Le (M, g) be a Riemannian manifold equipped with a pair of dual connections (∇, ∇ *).Such a structure is known as a statistical manifold since it was defined in the context of information geometry. This paper aims at defining the complete lift of such a structure to the cotangent bundle T * M using the Riemannian extension of the Levi-Civita connection of M.In the first section, common tensors associated with pairs of dual connections, emphasizing the cyclic symmetry property of the so-called skewness tensor. In a second section, the complete lift of this tensor is 6 obtained, allowing the definition of dual connections on TT * M with respect to the Riemannian extension.

Satellite-Based Augmentation Systems (SBAS) provide single-frequency services for aeronautical users by broadcasting corrections and integrity information on L1 frequency. Future dual-frequency services for aeronautical users will be broadcast on L5-I/E5a-I frequency. New services that could be potentially provided by SBAS to non-aeronautical community are currently being investigated. These services may require higher data rates that challenge current SBAS signal definitions. Considering there is, at this time, no standardized SBAS signal neither on L5/E5a-Q component nor on E5b frequency band, an opportunity to evaluate new signal candidates is identified. In this paper...

During the COVID-19 period and particularly during lockdown, the number of speeding offences on the roads have tended to increase. Likewise in the air, deviation from nominal operations have shown to become more frequent. This paper proposes to evaluate the impact of COVID-19 on the pilot/controller system, especially during the critical approach and landing phases. To study the influence of COVID-19, an existing energy atypicality metric is applied on a reference period before COVID-19 and compared to the COVID-19 period. Trends, statistics, and specific flights are illustrated and analyzed, underlying an increase in glide interceptions from above and high speed...

Animated visualizations are one of the methods for finding and understanding complex structures of time‐dependent vector fields. Many visualization designs can be used to this end, such as streamlines, vector glyphs, and image‐based techniques. While all such designs can depict any vector field, their effectiveness in highlighting particular field aspects has not been fully explored. To fill this gap, we compare three animated vector field visualization techniques, OLIC, IBFV, and particles, for a critical point detection‐and‐classification task through a user study. Our results show that the effectiveness of the studied techniques depends on the nature of the critical...

Global Navigation Satellite System (GNSS) L5/E5a interference environment is dominated by DME/TACAN and JTIDS/MIDS pulses causing a degradation of the effective Carrier to Noise (C/N0) observed by the receiver. This causes delay for the receiver satellite acquisition and impacts the tracking capability. As a mitigation technique, a time-domain blanker is implemented to mitigate their impact. RTCA DO-292 proposes a model to compute the (C/N0) degradation of the received useful signal by the increase of the noise power spectral density (PSD). This paper developed by ENAC and The MITRE Corporation as part of their cooperative efforts to support RTCA analyses, focus on the...

Accurate prediction of aircraft arrival times is one of the fundamental elements for air traffic controllers to manage an optimal arrival and departure sequencing on the runway, reduce flight delays, and achieve a good collaboration with airports and airlines. In this work, we analyze the feature engineering problem to predict Aircraft Landing Time (LDT) in Extended-TMA with machine learning models. Two main contributions are highlighted in this work. First, the impact of different features in LDT prediction is investigated. Second, a machine learning prediction model is presented to predict LDT. Our case of study is the E-TMA of Singapore Changi Airport (WSSS) with a...

In this paper, we introduce new indices adapted to outputs valued in general metric spaces. This new class of indices encompasses the classical ones; in particular, the so-called Sobol indices and the Cramér-von-Mises indices. Furthermore, we provide asymptotically Gaussian estimators of these indices based on U-statistics. Surprisingly, we prove the asymp-totic normality straightforwardly. Finally, we illustrate this new procedure on a toy model and on two real-data examples.

This paper presents a preliminary study of a new inversion strategy combining the method of adjoint applied to the wide-angle parabolic equation and the method of split-step wavelet for tropospheric refractivity estimation. Our main motivation is to use a gradient based optimization method to infer atmosphere from radio-frequency data, in an effort towards a real-time accurate refractivity-from-clutter system. The proposed adjoint formulation is validated with the method of finite differences. The validation setup is developed for inversion using a tomographic approach.

Ground-based aircraft trajectory prediction is a major concern in air traffic management. Focusing on the climb phase, neural networks are trained to predict some of the unknown point-mass model parameters. These unknown parameters are the mass and the speed intent. For each unknown parameter, our model predicts a Gaussian distribution. This predicted distribution is a predictive distribution: it is the distribution of possible unknown parameter values conditional to the observed past trajectory of the considered aircraft. Using this distribution, one can extract a predicted value and the uncertainty related to this specific prediction. This study relies on Automatic...