Jean-Francois Bousquet

This article presents a flux-tunable Josephson Parametric Amplifier (JPA), where a linear model of the circuit allows small-signal S-parameter analysis for quantum magnetometer applications. By modeling the superconducting quantum interference device (SQUID) as a flux-modulated inductor, simulation results verify the proposed negative-resistance models, demonstrating the gain–bandwidth range of a phase-insensitive degenerate JPA. A pump signal controls the nonlinear inductance, and for a small input signal, a matching circuit is designed using S-parameter simulations. The impedance-matching network is designed using a single-stub configuration by applying an equivalent Smith chart transformation to optimize gain and stability. This work offers a potential strategy for integrating JPAs into cryogenic quantum sensors.

In this work, the use of magnetic induction to cross the air-water boundary is investigated. An analytical expression is derived for the magnetic field in air from a coil underwater and is validated with simulation results that also include the effect of the front-end. Specifically, the ratio of the induced voltage of the receiver over transmitter current is maximized for a given distance between small coils with a radius of 6.5 cm and it is found that an optimal frequency exists: for a distance between 10 to 100 meters, the optimum frequency of operation decreases from 8000 Hz down to 80 Hz. Experiments are performed in air as well as in sea-water tanks to verify the mutual inductance and end-to-end attenuation. The experiments agree with the theory for distances up to 1.6 meters, after which a noise floor is reached. To increase the range, the use of passive repeaters is studied and a relay coil that transfers the energy to a receiver inside a magnetic shield is analyzed. When configured correctly, this relay can significantly enhance the receiver output voltage, as demonstrated through simulations, potentially increasing it by up to tenfold.

This article presents a channel state information acquisition approach based on a Markov chain process that exploits information from the physical environmental conditions, including the tide phase and flow. The method is intended to predict channel characteristics, including the gain, delay, and Doppler spread, as well as the standard deviation of intrapath delays in time-varying conditions. Specifically, the correlation between different oceanic processes and the acoustic channel characteristics is confirmed to define a set of tide-dependent states corresponding to a particular channel condition. Channel soundings from a 34-day sea trial conducted in Grand Passage, Nova Scotia, are used to derive the channel characteristics statistics. For this purpose, channel soundings measurements are applied to a parametric model of the propagation channel. The probabilistic parametric model forms a data set by characterizing the time-varying channel impulse response and describing the channel tapped-delay structure statistically as a function of different tide phases. The proposed Markov chain is driven by the measured channel data set and predicts the future channel characteristics one tide cycle ahead. To validate the accuracy of the proposed method, the predicted channel characteristics are compared to the channel measurements obtained in a 566-m channel in Grand Passage, Nova Scotia.

In this work, a hardware-in-the-loop (HIL) simulator is designed to diagnose the behavior of an autonomous sailboat as it navigates between waypoints. At its core, the HIL simulator includes the sailboat pilot on an embedded system. The sensor data input to the embedded system is fed by a navigation simulator that takes into account the different forces on the sailboat due to the wind, waves and current conditions. The HIL simulator is then tested for a navigation route from sea trials published in 2014, and the behavior of the automated pilot is compared to its behavior when the vessel is driven by a crew. As demonstrated, the automated system can outperform the man-operated vessel. The tool is also used to diagnose weaknesses in the sailboat autopilot algorithm that can be improved in the future.

The objective of this work is to develop a localization system using a compact array capable of obtaining a coarse estimate of the location of high frequency echolocation pulses emitted by harbour porpoises. This work improves upon a traditional grid search by using a lookup table which is stored in a hyperoctree to reduce the computation time required to perform the localization. Additionally, the impact of the sensor geometry is analysed to improve the accuracy of an existing sensor configuration. Finally, the impact of the noise on the measured signal is analysed and mitigated by using various preprocessing techniques.