This paper introduces a new statistical model for clock phases assuming a multivariate Gaussian distribution for the clock phase deviations from a common time scale. This model allows us to derive a maximum likelihood estimator for the clock phases, which is consistent with the current methods of computing a common time scale for a collection of clocks. Detailing a statistical model of the clock phases, which assumes a Gaussian distribution allows us to find the MLE for each clock’s phase deviation from a common time scale. For verification, the MLE for the clock phases is shown to be consistent with the result of the existing basic time scale equation. The statistical distribution of the frequency states resulting from this statistical model is Gaussian over a window of past time instants. This property can be used to design a new time scale based on the maximum likelihood estimator of frequency and frequency variances that are alternatives to the exponential filters designed for AT1. With the appropriate number of past frequency samples, this MLE has identical performance to the optimal AT1 algorithm in a nominal context. The statistical distribution of the frequency when the clock suffers a phase jump anomaly is then identified as a Student’s t-distribution. The Student’s t-distribution models the statistics of datasets contaminated by outliers, leading to the derivation of a different MLE that is robust to those outliers. The time scale using the robust MLE provides estimates of each clock’s frequency and frequency variance that are unaffected by phase jump anomalies and improves the long-term frequency stability when each clock in the ensemble experiences phase jump anomalies within some window of time.

Precise positioning (based on Precise Point Positioning, PPP, or Real Time Kinematics, RTK) is steadily gaining momentum. The main difficulty when using carrier phase measurements remains to correctly estimate their ambiguities: not only is it a computationally intensive process, but it can be affected by cycle slips (CS), which are brutal variations in ambiguity values, due to receiver’s dynamics or unfortunate reception events. As GNSS constellations are now able to provide users with signals on three different frequencies, the concept of Triple Carrier Ambiguity Resolution has become widespread. It typically relies on the use of widelane signals, which are combinations of raw signals and are defined as to have an apparent wavelength much higher than original signals, thus making accelerating the ambiguity fixing process and reducing the frequency of cycle slips. However, CS may remain a problem for the availability of precise positioning services. The present paper therefore focuses on a cycle slip detection method, based on a hypothesis test. The main idea consists in using both code and widelane phase measurements to compute a geometry- and ionospheric-free test vector, theoretically containing only noise and possible cycle slips. The latter can be detected by looking for brutal changes on the average of the test vector. Performance is assessed on simulated and Rinex data.

This paper proposes methods designed to optimize and robustify the demodulation of the Time Of Week information contained in the GALILEO navigation message. The TOW is crucial to the determination of user’s Position-Velocity-Time and is broadcasted several times in each message frame. The redundancy and predictability of the successive TOW values can be used to reduce the probability of a demodulation error. Three methods are proposed to take advantage of this, two are empirical methods, the third consists in considering the sequence of TOWs and determining the values which maximize reception probability.

This paper presents an analysis on the implementation on a GNSS signal of a Code Shift Keying (CSK) modulation: an orthogonal M-ary modulation specifically designed to increase the bandwidth efficiency of direct-sequence spread spectrum (DS-SS) signals. Two decoding methods are presented as suitable candidates to be implemented by a CSK modulation with a LDPC channel code: classical sequential decoding and Bit-interleaved coded Modulation – Iterative Decoding (BICM-ID). Afterwards, this paper presents the methodology used to construct CSK signals which increase the useful bit rate with respect to a BPSK signal but maintaining the same symbol rate. This methodology includes the calculation and comparison of signal demodulation performances in AWGN and mobile channels, the generation of CSK symbols allowing the desired bit rate and the determination of the codeword durations. Proposals for real signals have been made. Finally, this paper analyses the impact of processing a CSK modulated signal on a GNSS receiver with respect to a BPSK signal. This analysis includes the increase of complexity of the demodulator block and the possible performance degradation of the acquisition and, the carrier and code delay tracking.

This paper addresses the problem of ship localization by using the messages received by satellites and transmitted by the automatic identification system (AIS). In particular, one considers the localization of ships that do not transmit their actual position in AIS signals. The proposed localization method is based on the least squares algorithm and uses the differences of times of arrival and the carrier frequencies of the messages received by satellite. A modification of this algorithm is proposed to take into account the displacement model of the ships as additional measurements. This modification shows a significant localization improvement.

This paper presents the modelling of new WLAN models for different indoor environments. This work was carried out in the frame of the FIL project which is funded by the French research agency ANR, in collaboration with Thales Alenia Space France. Based on the standard Opnet models for WLAN nodes, the propagation loss estimation for these types of environment has been improved. We derive an empirical model for spatial registration patterns of mobile users as they move within a TeSA Labs wireless local area network (WLAN) environment and register signal power from different access points. Such a model can be very useful in a variety of simulation studies of the performance of mobile wireless systems, to address issues such as resource management and mobility management protocols. We base the model on extensive experimental data from a TeSA Labs 2.4 GHz WiFi LAN installation. We divide the empirical data available to us into training and test data sets, develop the model based on the training set, and evaluate it against the test set. The new scenarios used to simulate these new propagation models are shown. Finally, results, conclusions and further work are given.

In this paper, a way of improving the positioning performance of the GNSS system through hybridization with distances derived from GSM power measurements was proposed. The GNSS/GSM Fusion algorithm was an APF (Auxiliary Particle Filter) algorithm with UKF (Unscented Kalman Filter) proposal and Rao-Blackwellisation allowing tight hybridization of GPS and GSM measurements. Scenario 1 and 2 showed an improvement in terms of accuracy and availability thanks to the use of GSM received powers in addition to GPS pseudoranges in a realistic scenario. Several perspectives can be given: First, the automatic estimation of hyperparameters: PF algorithms can be used to perform joint estimation of some global parameters (as for instance observation and evolution noises variances). This would give the fusion algorithm a better adaptability to local situations. Finally, the use of “multiple models” formulation can be envisaged: ability of PF algorithms to select automatically the most adapted model among a bank of available evolution and observation models. This would allow the algorithm to deal better with multipath effects.

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 European satellite navigation system GALILEO will provide radionavigation signals for a variety of applications. Safety Of Life users will get a safe navigation service through ranging signals carrying integrity information. The Galileo Integrity Baseline algorithm includes the transmission of three parameters allowing users to monitor their integrity level. These parameters are the Signal-In-Space Accuracy (SISA: prediction of the minimum standard deviation of a Gaussian distribution overbounding the Signal-In-Space error in the fault-free case), the Signal-In-Space Monitoring Accuracy (SISMA: minimum standard deviation of a Gaussian distribution overbounding the difference between Signal- In-Space error and its estimation by ground control stations) and the Integrity Flag, which accounts for satellite status (it can be set to 'OK', 'DON'T USE' or 'NOT MONITORED'). These parameters are part of the input of the user integrity algorithm, which computes user integrity risk at the alert limit and compares it to the Integrity Risk requirement corresponding to user's phase of flight. The work presented in this paper studies the influence of the algorithm used for computation of SISMA on user integrity and system availability. The algorithms used to compute SISMA are the reference Least-Squares and several robust methods, designed to reject wrong measurements and decrease ground system False Alarm rate (fault-free satellites flagged 'DON'T USE').

The European satellite navigation system GALILEO will provide radio-navigation signals for a variety of applications. Safety Of Life users will get a safe navigation service through ranging signals carrying integrity information. The Galileo Integrity Baseline algorithm includes the transmission of three parameters allowing users to monitor their integrity level. These parameters are the Signal-In- Space Accuracy (SISA: prediction of the minimum standard deviation of a Gaussian distribution overbounding the Signal-In-Space error in the fault-free case), the Signal-In-Space Monitoring Accuracy (SISMA: minimum standard deviation of a Gaussian distribution overbounding the difference between Signal-In-Space error and its estimation by ground control stations) and the Integrity Flag, which accounts for satellite status (it can be set to “OK”, “DON’T USE” or “NOT MONITORED”). The work presented in this paper studies the possibility of computing SISMA using a statistically robust algorithm, so as to reject wrong measurements and decrease ground system False Alarm rate (fault-free satellites flagged “DON’T USE”).