Analysis and design of antennas and radiometers for radio astronomy applications in microwave, Mm-wave, and THz Bands

Mención Internacional en el título de doctorWe are living in interesting times for astronomy science, since the birth of the radio astronomy field in the 20th century by Karl Jansky, the availability of new and better radio astronomy receivers is in increasing demand to push the human understanding of the universe. In this thesis, various components (antennas, baluns, antenna-arrays, and radiometers) are proposed for radio astronomy receivers. The proposed designs are belonging to three receiver topologies (direct detection, down-conversion, and up-conversion) that operate at different frequency bands from MHz up to a few of THz. Also, to demonstrate that the same proposed design is capable of working efficiently at different operating frequencies, multiple adjusted designs are presented for several practical radio astronomy and space applications. Firstly, a receiver based on the direct detection of the Electromagnetic (EM) radiation through a radio telescope working on cryogenic cooling conditions. In this part, the focus is on designing conical log-spiral antennas and baluns (balanced to unbalanced transformers) to be used as feeds for VLBI Global Observing System (VGOS) ground-based radio telescopes. The feeds cover the Ultrawideband (UWB) from 2 GHz to 14 GHz with Circular Polarization (CP) radiation and stable radiation patterns. After integration of the feeds to the radio telescope, the whole system operates with high aperture efficiency and high System Equivalent Flux Density (SEFD) over the whole required wide range. The fabrication, assembly, and measurements for single-element and four-elements array are provided for achieving the requirements for single CP and dual CP operation. Also, in the same first part, the proposed single-element feed (antenna + balun) is readjusted for being used for CryoRad spaceborne Earth observations. This feed has a single CP over low-frequency UWB from 400MHz to 2 GHz with low weight and physical size compared to standard horn feeds. The second part of the thesis is dedicated to a THz source to be used as a local oscillator for heterodyne radio astronomy THz receivers in which the down-conversion of the THz radiation to a lower frequency occurs. The source is based on an array of self-complementary bow-tie antennas and photomixers that lies on a dielectric lens. The source can be scaled easily to cover different UWB ranges, three ranges are analyzed from 200 GHz to 2 THz, 100 GHz to 1 THz, and 50 GHz to 0.5 THz. Additionally, in this part, a complete study for the effects of metal losses on such THz planar antennas is performed which are not well-investigated in literature yet, the physical explanations behind such effects are also provided. Although these proposed THz sources themselves can work at room temperature, the receiver probably still needs the cooling for the other receiver components (such as the mixer) to work efficiently at such high frequencies. This is the motivation for the third part of this thesis which presents a different type of radio astronomy receiver that is completely able to work without cooling. The third receiver is based on the nonlinear up-converting of the microwave radiation into the optical domain using Whispering Gallery Mode (WGM) resonators which can work at room temperature efficiently. For such advantage and since this concept is naturally narrow-band, it can be a proper candidate for Cosmic Microwave Background (CMB) spectroscopy and space applications. The system design and its performance are analyzed for Ku band at 12 GHz with proposing a novel microwave coupling scheme for enhancing the up-conversion photonic efficiency which is the main limitation for such upconversion systems. Likewise, several high gain 3D-printed Dielectric Resonator Antenna (DRA)s are proposed in both isolated and array configurations to have a direct coupling of the microwave radiation to the proposed scheme. Another practical application for such receiver is presented for CubeSat missions at the mm-wave band (183 GHz) for climate change forecasting. It is clear here that removing the cryogenic cooling conditions decreases satellite weight and cost, which in turn significantly increases its lifetime. Also, it is worth noting that besides the radio astronomy applications, the proposed receivers (and/or their antenna/components) can be used for many other applications. For example, the UWB antennas in the first part can be used as wideband scalable probes for EM compatibility testing or other wireless systems that require single or dual CP such as radar and military applications. This is because the solutions provide constant beam characteristics with good CP polarization purity and stable performance over the operating UWB. In the same way, the proposed THz source in the second part can be used in several THz applications such as very high-speed wireless communications, highresolution imaging for medical and security purposes. This is because of its key benefits as decade bandwidth, compact size, low noise, low power demand, high tunability, and the ability to work at room temperature. For the up-conversion scheme proposed in the third part, due to its high photonic efficiency, low noise level which enables it to work at room temperature, and its scalability from a few GHz up to several THz, it is suitable for low-cost and high sensitivity applications. Specifically, the ones that need to get rid of the hard cryogenic cooling conditions, or at least, relax them and allow the system to work efficiently at higher temperatures. For instance, portable mm-wave and THz systems for quality control, security, and biochemistry. Finally, in this part, the proposed DRA elements and arrays, due to their low cost, high gain, and low losses, can be used for sensing applications and 5G base station antennas.Programa de Doctorado en Multimedia y Comunicaciones por la Universidad Carlos III de Madrid y la Universidad Rey Juan CarlosPresidente: Raed Shubair.- Secretario: Adrián Amor Martín.- Vocal: José Manuel Fernández Gonzále

Enhancement of a Text-Independent Speaker Verification System by using Feature Combination and Parallel-Structure Classifiers

Speaker Verification (SV) systems involve mainly two individual stages: feature extraction and classification. In this paper, we explore these two modules with the aim of improving the performance of a speaker verification system under noisy conditions. On the one hand, the choice of the most appropriate acoustic features is a crucial factor for performing robust speaker verification. The acoustic parameters used in the proposed system are: Mel Frequency Cepstral Coefficients (MFCC), their first and second derivatives (Deltas and Delta- Deltas), Bark Frequency Cepstral Coefficients (BFCC), Perceptual Linear Predictive (PLP), and Relative Spectral Transform - Perceptual Linear Predictive (RASTA-PLP). In this paper, a complete comparison of different combinations of the previous features is discussed. On the other hand, the major weakness of a conventional Support Vector Machine (SVM) classifier is the use of generic traditional kernel functions to compute the distances among data points. However, the kernel function of an SVM has great influence on its performance. In this work, we propose the combination of two SVM-based classifiers with different kernel functions: Linear kernel and Gaussian Radial Basis Function (RBF) kernel with a Logistic Regression (LR) classifier. The combination is carried out by means of a parallel structure approach, in which different voting rules to take the final decision are considered. Results show that significant improvement in the performance of the SV system is achieved by using the combined features with the combined classifiers either with clean speech or in the presence of noise. Finally, to enhance the system more in noisy environments, the inclusion of the multiband noise removal technique as a preprocessing stage is proposed

Detecting Command-Driven Brain Activity in Patients with Disorders of Consciousness Using TR-fNIRS

Vegetative state (VS) is a disorder of consciousness often referred to as “wakefulness without awareness”. Patients in this condition experience normal sleep-wake cycles, but lack all awareness of themselves and their surroundings. Clinically, assessing consciousness relies on behavioural tests to determine a patient’s ability to follow commands. This subjective approach often leads to a high rate of misdiagnosis (~40%) where patients who retain residual awareness are misdiagnosed as being in a VS. Recently, functional neuroimaging techniques such as functional magnetic resonance imaging (fMRI), has allowed researchers to use command-driven brain activity to infer consciousness. Although promising, the cost and accessibility of fMRI hinder its use for frequent examinations. Functional near-infrared spectroscopy (fNIRS) is an emerging optical technology that is a promising alternative to fMRI. The technology is safe, portable and inexpensive allowing for true bedside assessment of brain function. This thesis focuses on using time-resolved (TR) fNIRS, a variant of fNIRS with enhanced sensitivity to the brain, to detect brain function in healthy controls and patients with disorders of consciousness (DOC). Motor imagery (MI) was used to assess command-driven brain activity since this task has been extensively validated with fMRI. The feasibility of TR-fNIRS to detect MI activity was first assessed on healthy controls and fMRI was used for validation. The results revealed excellent agreement between the two techniques with an overall sensitivity of 93% in comparison to fMRI. Following these promising results, TR-fNIRS was used for rudimentary mental communication by using MI as affirmation to questions. Testing this approach on healthy controls revealed an overall accuracy of 76%. More interestingly, the same approach was used to communicate with a locked-in patient under intensive care. The patient had residual eye movement, which provided a unique opportunity to confirm the fNIRS results. The TR-fNIRS results were in full agreement with the eye responses, demonstrating for the first time the ability of fNIRS to communicate with a patient without prior training. Finally, this approach was used to assess awareness in DOC patients, revealing residual brain function in two patients who had also previously shown significant MI activity with fMRI

Forecasting of Cairo Population using ARMA Model

The problem of large population is one of the most important factors influencingthe economy and social advancement of Egypt. Population forecasts, whencarefully and intelligently made, serves a valuable purpose in helping to direct theemployment of labor and capital to places or projects where they are most needed.Firstly, the paper focuses on studying the population of the capital of Egypt (Cairo).By large numbers of sampling to the population data sequence, the increasing trendis found. Then, a time series model is given which can accurately forecast thepopulation of Cairo. Multiple Autoregressive models AR (1), AR (2) are used theforecasting of the population in the next twenty years. The parameters of the modelare calculated using the famous two methods: Yule-Walker and Burg. Before usingthe model to make predictions, the test of model response is verified, and the MSEand MAPE are measured to verify the models. The result is a scary image of thepopulation in this city. Full descriptions for the steps of selecting the suitable modeland comprehensive MATLAB simulation are presented. Secondly, the totalpopulation density of Egypt is analyzing and forecasting with using the measureddata from 1970 to 2013. The same steps of the first part are done with thepopulation density and forecasting of the increasing of the population density ofEgypt in the 20 next years is presented. The main reasons for the populationproblem are discussed and solution of this problem is presente

Direct assessment of extracerebral signal contamination on optical measurements of cerebral blood flow, oxygenation, and metabolism

Significance: Near-infrared spectroscopy (NIRS) combined with diffuse correlation spectroscopy (DCS) provides a noninvasive approach for monitoring cerebral blood flow (CBF), oxygenation, and oxygen metabolism. However, these methods are vulnerable to signal contamination from the scalp. Our work evaluated methods of reducing the impact of this contamination using time-resolved (TR) NIRS and multidistance (MD) DCS. Aim: The magnitude of scalp contamination was evaluated by measuring the flow, oxygenation, and metabolic responses to a global hemodynamic challenge. Contamination was assessed by collecting data with and without impeding scalp blood flow. Approach: Experiments involved healthy participants. A pneumatic tourniquet was used to cause scalp ischemia, as confirmed by contrast-enhanced NIRS, and a computerized gas system to generate a hypercapnic challenge. Results: Comparing responses acquired with and without the tourniquet demonstrated that the TR-NIRS technique could reduce scalp contributions in hemodynamic signals up to 4 times (rSD ¼ 3 cm) and 6 times (rSD ¼ 4 cm). Similarly, blood flow responses from the scalp and brain could be separated by analyzing MD DCS data with a multilayer model. Using these techniques, there was no change in metabolism during hypercapnia, as expected, despite large increases in CBF and oxygenation. Conclusion: NIRS/DCS can accurately monitor CBF and metabolism with the appropriate enhancement to depth sensitivity, highlighting the potential of these techniques for neuromonitoring

Assessing the feasibility of time-resolved fNIRS to detect brain activity during motor imagery

Functional near-infrared spectroscopy (fNIRS) is a non-invasive optical technique for detecting brain activity, which has been previously used during motor and motor executive tasks. There is an increasing interest in using fNIRS as a brain computer interface (BCI) for patients who lack the physical, but not the mental, ability to respond to commands. The goal of this study is to assess the feasibility of time-resolved fNIRS to detect brain activity during motor imagery. Stability tests were conducted to ensure the temporal stability of the signal, and motor imagery data were acquired on healthy subjects. The NIRS probes were placed on the scalp over the premotor cortex (PMC) and supplementary motor area (SMA), as these areas are responsible for motion planning. To confirm the fNIRS results, subjects underwent functional magnetic resonance imaging (fMRI) while performing the same task. Seven subjects have participated to date, and significant activation in the SMA and/or the PMC during motor imagery was detected by both fMRI and fNIRS in 4 of the 7 subjects. No activation was detected by either technique in the remaining three participants, which was not unexpected due to the nature of the task. The agreement between the two imaging modalities highlights the potential of fNIRS as a BCI, which could be adapted for bedside studies of patients with disorders of consciousness

Using fMRI to investigate the potential cause of inverse oxygenation reported in fNIRS studies of motor imagery

© 2019 Elsevier B.V. Motor imagery (MI) is a commonly used cognitive task in brain–computer interface (BCI) applications because it produces reliable activity in motor-planning regions. However, a number of functional near-infrared spectroscopy (fNIRS) studies have reported the unexpected finding of inverse oxygenation: increased deoxyhemoglobin and decreased oxyhemoglobin during task periods. This finding questions the reliability of fNIRS for BCI applications given that MI activation should result in a focal increase in blood oxygenation. In an attempt to elucidate this phenomenon, fMRI and fNIRS data were acquired on 15 healthy participants performing a MI task. The fMRI data provided global coverage of brain activity, thus allowing visualization of all potential brain regions activated and deactivated during task periods. Indeed, fMRI results from seven subjects included activation in the primary motor cortex and/or the pre-supplementary motor area during the rest periods in addition to the expected activation in the supplementary motor and premotor areas. Of these seven subjects, two showed inverse oxygenation with fNIRS. The proximity of the regions showing inverse oxygenation to the motor planning regions suggests that inverse activation detected by fNIRS may likely be a consequence of partial volume errors due to the sensitivity of the optodes to both primary motor and motor planning regions

A miniaturized triple-band and dual-polarized monopole antenna based on a CSRR perturbed ground plane

This paper proposes a new triple-band monopole antenna based on Complementary Split Ring Resonators (CSRR) perturbing the ground plane (GND). The antenna consists of an inverted-L-shaped monopole fed by a modified microstrip line with two CSRRs cut out of the ground plane. The operational bands are independently controlled by the CSRR unit cell parameters. In addition, the antenna presents a dual-polarization performance (vertical polarization at 2.4 GHz band and horizontal polarization at both 3.6 and 5.9 GHz bands). The designed antenna is fully planar and low profile avoiding the vias with the ground plane and covering the WLAN, WiMAX, and IEEE 801.11p bands at 2.45, 3.6, and 5.8 GHz. A compact prototype ( 0.32λ0×0.32λ0 being λ0 is the wavelength corresponding to the lowest resonance frequency) has been fabricated and measured showing good agreement between simulations and measurements. The measured impedance bandwidths are 10% (2.38-2.63 GHz), 2.5% (3.54-3.63 GHz), and 20% (5.83-7.12 GHz) whereas the measured gains are 1.34, 0.68, and 2.65 dBi at 2.4, 3.6, and 5.9 GHz respectively.This work was supported by PID2019-109984RB-C41

Can time-resolved NIRS provide the sensitivity to detect brain activity during motor imagery consistently?

Previous functional magnetic resonance imaging (fMRI) studies have shown that a subgroup of patients diagnosed as being in a vegetative state are aware and able to communicate by performing a motor imagery task in response to commands. Due to the fMRI\u27s cost and accessibility, there is a need for exploring different imaging modalities that can be used at the bedside. A promising technique is functional near infrared spectroscopy (fNIRS) that has been successfully applied to measure brain oxygenation in humans. Due to the limited depth sensitivity of continuous-wave NIRS, time-resolved (TR) detection has been proposed as a way of enhancing the sensitivity to the brain, since late arriving photons have a higher probability of reaching the brain. The goal of this study was to assess the feasibility and sensitivity of TR fNIRS in detecting brain activity during motor imagery. Fifteen healthy subjects were recruited in this study, and the fNIRS results were validated using fMRI. The change in the statistical moments of the distribution of times of flight (number of photons, mean time of flight and variance) were calculated for each channel to determine the presence of brain activity. The results indicate up to an 86% agreement between fMRI and TR-fNIRS and the sensitivity ranging from 64 to 93% with the highest value determined for the mean time of flight. These promising results highlight the potential of TR-fNIRS as a portable brain computer interface for patients with disorder of consciousness

Incorporating early and late-arriving photons to improve the reconstruction of cerebral hemodynamic responses acquired by time-resolved near-infrared spectroscopy

Significance: Despite its advantages in terms of safety, low cost, and portability, functional near-infrared spectroscopy applications can be challenging due to substantial signal contamination from hemodynamics in the extracerebral layer (ECL). Time-resolved near-infrared spectroscopy (tr NIRS) can improve sensitivity to brain activity but contamination from the ECL remains an issue. This study demonstrates how brain signal isolation can be further improved by applying regression analysis to tr data acquired at a single source-detector distance. Aim: To investigate if regression analysis can be applied to single-channel trNIRS data to further isolate the brain and reduce signal contamination from the ECL. Approach: Appropriate regressors for trNIRS were selected based on simulations, and performance was evaluated by applying the regression technique to oxygenation responses recording during hypercapnia and functional activation. Results: Compared to current methods of enhancing depth sensitivity for trNIRS (i.e., higher statistical moments and late gates), incorporating regression analysis using a signal sensitive to the ECL significantly improved the extraction of cerebral oxygenation signals. In addition, this study demonstrated that regression could be applied to trNIRS data from a single detector using the early arriving photons to capture hemodynamic changes in the ECL. Conclusion: Applying regression analysis to trNIRS metrics with different depth sensitivities improves the characterization of cerebral oxygenation signals