A direction of arrival (DoA) estimation technique for broadband microwave signals is proposed using a single ultrawideband antenna. It is inspired by the sound source localization ability of a human auditory system using just one ear (monaural localization). By exploiting the incident angle-dependent frequency response of a wideband antenna, the DoA of a broadband microwave signal can be estimated. The DoA estimation accuracies are evaluated for two antenna configurations and microwave signals with different signal-to-noise ratios. Encouraging the DoA estimation performance of the proposed technique is demonstrated in both simulation and experiment.

Signal acquisition, signal reconstruction and analysis of spectrum of the signal are the three most important steps in signal processing and they are found in almost all of the modern day hardware. In most of the signal processing hardware, the signal of interest is sampled at uniform intervals satisfying some conditions like Nyquist rate. However, in some cases the privilege of having uniformly sampled data is lost due to some constraints on the hardware resources. In this thesis an important problem of signal reconstruction and spectral analysis from nonuniformly sampled data is addressed and a variety of methods are presented. The proposed methods are tested via numerical experiments on both artificial and real-life data sets. The thesis starts with a brief review of methods available in the literature for signal reconstruction and spectral analysis from non uniformly sampled data. The methods discussed in the thesis are classified into two broad categories - dense and sparse methods, the classification is based on the kind of spectra for which they are applicable. Under dense spectral methods the main contribution of the thesis is a non-parametric approach named LIMES, which recovers the smooth spectrum from non uniformly sampled data. Apart from recovering the spectrum, LIMES also gives an estimate of the covariance matrix. Under sparse methods the two main contributions are methods named SPICE and LIKES - both of them are user parameter free sparse estimation methods applicable for line spectral estimation. The other important contributions are extensions of SPICE and LIKES to multivariate time series and array processing models, and a solution to the grid selection problem in sparse estimation of spectral-line parameters. The third and final part of the thesis contains applications of the methods discussed in the thesis to the problem of radial velocity data analysis for exoplanet detection. Apart from the exoplanet application, an application based on Sudoku, which is related to sparse parameter estimation, is also discussed.

Un radar MIMO (Multiple Input Multiple Output) est un système radar qui utilise plusieurs antennes émettrices et réceptrices, dans lequel les formes d'ondes émises peuvent être indépendantes. Par rapport aux radars utilisant des antennes en réseaux phasés, les radars MIMO offrent davantage de degrés de liberté, ce qui permet d'améliorer les performances du système en termes de détection et localisation. La technique MIMO offre également la possibilité de synthétiser un diagramme de rayonnement désiré par une définition judicieuse des formes d'ondes émises. Dans la mesure où les paramètres des cibles (positions, vitesses, directions d'arrivée (DOA), ...) sont estimés à partir des échos des signaux émis, on comprend aisément que les formes d'ondes employées jouent un rôle clé dans les performances du système. Cette thèse porte sur l'estimation de DOA et sur la conception des formes d'ondes pour un radar MIMO. Le cadre d'étude est restreint au cas où les antennes sont colocalisées et les cibles sont immobiles et supposées ponctuelles. La plupart des travaux antérieurs (au commencement de la thèse) portaient sur le radar MIMO bande étroite et faisaient l'hypothèse d'émetteurs-récepteurs idéaux et indépendants. Cette thèse contribue à élargir le cadre d'étude en s'intéressant d'une part au passage en large bande et d'autre part à la modélisation et à la prise en compte de la non-indépendance des émetteurs-récepteurs et autres imperfections. Dans la mesure où le recours à des signaux large bande est nécessaire lorsqu'une résolution importante est souhaitée, nous nous sommes attachés dans cette thèse à adapter le modèle d'un système de radar MIMO au cas large bande et à proposer de nouvelles techniques visant à améliorer les performances d'estimation de DOA dans le cas de signaux large bande. Cette thèse analyse également l'influence de conditions non idéales comme l'impact des phénomènes de couplage électromagnétique sur les diagrammes de rayonnement dans un réseau d'antennes. Cette étude est menée dans le cas bande étroite. En particulier, nous étudions l'influence du couplage direct entre les réseaux d'antennes d'émission et de réception (appelé « crosstalk ») sur les performances des techniques proposées. Nous établissons un modèle du signal permettant de prendre en compte ce phénomène et proposons une technique de réduction du « crosstalk » qui permet une estimation efficace des DOA des cibles. Nous montrons par ailleurs comment améliorer les performances d'estimation de DOA en présence de diagrammes de rayonnement incluant le couplage entre antennes. Le dernier apport principal de cette thèse est la conception et réalisation d'une plateforme expérimentale comportant une seule architecture d'émetteur-récepteur, qui permet de simuler un système MIMO utilisant des antennes colocalisées en appliquant le principe de superposition. Cette plateforme nous a permis d'évaluer les performances des techniques proposées dans des conditions plus réalistes / A Multiple-Input Multiple-Output (MIMO) radar is a system employing multiple transmitters and receivers in which the waveforms to be transmitted can be totally independent. Compared to standard phased-array radar systems, MIMO radars offer more degrees of freedom which leads to improved angular resolution and parameter identifiability, and provides more flexibility for transmit beampattern design. The main issues of interest in the context of MIMO radar are the estimation of several target parameters (which include range, Doppler, and Direction-of-Arrival (DOA), among others). Since the information on the targets is obtained from the echoes of the transmitted signals, it is straightforward that the design of the waveforms plays an important role in the system accuracy. This document addresses the investigation of DOA estimation of non-moving targets and waveform design techniques for MIMO radar with colocated antennas. Although narrowband MIMO radars have been deeply studied in the literature, the existing DOA estimation techniques have been usually proposed and analyzed from a theoretical point of view, often assuming ideal conditions. This thesis analyzes existing signal processing algorithms and proposes new ones in order to improve the DOA estimation performance in the case of narrowband and wideband signals. The proposed techniques are studied under ideal and non-ideal conditions considering punctual targets. Additionally, we study the influence of mutual coupling on the performance of the proposed techniques and we establish a more realistic signal model which takes this phenomenon into account. We then show how to improve the DOA estimation performance in the presence of distorted radiation patterns and we propose a crosstalk reduction technique, which makes possible an efficient estimation of the target DOAs. Finally, we present an experimental platform for MIMO radar with colocated antennas which has been developed in order to evaluate the performance of the proposed techniques under more realistic conditions. The proposed platform, which employs only one transmitter and one receiver architectures, relies on the superposition principle to simulate a real MIMO system

Abstract The focus of this thesis is to study direction of arrival (DoA) estimation algorithms for reconfigurable leaky-wave antennas and advanced antenna arrays. Directional antennas can greatly improve the spectrum reuse, interference avoidance, and object and people localization. DoA estimation algorithms have also been shown to be useful for applications such as positioning for user tracking and location-based services in wireless local area networks (WLANs). The main goal is to develop novel DoA estimation algorithms for both advanced antenna arrays and composite right/left-handed (CRLH) leaky-wave antennas (LWAs). The thesis introduces novel modifications to existing DoA estimation algorithms and shows how these can be modified for real-time DoA estimation using both antenna types. Three modified DoA estimation algorithms for CRLH-LWAs are presented: 1) modified multiple signal classification (MUSIC), 2) power pattern cross-correlation (PPCC), and 3) adjacent power pattern ratio (APPR). Additionally, the APPR algorithm is also applied to advanced antenna arrays. The thesis also presents improvements to the modified MUSIC and APPR algorithms. The complexity of the algorithms is reduced by selecting a smaller number of received signals from different directions. The results show that the selection of the radiation patterns is very important and that the proposed algorithms can successfully estimate the DoA, even in a real-world environment. Based on the results, this thesis provides a good starting point for future research of DoA estimation algorithms to enhance the performance of future-generation wireless networks and the accuracy of localization. / Tiivistelmä Tässä väitöskirjassa tutkitaan suunnanestimointialgoritmeja uudelleen konfiguroituville vuotoaaltoantenneille (LWA, leaky wave antenna) ja kehittyneille antenniryhmille. Suuntaavilla antenneilla voidaan parantaa huomattavasti spektrin uudelleen käyttöä ja esineiden ja ihmisten sijaintipaikannusta sekä pienentää häiriöitä. Suunnanestimointialgoritmit ovat myös osoittautuneet hyödylliseksi esimerkiksi seuranta- ja sijaintipaikannuspalvelusovelluksille langattomissa lähiverkoissa. Työn päätavoite on kehittää uusia suunnanestimointialgoritmeja sekä kehittyneille antenniryhmille että vuotoaaltoantenneille (composite right/left-handed (CRLH) LWA). Työssä osoitetaan, miten olemassa olevia suunnanestimointialgoritmeja voidaan muokata uudella tavalla, jotta ne soveltuisivat molemmille antennityypeille reaaliaikaiseen suunnanestimointiin. Vuotoaaltoantennille on kehitetty kolme erilaista suunnanestimointialgoritmia: 1) muunneltu MUSIC- (multiple signal classification), 2) säteilykyvioiden tehojen ristikorrelaatio- (PPCC, power pattern cross correlation) ja 3) vierekkäisten säteilykuvioiden tehosuhdealgoritmi (APPR, adjacent power pattern ratio). APPR-algoritmia on myös käytetty kehittyneelle antenniryhmälle. Työssä esitetään myös parannuksia muunnelluille MUSIC- ja APPR-algoritmeille. Algoritmien kompleksisuutta voidaan pienentää valitsemalla vähemmän vastaanotettuja signaaleja. Tulokset osoittavat, että signaalien valinta on hyvin tärkeää ja ehdotetut algoritmit estimoivat onnistuneesti saapuvan signaalin suunnan todellisessa mittausympäristössä. Yhteenvetona voidaan sanoa, että tämä väitöstyö on hyvä lähtökohta suunnanestimointialgoritmitutkimukselle, jonka tavoitteena on parantaa tulevien sukupolvien langattomien verkkojen suorituskykyä ja paikannuksen tarkkuutta.

In this dissertation, sparse processing of signals for directions-of-arrival (DoAs) estimation is addressed in the framework of Compressive Sensing (CS). In particular, DoAs estimation problem for different types of sources, systems, and applications are formulated in the CS paradigm. In addition, the fundamental conditions related to the ``Sparsity'' and ``Linearity'' are carefully exploited in order to apply confidently the CS-based methodologies. Moreover, innovative strategies for various systems and applications are developed, validated numerically, and analyzed extensively for different scenarios including signal to noise ratio (SNR), mutual coupling, and polarization loss. The more realistic data from electromagnetic (EM) simulators are often considered for various analysis to validate the potentialities of the proposed approaches. The performances of the proposed estimators are analyzed in terms of standard root-mean-square error (RMSE) with respect to different degrees-of-freedom (DoFs) of DoAs estimation problem including number of elements, number of signals, and signal properties. The outcomes reported in this thesis suggest that the proposed estimators are computationally efficient (i.e., appropriate for real time estimations), robust (i.e., appropriate for different heterogeneous scenarios), and versatile (i.e., easily adaptable for different systems).