Thesis (M. App. Sc.)--Carleton University, 2001. / Includes bibliographical references (p. 117). Also available in electronic format on the Internet.

Thesis (Ph. D.)--University of Texas at Austin, 2007. / Vita. Includes bibliographical references.

Thesis (Ph. D.)--University of Texas at Austin, 2006. / Vita. Includes bibliographical references.

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In the last decade, microwave and millimeter-wave systems have gained importance in civil and security applications. Due to an increasing maturity and availability of circuits and components, these systems are getting more compact while being less expensive. Furthermore, quantitative imaging has been conducted at lower frequencies using computational intensive inverse problem algorithms. Due to the ill-posed character of the inverse problem, these algorithms are, in general, very sensitive to noise: the key to their successful application to experimental data is the precision of the measurement system. Only a few research teams investigate systems for imaging in the W-band. In this manuscript such a system is presented, designed to provide scattered field data to quantitative reconstruction algorithms. This manuscript is divided into six chapters. Chapter 2 describes the theory to compute numerically the scattered fields of known objects. In Chapter 3, the W-band measurement setup in the anechoic chamber is shown. Preliminary measurement results are analyzed. Relying on the measurement results, the error sources are studied and corrected by post-processing. The final results are used for the qualitative reconstruction of all three targets of interest and to image quantitatively the small cylinder. The reconstructed images are compared in detail in Chapter 4. Close range imaging has been investigated using a vector analyzer and a radar system. This is described in Chapter 5, based on a future application, which is the detection of FOD on airport runways. The conclusion is addressed in Chapter 6 and some future investigations are discussed.

Durant la dernière décade, les radars millimétriques en bande W (75 - 110 GHz) pour les applications civiles que ce soit dans le domaine de l'aide à la conduite ou de la sécurité. La maturité de ces systèmes et les exigences accrues en termes d'application, orientent actuellement les recherches vers l'insertion de fonctions permettant l'identification. Ainsi, des systèmes d'imagerie radar ont été développés, notamment à l'aide d'imagerie qualitative (SAR). Les premiers résultats sont très prometteurs, cependant, afin de reconstruire les propriétés électromagnétiques des objets, il faut travailler de manière quantitative. De nombreux travaux ont déjà été conduits en ondes centimétriques, mais aucun système d'imagerie quantitative n'existe, à notre connaissance, en gamme millimétrique. L'objectif du travail présenté dans ce manuscrit est de poser les bases d'un système d'imagerie quantitative en gamme millimétrique et de le comparer à l'imagerie radar de systèmes développés en collaboration avec l'Université d'Ulm (Allemagne). L'ensemble des résultats obtenus valide le processus développé pour d'imagerie quantitative. Les recherches doivent être poursuivies. D'une part le système de mesure doit évoluer vers un vrai système multi-incidences/multivues. D'autre part, le cas 2D-TE doit être implémenté afin de pouvoir traiter un objet 2D quelconque dans n'importe quelle polarisation. Enfin, les mesures à partir de systèmes radar réels doivent être poursuivies, en particulier pour rendre exploitables les mesures des coefficients de transmission. Ces dernières sont indispensables si l'on veut un jour appliquer les algorithmes d'inversion à des mesures issues de systèmes radar. / In the last decade, microwave and millimeter-wave systems have gained importance in civil and security applications. Due to an increasing maturity and availability of circuits and components, these systems are getting more compact while being less expensive. Furthermore, quantitative imaging has been conducted at lower frequencies using computational intensive inverse problem algorithms. Due to the ill-posed character of the inverse problem, these algorithms are, in general, very sensitive to noise: the key to their successful application to experimental data is the precision of the measurement system. Only a few research teams investigate systems for imaging in the W-band. In this manuscript such a system is presented, designed to provide scattered field data to quantitative reconstruction algorithms. This manuscript is divided into six chapters. Chapter 2 describes the theory to compute numerically the scattered fields of known objects. In Chapter 3, the W-band measurement setup in the anechoic chamber is shown. Preliminary measurement results are analyzed. Relying on the measurement results, the error sources are studied and corrected by post-processing. The final results are used for the qualitative reconstruction of all three targets of interest and to image quantitatively the small cylinder. The reconstructed images are compared in detail in Chapter 4. Close range imaging has been investigated using a vector analyzer and a radar system. This is described in Chapter 5, based on a future application, which is the detection of FOD on airport runways. The conclusion is addressed in Chapter 6 and some future investigations are discussed.

Η χρήση επαναληπτικών τεχνικών προσαρμοστικής ισοστάθμισης διαύλου αποτελεί μια σχετικά πρόσφατη και πολλά υποσχόμενη μέθοδο αντιμετώπισης του φαινομένου της διασυμβολικής παρεμβολής που εισάγεται από το κανάλι λόγω του φαινομένου της πολυδιόδευσης. Ο αλγόριθμος που έχει επικρατήσει στις περισσότερες προσαρμοστικές εφαρμογές είναι ο ελαχίστων μέσων τετραγώνων (LMS). Διακρίνεται για την απλότητά του, έχει όμως φτωχές ιδιότητες σύγκλισης. Η μέθοδος των αναδρομικών ελαχίστων τετραγώνων (RLS) είναι επίσης αρκετά διαδεδομένη και κατέχει υπερέχουσες ιδιότητες σύγκλισης. Ωστόσο παρουσιάζει μεγάλη υπολογιστική πολυπλοκότητα και αυξημένες απαιτήσεις σε μνήμη. Στα πλαίσια της εργασίας αυτής εγίνε μια προσπάθεια ανάλυσης των τεχνικών που βασίζονται στη μέθοδο των συζυγών παραγώγων (Conjugate Gradient), χρησιμοποιούνται σε προβλήματα προσαρμοστικού φιλτραρίσματος και πιο ειδικά στο πρόβλημα της προσαρμοστικής ισοστάθμισης διαύλου. Οι τεχνικές αυτές επεξεργάζονται τα δεδομένα και ανά μπλοκ. Είναι ικανές να παρέχουν ιδιότητες σύγκλισης συγκρίσιμες με αυτές της (RLS) μεθόδου, εισάγοντας υπολογιστική πολυπλοκότητα ενδιάμεσων απαιτήσεων μεταξύ των μεθόδων LMS και RLS χωρίς να παρουσιάζουν προβλήματα αριθμητικής ευστάθειας. / The use of iteration methods for adaptive equalization has received considerable attention during the past several decades. The Least Mean Squares (LMS) method, which has found widespread use owing to its simplicity, has poor convergence properties. The Recursive Least Squares (RLS) method possess superior convergence properties, but it is computationally intensive and has high storage requirements for matrix manipulations. In this MSc thesis the technique of conjugate gradients is applied for the adaptive filtering problem. Conjugate gradient algorithms for adaptive filtering applications suitable for efficient implementation has been developed and has been applied for the design of an adaptive transversal equalizer. Low cost block algorithms using the preconditioned conjugate gradient method are also discussed. The algorithms are capable of providing convergence comparable to RLS schemes at a computational complexity between the LMS and the RLS methods and does not suffer from any known instability problems.

Stable and computationally efficient reconstruction methodologies are developed to solve two important medical imaging problems which use near-infrared (NIR) light as the source of interrogation, namely, diffuse optical tomography (DOT) and one of its variations, ultrasound-modulated optical tomography (UMOT). Since in both these imaging modalities the system matrices are ill-conditioned owing to insufficient and noisy data, the emphasis in this work is to develop robust stochastic filtering algorithms which can handle measurement noise and also account for inaccuracies in forward models through an appropriate assignment of a process noise. However, we start with demonstration of speeding of a Gauss-Newton (GN) algorithm for DOT so that a video-rate reconstruction from data recorded on a CCD camera is rendered feasible. Towards this, a computationally efficient linear iterative scheme is proposed to invert the normal equation of a Gauss-Newton scheme in the context of recovery of absorption coefficient distribution from DOT data, which involved the singular value decomposition (SVD) of the Jacobian matrix appearing in the update equation. This has sufficiently speeded up the inversion that a video rate recovery of time evolving absorption coefficient distribution is demonstrated from experimental data. The SVD-based algorithm has made the number of operations in image reconstruction to be rather than. 2()ONN3()ONN The rest of the algorithms are based on different forms of stochastic filtering wherein we arrive at a mean-square estimate of the parameters through computing their joint probability distributions conditioned on the measurement up to the current instant. Under this, the first algorithm developed uses a Bootstrap particle filter which also uses a quasi-Newton direction within. Since keeping track of the Newton direction necessitates repetitive computation of the Jacobian, for all particle locations and for all time steps, to make the recovery computationally feasible, we devised a faster update of the Jacobian. It is demonstrated, through analytical reasoning and numerical simulations, that the proposed scheme, not only accelerates convergence but also yields substantially reduced sample variance in the estimates vis-à-vis the conventional BS filter. Both accelerated convergence and reduced sample variance in the estimates are demonstrated in DOT optical parameter recovery using simulated and experimental data. In the next demonstration a derivative free variant of the pseudo-dynamic ensemble Kalman filter (PD-EnKF) is developed for DOT wherein the size of the unknown parameter is reduced by representing of the inhomogeneities through simple geometrical shapes. Also the optical parameter fields within the inhomogeneities are approximated via an expansion based on the circular harmonics (CH) (Fourier basis functions). The EnKF is then used to recover the coefficients in the expansion with both simulated and experimentally obtained photon fluence data on phantoms with inhomogeneous inclusions. The process and measurement equations in the Pseudo-Dynamic EnKF (PD-EnKF) presently yield a parsimonious representation of the filter variables, which consist of only the Fourier coefficients and the constant scalar parameter value within the inclusion. Using fictitious, low-intensity Wiener noise processes in suitably constructed ‘measurement’ equations, the filter variables are treated as pseudo-stochastic processes so that their recovery within a stochastic filtering framework is made possible. In our numerical simulations we have considered both elliptical inclusions (two inhomogeneities) and those with more complex shapes ( such as an annular ring and a dumbbell) in 2-D objects which are cross-sections of a cylinder with background absorption and (reduced) scattering coefficient chosen as = 0.01 mm-1 and = 1.0 mm-1respectively. We also assume=0.02 mm-1 within the inhomogeneity (for the single inhomogeneity case) and=0.02 and 0.03 mm-1 (for the two inhomogeneities case). The reconstruction results by the PD-EnKF are shown to be consistently superior to those through a deterministic and explicitly regularized Gauss-Newton algorithm. We have also estimated the unknown from experimentally gathered fluence data and verified the reconstruction by matching the experimental data with the computed one. The superiority of a modified version of the PD-EnKF, which uses an ensemble square root filter, is also demonstrated in the context of UMOT by recovering the distribution of mean-squared amplitude of vibration, related to the Young’s modulus, in the ultrasound focal volume. Since the ability of a coherent light probe to pick-up the overall optical path-length change is limited to modulo an optical wavelength, the individual displacements suffered owing to the US forcing should be very small, say within a few angstroms. The sensitivity of modulation depth to changes in these small displacements could be very small, especially when the ROI is far removed from the source and detector. The contrast recovery of the unknown distribution in such cases could be seriously impaired whilst using a quasi-Newton scheme (e.g. the GN scheme) which crucially makes use of the derivative information. The derivative-free gain-based Monte Carlo filter not only remedies this deficiency, but also provides a regularization insensitive and computationally competitive alternative to the GN scheme. The inherent ability of a stochastic filter in accommodating the model error owing to a diffusion approximation of the correlation transport may be cited as an added advantage in the context of the UMOT inverse problem. Finally to speed up forward solve of the partial differential equation (PDE) modeling photon transport in the context of UMOT for which the PDE has time as a parameter, a spectral decomposition of the PDE operator is demonstrated. This allows the computation of the time dependent forward solution in terms of the eigen functions of the PDE operator which has speeded up the forward solution, which in turn has rendered the UMOT parameter recovery computationally efficient.