained even when the GPS system is not available, thus considerably improving availability.

The trajectory of Space Vehicles (SVs) derives due to external perturbations, such as the variation in the gravitation fields (earth, moon and sun) or the solar pressure effect. The station keeping of SVs is the operation that keeps the satellites in a predefined window. This operation implies that the SV position is known. Actual positioning systems for SVs are mainly based on ground equipment, that means heavy infrastructures. Autonomous positioning and navigation systems using Global Navigation Satellite System (GNSS) can then represent a great reduction in platform design and operating costs. This paper presents the configurations for Low Earth Orbit (LEO) and Geosynchronous Earth Orbit (GEO) missions. These configurations have been modeled from real mission parameters with the help of a dedicated software.

Header Compression techniques are now widely used in wireless and satellite communications. The main drawback of these techniques is to weaken the transmission against bit error or packet losses. Indeed, a corrupted or missing header can lead to a non-decompression of consecutive packets and then to a disconnection until the reception of a non-compressed packet. The parameters of the header compression system should then be carefully determined. In this paper, we first review the main header compression protocols standardized for a unidirectional link. This analysis allows us to build a simple generic header compression model depending on few parameters characterizing a header compression protocol. The evaluation of this model in cases corresponding to particular applications allows us to draw some first lessons for the use of header compression in Satellite communications.

This paper shows the interest of an interpolation method based on parametric modeling to retrieve missing samples in ECG signals. This problem occurs more and more with the emergence of telemedicine applications. The different links (fixed access network (PSTN), mobile access network (GSM/GPRS and future UMTS) or satellite interfacing (DVB- RCS technology)) involved in e-health applications are liable to induce errors on the transmitted data. These errors/losses can occur anytime and anywhere (according to the channel availability, memory overflows, protocols, etc) during a transmission process. Therefore the recovering of missing samples for biomedical signals is of great interest. The method used in this paper is based on a left-sided and right-sided autoregressive model, i.e., the interpolation algorithm uses the samples before and after the sequence of missing samples. An objective measure is used to assess the method performance. Results show that this interpolation method represents a really suitable technique to ECG signal reconstruction in a possible corrupted transmission.

In the past, in order for GPS (Global Positioning System) to work accurately, the presence of an unobstructed LOS (Line-Of-Sight) signal was necessary. Weak signals were not suitable for use because they may have large associated noise and other errors. The expansion of GPS to LBS (Location-Based Services) and other navigation applications all over the world, such as the E-911 and the E-112 mandates in the United States and Europe respectively, changed the paradigm. Consequently a dramatic increase in the need for more and more performant positioning techniques is expected, especially in urban and indoor environments. These rising localization requirements pose a particularly difficult challenge for GPS receivers design. The thesis objective is to evaluate and enhance existing GPS signal acquisition techniques for positioning goals in harsh environments, in the context of AGPS (Assisted GPS). The AGPS system assumes that the GPS receiver is connected to or introduced in a mobile phone. This allows for the transfer of AD (Assistance Data) to the GPS receiver via the GSM (Global System for Mobile communications) cellular network. Amongst others, the AD provides the GPS receiver with the list of visible satellites and estimates of their Dopplers and code delays, thus reducing the search window of these parameters. This work consists in exploring different GPS signal acquisition to reduce the acquisition time or TTFF (Time To First Fix), without affecting the receiver sensitivity. This is done after a prior study of the GPS radio channel. The study starts out with a revue of the GPS system and the GPS transmitted and received signal structure. The acquisition process is then described in details: the classical acquisition is first described in order to proceed afterwards with the impact of the propagation environment on this stage of the signal processing. For this purpose, harsh environments (urban and indoor) are modelled and analysed. This analysis enables to study the problems which encounter the radio frequency signal propagation through such environments. Note that the urban channel is studied using an existing statistical model developed by Alexander Steingass and Andreas Lehner at the DLR (German Aerospace Center) [Steingass et al., 2005]. On the other hand, an indoor channel model was developed by the ESA (European Space Agency) in the frame of a project entitled “Navigation signal measurement campaign for critical environments” and presented in [Pérez-Fontán et al, 2004]. But this model considers a time invariant statistical channel. Consequently, we developed an Indoor model which rather considers a time variant channel, by taking into account temporal variations of some channel parameters, like the transfer function delay and phase. The initial values are however based on the statistical distributions provided by the ESA model. The channels are analysed is terms of multipaths, cross-correlations and signal masking. The multipaths replicas are particularly disturbing in urban environments while the cross-correlations and masking effects are more disturbing in indoor environments. These phenomena may induce errors in the final solution calculated by the receiver. In order to avoid this error, one solution consists in increasing the signal observation duration in order to enhance the signal to noise ratio. But this generally implies longer acquisition time, thus affecting the receiver performance, commercially speaking. Indeed, the time requirements are as important as sensitivity requirements for GPS users. However, these two requirements are not generally compatible with each other. Consequently, an ideal solution consists in reducing the acquisition time without greatly affecting the receiver sensitivity. Accordingly, such advanced methods for acquisition signal processing are described next. Most of these methods aim at reducing the total acquisition time, rather than enhancing the receiver sensitivity. This means however that longer signal blocks can be processed (thus enhancing sensitivity) without affecting the global processing duration. At first, each of these methods is evaluated through the description of its advantages and drawbacks. A performance evaluation of these algorithms, using signals generated with a Spirent STR4500, ensues as a final step of this study.

It has already been shown that spectral estimation can be improved when applied to subband outputs of an adapted filterbank rather than to the original fullband signal. In the present paper, this procedure is applied jointly to a novel predictive autoregressive (AR) model. The model exploits time-shifting and is therefore referred to as time-shift AR (TSAR) model. Estimators are proposed for the unknown TS-AR parameters and the spectrum of the observed signal. The TS-AR model yields improved spectrum estimation by taking advantage of the correlation between subseries that arises after decimation. Simulation results on signals with continuous and line spectra that demonstrate the performance of the proposed method are provided.