635 research outputs found
Signal direction-of-arrival and amplitude estimation for multiple-row bathymetric sidescan sonars
Submitted in partial fulfillment of the requirements for the degree of Master of Science at the Massachusetts Institute of Technology and the Woods Hole Oceanographic Institution February 1998In practical applications with bathymetric sidescan sonars, the multipath reflections and
other directional interferences are the key limiting factors for a better performance. This
thesis proposes a new scheme to deal with the interferences using a multiple-row bathymetric sidescan sonar. Instead of smoothing the measurements over some time or angle
intervals, which was previously widely investigated, we resolve the multipath interferences from the direct signal. Two approaches on signal direction-of-arrival DOA and
amplitude estimation are developed, the correlated signal direction estimate CSDE for
three-row systems and the ESPRIT-based method. These approaches are compared using
different sonar data models, including a stochastic model from the statistical analysis on
bottom scattering and a coherent model from the analysis on interference field; the simulations show the ESPRIT-based approach is quite robust at the angular separation of 100
between two sources and at the signal-to-noise ratio above 10dB except for highly coherent or temporally correlated signals, for which CSDE works very well. The computer simulation results and the discussions on practical algorithm implementation indicate the
proposed scheme can be applied to a real multiple-row bathymetric sidescan sonar. With
the capability to simultaneously resolve two or more directional signals, the new sonar
model should work better for a wider variety of practical situations in shallow water with
out significant increase of the system cost.Funding supporting my thesis research project was provided by the Office of Naval
Research ONR
Microwave Non‐Destructive Testing of Non‐Dispersive and Dispersive Media Using High‐Resolution Methods
This chapter discusses the principle and application of two model‐based algorithms for processing non‐dispersive and dispersive ground penetrating radar (GPR) data over layered medium under monostatic antenna configuration. Both algorithms have been selected for their super‐time resolution capability and reduced computational burden; they allow GPR to measure a layer thickness smaller than the fraction of the dominant wavelength. For non‐dispersive data, the ESPRIT algorithm is generalized to handle different kinds of data models encountered in experiments and in the literature. For dispersive data, the proposed adaptation of the MPM algorithm allows recovering the full‐time resolution and jointly estimating the time delays and quality factors of a layered medium with reduced bias. Both processing techniques are applied to probe‐layered roadways for NDT&E purposes
Mutual Coupling in Phased Arrays: A Review
The mutual coupling between antenna elements affects the antenna parameters like terminal impedances, reflection coefficients and hence the antenna array performance in terms of radiation characteristics, output signal-to-interference noise ratio (SINR), and radar cross section (RCS). This coupling effect is also known to directly or indirectly influence the steady state and transient response, the resolution capability, interference rejection, and direction-of-arrival (DOA) estimation competence of the array. Researchers have proposed several techniques and designs for optimal performance of phased array in a given signal environment, counteracting the coupling effect. This paper presents a comprehensive review of the methods that model and mitigate the mutual coupling effect for different types of arrays. The parameters that get affected due to the presence of coupling thereby degrading the array performance are discussed. The techniques for optimization of the antenna characteristics in the presence of coupling are also included
Angular dispersion of radio waves in mobile channels
Multi-antenna techniques are an important solution for significantly increasing the bandwidth efficiency of mobile wireless data transmission systems. Effective and reliable design of these multi-antenna systems requires thorough knowledge of radiowave propagation in the urban environment. The aim of the work presented in this thesis is to obtain a better physical understanding of radiowave propagation in mobile radio channels in order to provide a basis for the improvement of radiowave propagation prediction techniques for urban environments using knowledge from 3-D propagation experiments and simulations combined with space-wave modelling. In particular, the work focusses on: the development of an advanced 3-D mobile channel sounding system, obtaining propagation measurement data from mobile radio propagation experiments, the analysis of measured data and the modelling of angular dispersive scattering effects for the improvement of deterministic propagation prediction models. The first part of the study presents the design, implementation and verification of a wideband high-resolution measurement system for the characterisation of angular dispersion in mobile channels. The system uses complex impulse response data obtained from a novel 3-D tilted-cross switched antenna array as input to an improved version of 3-D Unitary ESPRIT. It is capable of characterising the delay and angular properties of physically-nonstationary radio channels at moderate urban speeds with high resolution in both azimuth and elevation. For the first time, omnidirectional video data that were captured during the measurements are used in combination with the measurement results to accurately identify and relate the received radio waves directly to the actual environment while moving through it. The second part of the study presents the results of experiments in which the highresolution measurement system, described in the first part, is used in several mobile outdoor experiments in different scenarios. The objective of these measurements was to gain more knowledge in order to improve the understanding of radiowave propagation. From these results the dispersive effects in the angular domain, caused by rough building surfaces and other irregular structures was paid particular attention. These effects not only influence the total amount of received power in dense urban environments, but can also have a large impact on the performance and deployment of multi-antenna systems. To improve the data representation and support further data analysis a hierarchical clustering method is presented that can successfully identify clusters of multipath signal components in multidimensional data. By using the data obtained from an omnidirectional video camera the clusters can be related directly to the environment and the scattering effects of specific objects can be isolated. These results are important in order to improve and calibrate deterministic propagation models. In the third part of the study a new method is presented to account for the angular dispersion caused by irregular surfaces in ray-tracing based propagation prediction models. The method is based on assigning an effective roughness to specific surfaces. Unlike the conventional reflection reduction factor for Gaussian surfaces, that only reduces the ray power, the new method also distributes power in the angular domain. The results of clustered measurement data are used to calibrated the model and show that this leads to improved channel representations that are better matched to the real-world channel behavior
Estimation of Radio Channel Parameters
Kurzfassung
Diese Dissertation behandelt die Schätzung der Modellparameter einer
Momentanaufnahme des Mobilfunkkanals. Das besondere Augenmerk liegt zum einen
auf der Entwicklung eines generischen Datenmodells für den gemessenen Funkkanal,
welches für die hochauflösende Parameterschätzung geeignet ist. Der zweite
Schwerpunkt dieser Arbeit ist die Entwicklung eines robusten Parameterschätzers
für die Bestimmung der Parameter des entworfenen Modells aus Funkkanalmessdaten.
Entsprechend dieser logischen Abfolge ist auch der Aufbau dieser Arbeit.
Im ersten Teil wird ausgehend von einem aus der Literatur bekannten
strahlenoptischen Modell eine algebraisch handhabbare Darstellung von
beobachteten Wellenausbreitungspfaden entwickelt. Das mathematische Modell
erlaubt die Beschreibung von SISO (single-input-single-output)-
Übertragungssystemen, also von Systemen mit einer Sendeantenne und einer
Empfangsantenne, als auch die Beschreibung von solchen Systemen mit mehreren
Sende- und/oder Empfangsantennen. Diese Systeme werden im Allgemeinen auch als
SIMO- (single-input-multiple-output), MISO- (multiple-input-single-output) oder
MIMO-Systeme (multiple-input-multiple-output) bezeichnet. Im Gegensatz zu
bekannten Konzepten enthält das entwickelte Modell keine Restriktionen bezüglich
der modellierbaren Antennenarrayarchitekturen. Dies ist besonders wichtig in
Hinblick auf die möglichst vollständige Erfassung der räumlichen Struktur des
Funkkanals. Die Flexibilität des Modells ist eine Grundvoraussetzung für die
optimale Anpassung der Antennenstruktur an die Messaufgabe. Eine solche
angepasste Antennenarraystruktur ist zum Beispiel eine zylindrische Anordnung
von Antennenelementen. Sie ist gut geeignet für die Erfassung der räumlichen
Struktur des Funkkanals (Azimut und Elevation) in so genannten Outdoor-
Funkszenarien. Weiterhin wird im ersten Teil eine neue Komponente des
Funkkanaldatenmodells eingeführt, welche den Beitrag verteilter (diffuser)
Streuungen zur Funkübertragung beschreibt. Die neue Modellkomponente spielt eine
Schlüsselrolle bei der Entwicklung eines robusten Parameterschätzers im
Hauptteil dieser Arbeit. Die fehlende Modellierung der verteilten Streuungen ist
eine der Hauptursachen für die begrenzte Anwendbarkeit und die oft kritisierte
fehlende Robustheit von hochauflösenden Funkkanalparameterschätzern, die in der
Literatur etabliert sind. Das neue Datenmodell beschreibt die so genannten
dominanten Ausbreitungspfade durch eine deterministische Abbildung der
Pfadparameter auf den gemessenen Funkkanal. Der Beitrag der verteilten
Streuungen wird mit Hilfe eines zirkularen mittelwertfreien Gaußschen Prozesses
beschrieben. Die Modellparameter der verteilten Streuungen beschreiben dabei die
Kovarianzmatrix dieses Prozesses. Basierend auf dem entwickelten Datenmodell
wird im Anschluss kurz über aktuelle Konzepte für Funkkanalmessgeräte, so
genannte Channel-Sounder, diskutiert.
Im zweiten Teil dieser Arbeit werden in erster Linie Ausdrücke zur Bestimmung
der erzielbaren Messgenauigkeit eines Channel-Sounders abgeleitet. Zu diesem
Zweck wird die untere Schranke für die Varianz der geschätzten Modellparameter,
das heißt der Messwerte, bestimmt. Als Grundlage für die Varianzabschätzung wird
das aus der Parameterschätztheorie bekannte Konzept der Cramér-Rao-Schranke
angewandt. Im Rahmen der Ableitung der Cramér-Rao-Schranke werden außerdem
wichtige Gesichtspunkte für die Entwicklung eines effizienten Parameterschätzers
diskutiert.
Im dritten Teil der Arbeit wird ein Schätzer für die Bestimmung der
Ausbreitungspfadparameter nach dem Maximum-Likelihood-Prinzip entworfen. Nach
einer kurzen Übersicht über existierende Konzepte zur hochauflösenden
Funkkanalparameterschätzung wird die vorliegende Schätzaufgabe analysiert und in
Hinsicht ihres Typs klassifiziert. Unter der Voraussetzung, dass die Parameter
der verteilten Streuungen bekannt sind, lässt sich zeigen, daß sich die
Schätzung der Parameter der Ausbreitungspfade als ein nichtlineares gewichtetes
kleinstes Fehlerquadratproblem auffassen lässt. Basierend auf dieser Erkenntnis
wird ein generischer Algorithmus zur Bestimmung einer globalen Startlösung für
die Parameter eines Ausbreitungspfades vorgeschlagen. Hierbei wird von dem
Konzept der Structure-Least-Squares (SLS)-Probleme Gebrauch gemacht, um die
Komplexität des Schätzproblems zu reduzieren. Im folgenden Teil dieses
Abschnitts wird basierend auf aus der Literatur bekannten robusten numerischen
Algorithmen ein Schätzer zur genauen Bestimmung der Ausbreitungspfadparameter
abgeleitet. Im letzten Teil dieses Abschnitts wird die Anwendung
unterraumbasierter Schätzer zur Bestimmung der Ausbreitungspfadparameter
diskutiert. Es wird ein speichereffizienter Algorithmus zur Signalraumschätzung
entwickelt. Dieser Algorithmus ist eine Grundvoraussetzung für die Anwendung von
mehrdimensionalen Parameterschätzern wie zum Beispiel des R-D unitary ESPRIT
(Estimation of Signal Parameters via Rotational Invariance Techniques) zur
Bestimmung von Funkkanalparametern aus MIMO-Funkkanalmessungen. Traditionelle
Verfahren zur Signalraumschätzung sind hier im Allgemeinen nicht anwendbar, da
sie einen zu großen Speicheraufwand erfordern. Außerdem wird in diesem Teil
gezeigt, dass ESPRIT-Algorithmen auch zur Parameterschätzung von Daten mit so
genannter versteckter Rotations-Invarianzstruktur eingesetzt werden können. Als
Beispiel wird ein ESPRIT-basierter Algorithmus zur Richtungsschätzung in
Verbindung mit multibeam-Antennenarrays (CUBA) abgeleitet.
Im letzten Teil dieser Arbeit wird ein Maximum-Likelihood-Schätzer für die neue
Komponente des Funkkanals, welche die verteilten Streuungen beschreibt,
entworfen. Ausgehend vom Konzept des iterativen Maximum-Likelihood-Schätzers
wird ein Algorithmus entwickelt, der hinreichend geringe numerische Komplexität
besitzt, so dass er praktisch anwendbar ist. In erster Linie wird dabei von der
Toeplitzstruktur der zu schätzenden Kovarianzmatrix Gebrauch gemacht. Aufbauend
auf dem Schätzer für die Parameter der Ausbreitungspfade und dem Schätzer für
die Parameter der verteilten Streuungen wird ein Maximum-Likelihood-Schätzer
entwickelt (RIMAX), der alle Parameter des in Teil I entwickelten Modells der
Funkanalmessung im Verbund schätzt. Neben den geschätzten Parametern des
Datenmodells liefert der Schätzer zusätzlich Zuverlässigkeitsinformationen.
Diese werden unter anderem zur Bestimmung der Modellordnung, das heißt zur
Bestimmung der Anzahl der dominanten Ausbreitungspfade, herangezogen. Außerdem
stellen die Zuverlässigkeitsinformationen aber auch ein wichtiges Schätzergebnis
dar. Die Zuverlässigkeitsinformationen machen die weitere Verarbeitung und
Wertung der Messergebnisse möglich.The theme of this thesis is the estimation of model parameters of a radio channel snapshot. The main focus was the development of a general data model for the measured radio channel, suitable for both high resolution channel parameter estimation on the one hand, and the development of a robust parameter estimator
for the parameters of the designed parametric radio channel model, in line with this logical work flow is this thesis.
In the first part of this work an algebraic representation of observed
propagation paths is developed using a ray-optical model known from literature. The algebraic framework is suitable for the description of SISO (single-input-single-output) radio transmission systems. A SISO system uses one antenna as the transmitter (Tx) and one antenna as the receiver (Rx). The derived expression for the propagation paths is also suitable to describe SIMO (single-input-multiple-output), MISO (multiple-input-single-output), and MIMO (multiple-input-multiple-output) radio channel measurements. In contrast to other models used for high resolution channel parameter estimation the derived model makes no
restriction regarding the structure of the antenna array used throughout the measurement. This is important since the ultimate goal in radio channel sounding is the complete description of the spatial (angular) structure of the radio channel at Tx and Rx. The flexibility of the data model is a prerequisite for the optimisation of the antenna array structure with respect to the measurement
task. Such an optimised antenna structure is a stacked uniform circular beam array, i.e., a cylindrical arrangement of antenna elements. This antenna array configuration is well suited for the measurement of the spatial structure of the radio channel at Tx and/or Rx in outdoor-scenarios. Furthermore, a new component
of the radio channel model is introduced in the first part of this work. It describes the contribution of distributed (diffuse) scattering to the radio transmission. The new component is key for the development of a robust radio channel parameter estimator, which is derived in the main part of this work. The ignorance of the contribution of distributed scattering to radio propagation is one of the main reasons why high-resolution radio channel parameter estimators fail in practice. Since the underlying data model is wrong the estimators produce erroneous results. The improved model describes the so called dominant propagation paths by a deterministic mapping of the propagation path parameters
to the channel observation. The contribution of the distributed scattering is modelled as a zero-mean circular Gaussian process. The parameters of the distributed scattering process determine the structure of the covariance matrix of this process. Based on this data model current concepts for radio channel sounding devices are discussed.
In the second part of this work expressions for the accuracy achievable by a radio channel sounder are derived. To this end the lower bound on the variance of the measurements i.e. the parameter estimates is derived. As a basis for this evaluation the concept of the Cramér-Rao lower bound is employed. On the way to
the Cramér-Rao lower bound for all channel model parameters, important issues for the development of an appropriate parameter estimator are discussed. Among other things the coupling of model parameters is also discussed.
In the third part of this thesis, an estimator, for the propagation path parameters is derived. For the estimator the 'maximum-likelihood' approach is employed. After a short overview of existing high-resolution channel parameter estimators the estimation problem is classified. It is shown, that the estimation of the parameters of the propagation paths can be understood as a
nonlinear weighted least squares problem, provided the parameters of the distributed scattering process are known. Based on this observation a general algorithm for the estimation of raw parameters for the observed propagation paths is developed. The algorithm uses the concept of structured-least-squares (SLS) and compressed maximum likelihood to reduce the numerical complexity of the estimation problem. A robust estimator for the precise estimation of the propagation path parameters is derived. The estimator is based on concepts well known from nonlinear local optimisation theory. In the last part of this chapter the application of subspace based parameter estimation algorithms for path
parameter estimation is discussed. A memory efficient estimator for the signal subspace needed by, e.g., R-D unitary ESPRIT is derived. This algorithm is a prerequisite for the application of signal subspace based algorithms to MIMO-channel sounding measurements. Standard algorithms for signal subspace estimation (economy size SVD, singular value decomposition) are not suitable
since they require an amount of memory which is too large. Furthermore, it is shown that ESPRIT (Estimation of Signal Parameters via Rotational Invariance Techniques) based algorithms can also be employed for parameter estimation from data having hidden rotation invariance structure. As an example an ESPRIT
algorithm for angle estimation using circular uniform beam arrays (circular multi-beam antennas) is derived.
In the final part of this work a maximum likelihood estimator for the new component of the channel model is developed. Starting with the concept of iterative maximum likelihood estimation, an algorithm is developed having a low computational complexity. The low complexity of the algorithm is achieved by exploiting the Toeplitz-structure of the covariance matrix to estimate. Using
the estimator for the (concentrated, dominant, specular-alike) propagation paths and the parametric estimator for the covariance matrix of the process describing the distributed diffuse scattering a joint estimator for all channel parameter is derived (RIMAX). The estimator is a 'maximum likelihood' estimator and uses the genuine SAGE concept to reduce the computational complexity. The estimator provides additional information about the reliability of the estimated channel parameters. This reliability information is used to determine an appropriate model for the observation. Furthermore, the reliability information i.e. the estimate of the covariance matrix of all parameter estimates is also an important parameter estimation result. This information is a prerequisite for further processing and evaluation of the measured channel parameters
OXIDATION OF SILICON - THE VLSI GATE DIELECTRIC
Silicon dominates the semiconductor industry for good reasons. One factor is the stable, easily formed, insulating oxide, which aids high performance and allows practical processing. How well can these virtues survive as new demands are made on integrity, on smallness of feature sizes and other dimensions, and on constraints on processing and manufacturing methods? These demands make it critical to identify, quantify and predict the key controlling growth and defect processes on an atomic scale.The combination of theory and novel experiments (isotope methods, electronic noise, spin resonance, pulsed laser atom probes and other desorption methods, and especially scanning tunnelling or atomic force microscopies) provide tools whose impact on models is just being appreciated. We discuss the current unified model for silicon oxidation, which goes beyond the traditional descriptions of kinetic and ellipsometric data by explicitly addressing the issues raised in isotope experiments. The framework is still the Deal-Grove model, which provides a phenomenology to describe the major regimes of behaviour, and gives a base from which the substantial deviations can be characterized. In this model, growth is limited by diffusion and interfacial reactions operating in series. The deviations from Deal-Grove are most significant for just those first tens of atomic layers of oxide which are critical for the ultra-thin oxide layers now demanded. Several features emerge as important. First is the role of stress and stress relaxation. Second is the nature of the oxide closest to the Si, both its defects and its differences from the amorphous stoichiometric oxide further out, whether in composition, in network topology, or otherwise. Thirdly, we must consider the charge states of both fixed and mobile species. In thin films with very different dielectric constants, image terms can be important; these terms affect interpretation of spectroscopies, the injection of oxidant species and relative defect stabilities. This has added importance now that P-b concentrations have been correlated with interfacial stress. This raises further issues about the perfection of the oxide random network and the incorporation of interstitial species like molecular oxygen.Finally, the roles of contamination, particles, metals, hydrocarbons etc are important, as is interface roughness. These features depend on pre-gate oxide cleaning and define the Si surface that is to be oxidized which may have an influence on the features listed above
Different Approaches of Numerical Analysis of Electromagnetic Phenomena in Shaded Pole Motor with Application of Finite Elements Method
In this paper is used Finite Element Method-FEM
for analysis of electromagnetic quantities of small micro motor –
single phase shaded pole motor-SPSPM. FEM is widely used
numerical method for solving nonlinear partial differential
equations with variable coefficients. For that purpose motor
model is developed with exact geometry and material’s
characteristics. Two different approaches are applied in FEM
analysis of electromagnetic phenomena inside the motor:
magneto-static where all electromagnetic quantities are analysed
in exact moment of time meaning frequency f=0 Hz and timeharmonic
magnetic approach where the magnetic field inside the
machine is time varying, meaning frequency f=50 Hz. Obtained
results are presented and compared with available analytical
result
Propagation parameter estimation in MIMO systems
Multiple antenna techniques are in the heart of modern and next-generation wireless communications systems, such as 3GPP Long-Term Evolution (LTE), IEEE 802.16e (WiMAX), and IMT-Advanced (IMT-A). Such techniques are considered for the high link capacity gains that are achievable from spatial multiplexing, and also for the system capacity, link reliability, and coverage benefits that are possible from spatial diversity, beamforming, and spatial division multiple access techniques. Accurate spatial channel models play a key role on the characterization of the propagation environment and determination of which techniques provide higher gains in a given scenario. Such models are also fundamental tools in network planning, link and system performance studies, and transceiver development.
Realistic channel models are based on measurements. Hence, there is a need for techniques that extract the relevant information from huge amount of data. This may be achieved by estimating model parameters from the data. Most estimation algorithms are based on the assumption that the channel can be modeled as a combination of a finite number of specular, highly-concentrated paths, requiring estimation of a very large number of parameters. In this thesis, estimators are derived for the parameters of the concentrated propagation paths and the diffuse scattering component that are frequently observed in Multiple-Input Multiple-Output (MIMO) channel sounding measurements. Low complexity methods are derived for efficient computation of the estimates. The derived methods are based on a stochastic channel model, leading to a lower-dimensional parameter set that allow a reduction in computational complexity and improved statistical performance compared to methods found in the literature.
Simulation results demonstrate that high quality estimates are obtained. The large sample performance of the estimators are studied by establishing the Cramér-Rao lower bound (CRLB) and comparing it to the variances of the estimates. The simulations show that the variances of the proposed estimation techniques attain the CRLB for relatively small sample size for most parameters, and no bias is observed
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