This dissertation is the combination of three manuscripts –either published in or submitted to journals– on compressive sensing of propeller noise for detection, identification and localization of water crafts. Propeller noise, as a result of rotating blades, is broadband and radiates through water dominating underwater acoustic noise spectrum especially when cavitation develops. Propeller cavitation yields cyclostationary noise which can be modeled by amplitude modulation, i.e., the envelope-carrier product. The envelope consists of the so-called propeller tonals representing propeller characteristics which is used to identify water crafts whereas the carrier is a stationary broadband process. Sampling for propeller noise processing yields large data sizes due to Nyquist rate and multiple sensor deployment. A compressive sensing scheme is proposed for efficient sampling of second-order cyclostationary propeller noise since the spectral correlation function of the amplitude modulation model is sparse as shown in ...

THIS doctoral thesis attemps to propose a novel signal processing chain, aimed to exploit data acquired by long wave infrared (LWIR) hyperspectral sensors. In the LWIR, infrared radiation from an object is directly related to its temperature, i.e. hotter the surface, higher the emitted thermal energy. Hyperspectral sensors capture the radiated energy from the objects (target) in a large number of consecutive spectral bands within the LWIR, e.g. with the aid of a prism, in order to estimate the spectrum(spectral emissivity) and the temperature of the surface material. In this framework, two main challenging tasks affect the development and the deployment of thermal hyperspectral sensors: - atmospheric correction: the process of estimate and compensate the thermal radiation produced by the atmosphere, that affects the thermal radiation procuded by the target. This process is made more complicated by the complex combination ...

The recent announcement by the LIGO and Virgo Collaborations of the direct detection of gravitational waves started the era of gravitational wave astrophysics. Up to now there have been five confirmed detections (GW150914, GW151226, GW170104, GW170814 and GW170817). Each of the GW events detected so far, shed light on multiple aspects of gravity. The first four events were due to the coalescence of a binary black hole system. August 17th 2017 marked the beginning of the so-called Multi-Messenger astronomy: the binary neutron star merger GW170817 has been observed almost simultaneously by LIGO and Virgo interferometers and several telescopes in space and on Earth, which detected the electromagnetic counterpart of this event (first as a short gamma-ray burst, GRB 170817A, and then in the visible, infra-red and X-ray bands). These last two years of great scientific discoveries would not have been ...

Mapping stationary objects and tracking moving targets are essential for many autonomous functions in vehicles. In order to compute the map and track estimates, sensor measurements from radar, laser and camera are used together with the standard proprioceptive sensors present in a car. By fusing information from different types of sensors, the accuracy and robustness of the estimates can be increased. Different types of maps are discussed and compared in the thesis. In particular, road maps make use of the fact that roads are highly structured, which allows relatively simple and powerful models to be employed. It is shown how the information of the lane markings, obtained by a front looking camera, can be fused with inertial measurement of the vehicle motion and radar measurements of vehicles ahead to compute a more accurate and robust road geometry estimate. Further, it ...

Machine vision applies computer vision to industry and manufacturing in order to control or analyze a process or activity. Typical application of machine vision is the inspection of produced goods like electronic devices, automobiles, food and pharmaceuticals. Machine vision systems form their judgement based on specially designed image processing softwares. Therefore, image processing is very crucial for their accuracy. Food industry is among the industries that largely use image processing for inspection of produce. Fruits and vegetables have extremely varying physical appearance. Numerous defect types present for apples as well as high natural variability of their skin color brings apple fruits into the center of our interest. Traditional inspection of apple fruits is performed by human experts. But, automation of this process is necessary to reduce error, variation, fatigue and cost due to human experts as well as to increase ...

With the continuous growth in demand for air traffic and wind turbines, the noise emissions they generate are becoming an increasingly important issue. To reduce their noise levels, it is essential to obtain accurate information about all the sound sources present. Phased microphone arrays and acoustic imaging methods allow for the estimation of the location and strength of sound sources. Experiments with these devices are one of the main approaches in the current research in aeroacoustics, along with computational simulations or noise prediction models. This thesis presents a detailed literature review on the most common aerospace noise sources, challenges in aeroacoustic measurements, and the acoustic imaging methods typically used to overcome them. Practical recommendations are provided for selecting the appropriate imaging technique depending on the type of experiment. New integration techniques for distributed sound sources, such as leading– or trailing–edge ...

Blind channel identication and equalisation are the processes by which a channel impulse response can be identified and proper equaliser filter coeffcients can be obtained, without knowledge of the transmitted signal. Techniques that exploit cyclostationarity can reveal information about systems which are nonminimum phase, nonminimum phase channels cannot be identied using only second-order statistics (SOS), because these do not contain the necessary phase information. Cyclostationary blind equalisation methods exploit the fact that, sampling the received signal at a rate higher than the transmitted signal symbol rate, the received signal becomes cyclostationary. In general, cyclostationary blind equalisers can identify a channel with less data than higher-order statistics (HOS) methods, and unlike these, noconstraint is imposed on the probability distribution function of the input signal. Nevertheless, cyclostationary methods suffer from some drawbacks, such as the fact that some channels are unidentiable when ...

Modern wireless communication systems utilize complex modulated signals such as OFDM signals to achieve increased data rates and spectral efficiency. These signals are characterized by a high peak-to-average-power ratio (PAPR). Thus, highly linear transmitters are required to provide sufficient transmission signal linearity. Conventional linear PAs, such as Class A or Class AB, produce high efficiency only near or at the peak output power region. As a result, the average efficiency is quite low for high PAPR signals. For non-portable devices such as base stations or mobile devices like mobile phones, low PA efficiency means higher heat dissipation which is often a design criterion. In addition, in mobile devices, a direct consequence of the low PA efficiency is the reduced battery lifetime, especially when the mobile device is required to operate at quite different output power levels. This thesis addresses the ...

Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia encountered in clinical practice, and one of the main causes of ictus and strokes. Despite the advances in the comprehension of its mechanisms, its thorough characterization and the quantification of its effects on the human heart are still an open issue. In particular, the choice of the most appropriate therapy is frequently a hard task. Radiofrequency catheter ablation (CA) is becoming one of the most popular solutions for the treatment of the disease. Yet, very little is known about its impact on heart substrate during AF, thus leading to an inaccurate selection of positive responders to therapy and a low success rate; hence, the need for advanced signal processing tools able to quantify AF impact on heart substrate and assess the effectiveness of the CA therapy in an objective and ...

he main objective of the Magnetospheric Multiscale (MMS) mission is to characterize fine-scale structures in the Earth’s magnetotail and magnetopause. These dynamic structures traverse the MMS spacecraft formation at high speed and generate magnetic field signatures that cross the sensitive frequency bands of both search-coil and fluxgate magnetometers. An improved understanding of these events is only possible by combining data from both instrument types for magnetospheric event analysis. This combination is done using a model-based sensor fusion approach that merges data from both instrument types to a virtual instrument with flat gain curve, linear phase and known timing properties as well as the highest sensitivity and lowest noise floor. The generation of the underlying instrument models requires precise knowledge of the instrument frequency responses and timing. This knowledge was obtained in a dedicated end-to-end measurement campaign using a purpose-built magnetic ...

In this thesis we examine the autonomous oscillator model for synthesis of speech signals. The contributions comprise an analysis of realizations and training methods for the nonlinear function used in the oscillator model, the combination of the oscillator model with inverse filtering, both significantly increasing the number of `successfully' re-synthesized speech signals, and the introduction of a new technique suitable for the re-generation of the noise-like signal component in speech signals. Nonlinear function models are compared in a one-dimensional modeling task regarding their presupposition for adequate re-synthesis of speech signals, in particular considering stability. The considerations also comprise the structure of the nonlinear functions, with the aspect of the possible interpolation between models for different speech sounds. Both regarding stability of the oscillator and the premiss of a nonlinear function structure that may be pre-defined, RBF networks are found a ...

Wireless sensor networks has been one of the major research topics in recent years because of its great potential for a wide range of applications. In some application scenarios, sensor nodes intend to report the sensing data to a far-field destination, which cannot be realized by traditional transmission techniques. Due to the energy limitations and the hardware constraints of sensor nodes, distributed transmit beamforming is considered as an attractive candidate for long-range communications in such scenarios as it can reduce energy requirement of each sen-sor node and extend the communication range. However, unlike conventional beamforming, which is performed by a centralized antenna array, distributed beamforming is performed by a virtual antenna array composed of randomly located sensor nodes, each of which has an independent oscillator. Sensor nodes have to coordinate with each other and adjust their transmitting signals to collaboratively ...

Recent improvements in the development of inertial and visual sensors allow building small, lightweight, and cheap motion capture systems, which are becoming a standard feature of smartphones and personal digital assistants. This dissertation describes developments of new motion sensing strategies using the inertial and inertial-visual sensors. The thesis contributions are presented in two parts. The first part focuses mainly on the use of inertial measurement units. First, the problem of sensor calibration is addressed and a low-cost and accurate method to calibrate the accelerometer cluster of this unit is proposed. The method is based on the maximum likelihood estimation framework, which results in a minimum variance unbiased estimator.Then using the inertial measurement unit, a probabilistic user-independent method is proposed for pedestrian activity classification and gait analysis.The work targets two groups of applications including human activity classificationand joint human activity and ...

In recent years, there has been a proliferation of wireless devices for individual use to the point of being ubiquitous. Recent trends have been incorporating many of these devices (or nodes) together, which acquire signals and work in unison over wireless channels, in order to accomplish a predefined task. This type of cooperative sensing and communication between devices form the basis of a so-called wireless sensor network (WSN). Due to the ever increasing processing power of these nodes, WSNs are being assigned more complicated and computationally demanding tasks. Recent research has started to exploit this increased processing power in order for the WSNs to perform tasks pertaining to audio signal acquisition and processing forming so-called wireless acoustic sensor networks (WASNs). Audio signal processing poses new and unique problems when compared to traditional sensing applications as the signals observed often have ...

In recent years, there has been a proliferation of wireless devices for individual use to the point of being ubiquitous. Recent trends have been incorporating many of these devices (or nodes) together, which acquire signals and work in unison over wireless channels, in order to accomplish a predefined task. This type of cooperative sensing and communication between devices form the basis of a so-called wireless sensor network (WSN). Due to the ever increasing processing power of these nodes, WSNs are being assigned more complicated and computationally demanding tasks. Recent research has started to exploit this increased processing power in order for the WSNs to perform tasks pertaining to audio signal acquisition and processing forming so-called wireless acoustic sensor networks (WASNs). Audio signal processing poses new and unique problems when compared to traditional sensing applications as the signals observed often have ...