State of the art direction finding (DF) systems usually have several antennas in order to increase accuracy and robustness to certain factors. In this thesis, a three antenna DF system is built and evaluated. While more antennas give better DF performance, a three antenna system is useful for system simplicity and many of the problems in DF systems can be observed and evaluated easily. This system can be used for both azimuth and elevation direction of arrival (DOA) estimation. The system is composed of three monopole antennas, an RF front end, A/D converters and digital signal processing (DSP) units. A number of algorithms are considered, such as, three channel interferometer, correlative interferometer, LSE (least square error) based correlative interferometer and MUSIC (multiple signal classification) algorithms. Different problems in DF systems are investigated. These are gain/phase mismatch of the receiver channels, mutual coupling between antennas, multipath signals and multiple sources. The advantages and disadvantages of different algorithms are outlined.

There are plenty of things said about the financial industry, an always ongoing debate, to say the least. We have identified a complex situation with three dimensions: Initial public offerings, Venture capital, and Lockup agreements. IPOs are generally difficult to put a price on because the market is not united yet, which creates uncertainties. Venture capital firms invest into startups, often with the incentive of bringing them to an IPO and then make a fast cash out exit. Lockup agreements are contracts that prevent insiders from dumping their shares during a set period in the beginning of the IPO. Additionally, based on the market efficiency theory, a market should always be efficient. But does it play out when these characteristics are affecting each other? The purpose of this research was to investigate whether there are abnormal returns in the financial performance for publicly listed companies on the London Stock Exchange at the end of their lockup period. We sorted on venture capital backed companies and sought to explore differences between VC backed, Non-VC backed firms, and the entire market. The research question for this study is: ‘Does The theoretical aspects of this research’s ontological and epistemological views were set in positivism and objectivism with a deductive approach. The financial performance was key in this research, and it was essential to get ample and appropriate data, therefore a quantitative research method was used with an archival research strategy and explanatory research design. We explored a big research gap in this area after the financial crisis 2008, which made us look at IPOs from 2009 to 2012 with an event window as our time horizon. To answer the research question and fulfill our purpose, four hypotheses were developed with focus on VC backed firms, Non-VC backed firms, the entire market, and one shorter event window. Our results prove that the market efficiency theory does not hold. To answer the research question, we found negative abnormal returns after the lockup expiration date for both Non- VC backed firms and the entire market. However, we were unable to provide a statistically significant result for VC backed firms. There was an extra clear trend during the middle 20 days, and we suggest and encourage to further research with a longer time horizon than [- 20, +20] days.

A software GPS receiver is a functional GPS receiver in software. It has several advantages compared to its hardware counterparts. For instance, improvements in receiver architecture as well as GPS system structure can be easily adapted to it. Furthermore, interaction between nearby sensors can be coordinated easily. In this thesis, a SGR (software GPS receiver) is presented from a practical point of view. Major components of the SGR are implemented in Matlab environment. Furthermore, some alternative algorithms are implemented. SGR implementation is considered in two main sections namely a signal processing section and a navigation section. Signal processing section is driven by the raw GPS signal samples obtained from a GPS front-end of NordNavTM R-25 instrument. The conventional and the block adjustment of synchronizing signal (BAAS) processing methods are implemented and their performances are compared in terms of their speed and outputs. Signal processing section outputs raw GPS measurements and navigation data bits. Since the output data length is insufficient in our case, navigation section input is fed from AshtechTM GPS receiver for a moving platform and TrimbleTM GPS Receiver for a stationary platform. Satellite position computation, pseudorange corrections, Kalman filter and LSE (least squares estimation) are implemented in the navigation section. Kalman filter and LSE methods are compared in terms of positioning accuracy for a moving as well as a stationary platform. Results are compared with the commercial GPS outputs. This comparison shows that the software navigation section is equivalent to the commercial GPS in terms of positioning accuracy.

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Dans cette thèse nous élargissons le champ d'application des modèles ARMA (AutoRegressive Moving-Average) vectoriels en considérant des termes d'erreur non corrélés mais qui peuvent contenir des dépendances non linéaires. Ces modèles sont appelés des ARMA faibles vectoriels et permettent de traiter des processus qui peuvent avoir des dynamiques non linéaires très générales. Par opposition, nous appelons ARMA forts les modèles utilisés habituellement dans la littérature dans lesquels le terme d'erreur est supposé être un bruit iid. Les modèles ARMA faibles étant en particulier denses dans l'ensemble des processus stationnaires réguliers, ils sont bien plus généraux que les modèles ARMA forts. Le problème qui nous préoccupera sera l'analyse statistique des modèles ARMA faibles vectoriels. Plus précisément, nous étudions les problèmes d'estimation et de validation. Dans un premier temps, nous étudions les propriétés asymptotiques de l'estimateur du quasi-maximum de vraisemblance et de l'estimateur des moindres carrés. La matrice de variance asymptotique de ces estimateurs est d'une forme "sandwich", et peut être très différente de la variance asymptotique obtenue dans le cas fort. Ensuite, nous accordons une attention particulière aux problèmes de validation. Dans un premier temps, en proposant des versions modifiées des tests de Wald, du multiplicateur de Lagrange et du rapport de vraisemblance pour tester des restrictions linéaires sur les paramètres de modèles ARMA faibles vectoriels. En second, nous nous intéressons aux tests fondés sur les résidus, qui ont pour objet de vérifier que les résidus des modèles estimés sont bien des estimations de bruits blancs. Plus particulièrement, nous nous intéressons aux tests portmanteau, aussi appelés tests d'autocorrélation. Nous montrons que la distribution asymptotique des autocorrelations résiduelles est normalement distribuée avec une matrice de covariance différente du cas fort (c'est-à-dire sous les hypothèses iid sur le bruit). Nous en déduisons le comportement asymptotique des statistiques portmanteau. Dans le cadre standard d'un ARMA fort, il est connu que la distribution asymptotique des tests portmanteau est correctement approximée par un chi-deux. Dans le cas général, nous montrons que cette distribution asymptotique est celle d'une somme pondérée de chi-deux. Cette distribution peut être très différente de l'approximation chi-deux usuelle du cas fort. Nous proposons donc des tests portmanteau modifiés pour tester l'adéquation de modèles ARMA faibles vectoriels. Enfin, nous nous sommes intéressés aux choix des modèles ARMA faibles vectoriels fondé sur la minimisation d'un critère d'information, notamment celui introduit par Akaike (AIC). Avec ce critère, on tente de donner une approximation de la distance (souvent appelée information de Kullback-Leibler) entre la vraie loi des observations (inconnue) et la loi du modèle estimé. Nous verrons que le critère corrigé (AICc) dans le cadre des modèles ARMA faibles vectoriels peut, là aussi, être très différent du cas fort.