The recent decades have seen an increasing interest in Medium Earth Orbit and Low Earth Orbit satellite constellations. However, there is little information on the delay variation characteristics of these systems and the resulting impact on high layer protocols. To fill this gap, this paper simulates a constellation that exhibits the same delay characteristics as the already deployed Iridium but considers closer bandwidths to constellation projects'. We identify five major sources of delay variation in polar satellite constellations with different occurrence rates: elevation, intra-orbital handover, inter-orbital handover, orbital seam handover and Inter-Satellite Link changes. We simulate file transfers of different sizes to assess the impact of each of these delay variations on the file transfer. We conclude that the orbital seam is the less frequent source of delay and induces a larger impact on a small file transfers: the orbital seam, which occurs at most three times during 24 hours, induces a 66% increase of the time needed to transmit a small file. Inter-orbital and intra-orbital handovers occur less often and reduce the throughput by approximately about 8% for both low and high throughput configurations. The other sources of delay variations have a negligible impact on small file transfer, and long file transfers are not impacted much by the delay variations.

Recently, the joint design of the GNSS message structure and the associated channel‐coding scheme have been investigated as a means to reduce the Time‐To‐First‐Fix (TTFF) and particularly the time to retrieve the Clock and Ephemerides Data (CED). In this context, a new method to co‐design the navigation message and the channel‐coding scheme structure is proposed in this paper. This new co‐design enables us to reduce the time to retrieve the CED while enhancing error‐correction capabilities under degraded channel conditions. In order to fulfill such requirements, some structured coding schemes are designed, which provide both maximum distance separable (MDS) and full diversity properties under a non‐ergodic channel assumption.

In this paper, we study the the complexity of packet localization at reception, for recent synchronous Random Access (RA) techniques based on the protocol ALOHA for satellite communications. The promising CRDSA (Contention Resolution Diversity Slotted ALOHA) offers better throughput, in comparison to the traditional slotted ALOHA protocols, thanks to the use of Successive Interference Cancellation (SIC) along with multireplica transmission. MARSALA (Multi-replicA decoding using corRelation baSed locALizAtion) is one of the many variants and enhancement schemes of CRDSA that have been proposed in the literature. It is applied to CRDSA each time a decoding deadlock situation is reached (when no packets can be retrieved by CRDSA). MARSALA first localizes the replicas of collided packets on a chosen reference time slot using correlations. Then it performs coherent signal combination of packet replicas prior to decoding. However, despite the good performance offered by MARSALA, its localization process adds a significant complexity to the receiver in terms of correlation operations. R-SPOTiT (Random Shared POsition Technique for Interfered random Transmissions) mitigates this complexity by introducing a shared information between the receiver and each of the transmitters, about all potential packets' locations on the frame, without any additional signaling overhead. We focus in this paper on the analysis of the total number of correlations which are needed to localize packets' replicas for both MARSALA and R-SPOTiT, with a single or with multiple Gold preambles. This should include preamble detection operations that are performed at CRDSA with a coarse and fine tracking. The results show that the most suitable system to use is the multi-preamble R-SPOTiT with two preambles.

As part of aircraft certification and optimization, wing bending and twist measurements are performed under various load cases (aircraft weight, speed, angle of attack, etc.) to validate and improve wing deformation models. Since these measurements are acquired during flight, their analysis requires to face strong environmental constraints. Indeed, the highly varying luminosity conditions, the presence of possible reflections or shadows, the vibrations and the deformations of the entire aircraft, are strong constraints that need to be considered carefully. Current approaches applied in Airbus are based on inertial measurement units installed inside the wing, or on photogrammetry-based solutions using calibrated sensors and retro-reflective targets located on the wings. These methods are not only highly intrusive, but also require time-consuming installation, calibration phases and dedicated flights to produce only sparse measurements. Moreover, the use of reflective targets on the wing has an impact on the wing aerodynamic, which should be avoided. In this paper, we investigate a new method for estimating wing deformations. This method adapts a photogrammetry approach classically used for reconstructing buildings or art structures to the aircraft environment. To this aim, we propose to use synchronous videos from high resolution cameras, which can be easily installed on the aircraft windows and on the vertical stabilizer. Appropriate features are extracted from the images acquired by these cameras, related to wing joints or reference points located on the aircraft wing. The system uses these features to autonomously recalibrate itself at each frame and provide a dense 3D reconstruction of the wing in the aircraft reference coordinate system. Some experiments conducted on real data acquired on Airbus aircrafts show that the proposed estimation method provide promising results.

Global Navigation Satellite Systems (GNSS) are the main source of position, navigation, and timing (PNT) information and will be a key player in the next-generation intelligent transportation systems and safety-critical applications, but several limitations need to be overcome to meet the stringent performance requirements. One of the open issues is how to provide precise PNT solutions in harsh propagation environments. Under nominal conditions, the former is typically achieved by exploiting carrier phase information through precise positioning techniques, but these methods are very sensitive to the quality of phase observables. Another option that is gaining interest in the scientific community is the use of large bandwidth signals, which allow obtaining a better baseband resolution, and therefore more precise code-based observables. Two options may be considered: (i) high-order binary offset carrier (HO-BOC) modulations or (ii) the concept of GNSS meta-signals. In this contribution, we assess the time-delay and phase maximum likelihood (ML) estimation performance limits of such signals, together with the performance translation into the position domain, considering single point positioning (SPP) and RTK solutions, being an important missing point in the literature. A comprehensive discussion is provided on the estimators’behavior, the corresponding ML threshold regions, the impact of good and bad satellite constellation geometries, and final conclusions on the best candidates, which may lead to precise solutions under harsh conditions. It is found that if the receiver is constrained by the receiver bandwidth, the best choices are the L1-M or E6-Public Regulated Service (PRS) signals. If the receiver is able to operate at 60 MHz, it is recommended to exploit the full-bandwidth Galileo E5 signal. In terms of robustness and performance, if the receiver can operate at 135 MHz, the best choice is to use the GNSS meta-signals E5 + E6 or B2 + B3, which provide the best overall performances regardless of the positioning method used, the satellite constellation geometry, or the propagation conditions.

Named Data Networking (NDN), an Information-Centric Network (ICN) architecture, is based on caching, multipath and multi-producers retrieving. These properties provide new opportunities for a single user to increase its Quality of Experience (QoE). However, handling multiple flows, each of them having its own multiple paths, is more complex. To tackle this challenge, we highlight three main principles a solution should include. Nodes should cooperate, supervise their output queues and, eventually, wisely manage the multipath capacities of NDN. These three elements are the core of our proposition : Cooperative Congestion Control (CCC). More than a solution, CCC is proposed as a framework where each principle could be implemented in multiple ways. The ultimate objective is to fairly distribute the flows on the network and maximize QoE of users. We choose basic algorithms in order to evaluate the overall framework. We evaluate our solution with simulations and compare their results with a theoretical model.

The derivation of tight estimation lower bounds is a key tool to design and assess the performance of new estimators. In this contribution, first, the authors derive a new compact Cramér–Rao bound (CRB) for the conditional signal model, where the deterministic parameter's vector includes a real positive amplitude and the signal phase. Then, the resulting CRB is particularised to the delay, Doppler, phase, and amplitude estimation for band-limited narrowband signals, which are found in a plethora of applications, making such CRB a key tool of broad interest. This new CRB expression is particularly easy to evaluate because it only depends on the signal samples, then being straightforward to evaluate independently of the particular baseband signal considered. They exploit this CRB to properly characterise the achievable performance of satellite-based navigation systems and the so-called real-time kinematics (RTK) solution. To the best of the authors’ knowledge, this is the first time these techniques are theoretically characterised from the baseband delay/phase estimation processing to position computation, in terms of the CRB and maximum-likelihood estimation.

The release of Android GNSS raw measurements, in late 2016, unlocked the access of smartphones’ technologies for advanced positioning applications. Recently, smartphones’ GNSS capabilities were optimized with the release of multi-constellation and multi-frequency GNSS chipsets. In the last few years, several papers studied the use of Android raw data measurements for developing advanced positioning techniques such as Precise Point Positioning (PPP) or Real-Time Kinematic (RTK), and quantified those measurements compare to high-end commercial receivers. However, characterizing different smartphone models and chipset manufacturers in urban environment remains an unaddressed challenge. In this paper, a thorough data analysis will be conducted based on a data collection campaign that took place in Toulouse city center. Collaborative scenarios have been put in place while navigating in deep urban canyons. Two vehicles were used for this experiment protocol, equipped with high-end GNSS receivers for reference purposes, while seven smartphones were tested. Android algorithms reliability of both the multipath and cycle slip flags were investigated and evaluated as potential performance parameters. Our study suggests that their processing may differ from one brand to another, making their use as truthful quality indicators for collaborative positioning yet open to debate.

In previous works, new families of Pseudo-Random Noise (PRN) codes of length 1023 chips were proposed in order to ease the acquisition engine. These studies analyzed several metrics for code design in order to improve the acquisition but no analysis was conducted on the estimation performance, which in turn drives the final position, velocity and timing estimates. The main goal of this contribution is to assess if these new PRN codes designed to improve the acquisition engine lose in achievable time-delay estimation performance with respect to the standard GPS L1 C/A Gold codes. The analysis is performed by resorting to a new compact closed-form Cramér-Rao bound expression for time-delay estimation which only depends on the signal samples. In addition, the corresponding time-delay maximum likelihood estimate is also provided to assess the minimum signal-to-noise ratio that allows to be in optimal receiver operation.