Global Navigation Satellite Systems (GNSS) rely on estimating the signal propagation delay and Doppler shift to a set of visible satellites, which in turn allows to determine the receiver position, velocity and timing. However, the presence of interfering signals degrades the estimation of such synchronization parameters, reason why robust solutions must be accounted for. Considering constant modulus (CM) interferences, which include chirp and continuous wave signals, a recent solution proposed an expectation-maximization (EM) algorithm to estimate both interference and signal parameters, which relies on the von Mises distribution to exploit the interference CM property...

In the context of global navigation satellite systems (GNSS), synchronization is crucial for successfully decoding the navigation message and accurately estimating pseudoranges. Synchronization of each received GNSS signal typically involves at least two tracking loops: a delay lock loop (DLL) and a phase lock loop (PLL). The reception of a spoofed signal disrupts the synchronization process, potentially leading to erroneous pseudorange estimation or loss of service. This paper investigates the impact of spoofing on code, carrier phase, and frequency tracking estimates and proposes a transformation-based strategy to characterize the joint DLL and PLL under spoofing...

The projected rise in global temperatures and evolving wind patterns are expected to increasingly challenge aviation operations, particularly during the take-off phase, when aircraft performance is highly sensitive to ambient atmospheric conditions. In this study, a multidisciplinary framework is developed to quantify the combined impact of temperature rise and headwind variability on take-off field length (TOFL) at 60 major global airports. Climate projections are drawn from a multi-model ensemble of 26 bias-corrected members across six CMIP6 models, using the CDFt bias correction method with historical ERA5 reanalysis as reference. The correction is validated over the...

Despite being considered a hard-to-abate sector, aviation’s emissions will play an important role in long-term climate mitigation of transportation. The introduction of low-carbon energy carriers and the deployment of new aircraft in the current fleet are modeled as technology-centered decarbonization policies, while supply constraints in targeted market segments are modeled as demand-side policies. Shared Socioeconomic Pathways (SSPs) are used to estimate trend traffic demand and to limit the sectoral consumption of electricity and biomass. Mitigation scenarios are formulated as optimization problems, and three applications are demonstrated: no-policy baselines, single...

For almost 100 years, the incompleteness of quantum formalism and the probabilistic nature of measurement have been debated without any experiment being able to settle these questions. There exist contingent quantum interpretations that share the same mathematical formalism but have contradictory world views. In double-slit interference experiments, standard quantum theory does not take particle size into account, which is not the case in de Broglie’s double solution theory. We use the large size of Rydberg atoms to propose an experiment to test the incompleteness of the standard quantum formalism. We present an interference experiment with asymmetric slits, a large slit...

<div><p>Airports, as critical hubs connecting air and ground transportation, play a key role in managing airspace and ground resources. However, increasing flight volumes and dynamic ground conflicts present significant challenges to accurately predicting taxi times and push-back schedules. These uncertainties make it difficult for existing routing methods to coordinate taxiway usage with runway scheduling. To address this issue, this paper introduces a Reverse Time-Window-based Multiobjective A* algorithm (R-TMOA*), which optimizes taxi routes by routing backward from the runway to the stand. This approach enhances taxi time predictions and improves alignment with DMAN...

This paper describes a dedicated approach to solve the 2025 NASA-DNV UQ challenge problem using adaptive Gaussian process strategies. The uncertainty model is determined through a calibration problem using an optimization approach to identify the aleatory variable joint distribution and the epistemic variable uncertainties. The estimation of the prediction interval for the model output components consists of a quantile estimation problem based on an adaptive Gaussian process strategy. Eventually, the design optimization problems are solved using Bayesian optimization controlling the noise level involved in the estimation of the objective and constraint functions.

Dans les processus de décision markoviens orientés but avec états catastrophiques, nous travaillons dans un cadre de maximisation d'utilité, une fonction qui prend en compte à la fois le coût cumulé et l'atteinte ou non du but. Ce cadre intègre un paramètre K g représentant le bonus que l'agent reçoit lorsqu'il atteint un état but. Notre contribution principale est une formule analytique qui, pour un seuil de probabilité d'attendre le but P th spécifié par l'utilisateur, détermine la valeur minimale de K g garantissant que la politique optimale respecte ce seuil de sécurité. Cette transformation du MDP permet ainsi d'utiliser toutes les méthodes classiques et efficaces de...

<div><p>Flight instructors are vital in the training of novice pilots. Just as the mental workload in student pilots fluctuates during training, so does the mental workload of the instructors, affecting their dyadic performance and judgment. This paper explored how training environments (simulated vs. real flight), flight control conditions (student pilot flying vs. monitoring), and flight phases (take-off vs. downwind vs. landing) could affect mental workload in student and instructor pilots, as well as their interpersonal coordination through electrocardiography (ECG) based measures. Student pilots performed four consecutive standard flight traffic patterns with an...