Les produits d’intermodulation passifs ne suivent pas la loi classique d’augmentation de puissance de 3 dB par dB de puissance d’entrée. Un modèle basé sur des fonctions non-analytique permet de simuler correctement ce comportement pour deux ou plusieurs porteuses. Le modèle explique l’amélioration du rapport C/I lorsque le nombre de porteuses augmente et permet de calculer cette amélioration à partir des mesures à deux porteuses et de la pente. Ceci permet de relâcher les spécifications à deux porteuses de 4 dB si la pente est de 2,5 dB/dB et de 8 dB si la pente est de 2 dB/dB pour une même performance en multi-porteuse. Cette relaxation peut permettre d’utiliser une technologie d’antenne de masse ou de coût plus faible alors qu’elle n’aurait pas été acceptée en l’absence de modèle.

We propose to use memristors as memory nonlinear circuits to build behavioral models useful in the simulation of passive inter-modulation in RF and microwave devices such as filters, antennas and in general connections

Leon Chua introduced memristors in 1971 [1] as an ideal two-terminal circuit element in complement to the already known three basic circuit elements: resistor, inductor and capacitor (RLC). Memristors are defined by a non-linear memristance that relates the flux (or integral of voltage across the device) to the charge (or integral of current in the device). Because of this definition the memristor will generate passive intermodulation products and their power will depend on the memory of the past current that is contained in the device.

Non-analytic behavioral models of passive non linearity presented in 2013 are used to define and propose new specifications for multicarrier passive intermodulation in antennas. A margin of up to 10 dB is obtained in some cases and can be used to relax 2-carrier PIM specifications.

Global aircraft optimization is a main concern for future and upcoming programs. In particular, great research efforts are dedicated to Electrical Flight Control Systems (EFCS). Obviously, their reliability increases with the redundancy of the flight parameter sensors. However, physical redundancy, obtained by increasing the number of sensors, penalizes the aircraft weight and cost. This paper proposes a sensor failure detection method based on analytic redundancy. The flight parameter of interest is modelled as a linear function of independent sensor measurements on a sliding observation window. The Partial Least Squares (PLS) algorithm is used to estimate regression coefficients on this window. The PLS computes the solution via an iterative processing, and thus can be implemented in the flight control computer for a real time use. Two different failure detection strategies based on the behaviour of the regression coefficients are proposed. Simulation results show that the proposed method leads to robust detections.

Electrical Flight Control Systems (EFCS) now constitute an industrial standard for commercial applications, ensuring a more sophisticated control of the aircraft and flight envelope protection functions. In the scope of a global optimization towards extended system availability and more easy-to-handle aircraft, sophisticated tools are necessary to diagnose sensor behaviour and to prevent from faulty measurements. In this context, a signal processing approach using Partial Least Squares (PLS) has been proposed to increase the EFCS autonomy. This algorithm establishes a linear relation between observed flight parameters - issued from possibly faulty sensors - and independent sensor measurements thanks to an iterative process. A monitoring strategy based on the regression coefficient dynamics, provided by the PLS, has been implemented and tested on real flight data and through an Airbus high-fidelity simulator, including realistic failure scenarios. The simulation results demonstrate the method performance robustness, in compliance with current real-time constraints. This paper focuses on the application of the method to the industrial context. A special attention is dedicated to the simulation process and to the performance analysis.

The SARGOS project aims to satisfy the strong emerging need to improve safety for the civilian offshore infrastructures, sensitive to the actions conducted by spite, piracy or terrorism on sea. SARGOS brings a new and innovative answer in this field of maritime security. A special care is taken to comply with the infrastructures operational constraints and the contractual and legislative rules. The innovative part of the project is mainly the global approach used, based on three levels: a) The level of a safe detection of a small size marine object, in a small range protection area, with rough sea, using innovative CW radar waveforms improved by new efficient signal processing algorithms b) The level of construction of a response plan facing a detected intrusion, taking into account the progressive improvement of the knowledge and the kind of detected object defined by its characterisation attributes. The acquisition process allows appropriate responses taking into account the crisis situation. (Platform safety rules, geopolitical environment and legal aspects). c) The managing level of the variety of non-lethal response means, either internal to the offshore platform (predefined security procedures, safety mode), or external to reply to the menace (injunction, intimidation or, as a last resort, activation of authorised means) and broadcast the alert to the local authorities. This article presents more specifically the main functionalities and the design of SARGOS system.

Subband decomposition has already been shown to increase the performances of spectral estimation but induced frequency overlapping may be troublesome, bringing edge effects, when spectral estimation is applied after subband decomposition and decimation. This paper proposes a new spectral estimation procedure based on subband decomposition and frequency warping which reduces the overlapping frequency problem. Simulation results confirm the interest of this new algorithm.

This paper addresses the problem of frequency overlapping which occurs when spectral estimation is applied after subband decomposition. Subband decomposition has already been shown to increase the performances of spectral estimation but induced frequency overlapping may be troublesome. This paper proposes a new spectral estimation procedure based on sub band decomposition and frequency warping which reduces the overlapping frequency problem. Simulations confirm the interest of this new algorithm.