Antenna Arrays for Multipath and Interference Mitigation in GNSS Receivers

This thesis deals with the synchronization of one or several replicas of a known signal received in a scenario with multipath propagation and directional interference. A connecting theme along this work is the systematic application of the maximum likelihood (ML) principle together with a signal model in which the spatial signatures are unstructured and the noise term is Gaussian- distributed with an unknown correlation matrix. This last assumption is key in obtaining estimators that are capable of mitigating the disturbing signals that exhibit a certain structure, and this is achieved without resorting to the estimation of the parameters of those signals. On the other hand, the assumption of unstructured spatial signatures is interesting from a practical standpoint and facilitates the estimation problem since the estimates of these signatures can be obtained in closed form. This constitutes a first step towards ...

Seco-Granados, Gonzalo — Universitat Politecnica de Catalunya


Direction Finding In The Presence of Array Imperfections, Model Mismatches and Multipath

In direction finding (DF) applications, there are several factors affecting the estimation accuracy of the direction-of-arrivals (DOA) of unknown source locations. The major distortions in the estimation process are due to the array imperfections, model mismatches and multipath. The array imperfections usually exist in practical applications due to the nonidealities in the antenna array such as mutual coupling (MC) and gain/phase uncertainties. The model mismatches usually occur when the model of the received signal differs from the signal model used in the processing stage of the DF system. Another distortion is due to multipath signals. In the multipath scenario, the antenna array receives the transmitted signal from more than one path with different directions and the array covariance matrix is rank-deficient. In this thesis, three new methods are proposed for the problems in DF applications in the presence of array ...

Elbir, Ahmet M. — Middle East Technical Univresity


Sensor Fusion for Automotive Applications

Mapping stationary objects and tracking moving targets are essential for many autonomous functions in vehicles. In order to compute the map and track estimates, sensor measurements from radar, laser and camera are used together with the standard proprioceptive sensors present in a car. By fusing information from different types of sensors, the accuracy and robustness of the estimates can be increased. Different types of maps are discussed and compared in the thesis. In particular, road maps make use of the fact that roads are highly structured, which allows relatively simple and powerful models to be employed. It is shown how the information of the lane markings, obtained by a front looking camera, can be fused with inertial measurement of the vehicle motion and radar measurements of vehicles ahead to compute a more accurate and robust road geometry estimate. Further, it ...

Lundquist, Christian — Linköping University


Bayesian State-Space Modelling of Spatio-Temporal Non-Gaussian Radar Returns

Radar backscatter from an ocean surface is commonly referred to as sea clutter. Any radar backscatter not due to the scattering from an ocean surface constitutes a potential target. This thesis is concerned with the study of target detection techniques in the presence of high resolution sea clutter. In this dissertation, the high resolution sea clutter is treated as a compound process, where a fast oscillating speckle component is modulated in power by a slowly varying modulating component. While the short term temporal correlations of the clutter are associated with the speckle, the spatial correlations are largely associated with the modulating component. Due to the disparate statistical and correlation properties of the two components, a piecemeal approach is adopted throughout this thesis, whereby the spatial and the temporal correlations of high resolution sea clutter are treated independently. As an extension ...

Noga, Jacek Leszek — University of Cambridge


Performance Analysis of Bistatic Radar and Optimization methodology in Multistatic Radar System

This work deals with the problem of calculating the Cramer-Rao lower bounds (CRLBs) for bistatic radar channels. To this purpose we exploited the relation between the Ambiguity Function (AF) and the CRLB. The bistatic CRLBs are analyzed and compared to the monostatic counterparts as a function of the bistatic geometric parameters. In the bistatic case both geometry factors and transmitted waveforms play an important role in the shape of the AF, and therefore in the estimation accuracy of the target range and velocity. In particular, the CRLBs depend on the target direction of arrival, the bistatic baseline length, and the distance between the target and the receiver. The CRLBs are then used to select the optimum bistatic channel (or set of channels) for the tracking of a radar target moving along a trajectory in a multistatic scenario and for design ...

Stinco, Pietro — Universita di Pisa


Signal processing of FMCW Synthetic Aperture Radar data

In the field of airborne earth observation there is special attention to compact, cost effective, high resolution imaging sensors. Such sensors are foreseen to play an important role in small-scale remote sensing applications, such as the monitoring of dikes, watercourses, or highways. Furthermore, such sensors are of military interest; reconnaissance tasks could be performed with small unmanned aerial vehicles (UAVs), reducing in this way the risk for one's own troops. In order to be operated from small, even unmanned, aircrafts, such systems must consume little power and be small enough to fulfill the usually strict payload requirements. Moreover, to be of interest for the civil market, cost effectiveness is mandatory. Frequency Modulated Continuous Wave (FMCW) radar systems are generally compact and relatively cheap to purchase and to exploit. They consume little power and, due to the fact that they are ...

Meta, Adriano — Delft University of Technology


A multimicrophone approach to speech processing in a smart-room environment

Recent advances in computer technology and speech and language processing have made possible that some new ways of person-machine communication and computer assistance to human activities start to appear feasible. Concretely, the interest on the development of new challenging applications in indoor environments equipped with multiple multimodal sensors, also known as smart-rooms, has considerably grown. In general, it is well-known that the quality of speech signals captured by microphones that can be located several meters away from the speakers is severely distorted by acoustic noise and room reverberation. In the context of the development of hands-free speech applications in smart-room environments, the use of obtrusive sensors like close-talking microphones is usually not allowed, and consequently, speech technologies must operate on the basis of distant-talking recordings. In such conditions, speech technologies that usually perform reasonably well in free of noise and ...

Abad, Alberto — Universitat Politecnica de Catalunya


Fundamental Frequency and Direction-of-Arrival Estimation for Multichannel Speech Enhancement

Audio systems receive the speech signals of interest usually in the presence of noise. The noise has profound impacts on the quality and intelligibility of the speech signals, and it is therefore clear that the noisy signals must be cleaned up before being played back, stored, or analyzed. We can estimate the speech signal of interest from the noisy signals using a priori knowledge about it. A human speech signal is broadband and consists of both voiced and unvoiced parts. The voiced part is quasi-periodic with a time-varying fundamental frequency (or pitch as it is commonly referred to). We consider the periodic signals basically as the sum of harmonics. Therefore, we can pass the noisy signals through bandpass filters centered at the frequencies of the harmonics to enhance the signal. In addition, although the frequencies of the harmonics are the ...

Karimian-Azari, Sam — Aalborg Univeristy


Adaptive Edge-Enhanced Correlation Based Robust and Real-Time Visual Tracking Framework and Its Deployment in Machine Vision Systems

An adaptive edge-enhanced correlation based robust and real-time visual tracking framework, and two machine vision systems based on the framework are proposed. The visual tracking algorithm can track any object of interest in a video acquired from a stationary or moving camera. It can handle the real-world problems, such as noise, clutter, occlusion, uneven illumination, varying appearance, orientation, scale, and velocity of the maneuvering object, and object fading and obscuration in low contrast video at various zoom levels. The proposed machine vision systems are an active camera tracking system and a vision based system for a UGV (unmanned ground vehicle) to handle a road intersection. The core of the proposed visual tracking framework is an Edge Enhanced Back-propagation neural-network Controlled Fast Normalized Correlation (EE-BCFNC), which makes the object localization stage efficient and robust to noise, object fading, obscuration, and uneven ...

Ahmed, Javed — Electrical (Telecom.) Engineering Department, National University of Sciences and Technology, Rawalpindi, Pakistan.


Enhancement of Periodic Signals: with Application to Speech Signals

The topic of this thesis is the enhancement of noisy, periodic signals with application to speech signals. Generally speaking, enhancement methods can be divided into signal- and noise-driven methods. In this thesis, we focus on the signal-driven approach by employing relevant signal parameters for the enhancement of periodic signals. The enhancement problem consists of two major subproblems: the estimation of relevant parameters or statistics, and the actual noise reduction of the observed signal. We consider both of these subproblems. First, we consider the problem of estimating signal parameters relevant to the enhancement of periodic signals. The fundamental frequency is one example of such a parameter. Furthermore, in multichannel scenarios, the direction-of-arrival of the periodic sources onto an array of sensors is another parameter of relevance. We propose methods for the estimation of the fundamental frequency that have benefits compared to ...

Jensen, Jesper Rindom — Aalborg University


Array Signal Processing Algorithms for Beamforming and Direction Finding

Array processing is an area of study devoted to processing the signals received from an antenna array and extracting information of interest. It has played an important role in widespread applications like radar, sonar, and wireless communications. Numerous adaptive array processing algorithms have been reported in the literature in the last several decades. These algorithms, in a general view, exhibit a trade-off between performance and required computational complexity. In this thesis, we focus on the development of array processing algorithms in the application of beamforming and direction of arrival (DOA) estimation. In the beamformer design, we employ the constrained minimum variance (CMV) and the constrained constant modulus (CCM) criteria to propose full-rank and reduced-rank adaptive algorithms. Specifically, for the full-rank algorithms, we present two low-complexity adaptive step size mechanisms with the CCM criterion for the step size adaptation of the ...

Lei Wang — University of York


Sinusodial Frequency Estimation with Applications to Ultrasound

This thesis comprises two parts. The first part deals with single carrier and multiple-carrier based frequency estimation. The second part is concerned with the application of ultrasound using the proposed estimators and introduces a novel efficient implementation of a subspace tracking technique. In the first part, the problem of single frequency estimation is initially examined, and a hybrid single tone estimator is proposed, comprising both coarse and refined estimates. The coarse estimate of the unknown frequency is obtained using the unweighted linear prediction method, and is used to remove the frequency dependence of the signal-to-noise ratio (SNR) threshold. The SNR threshold is then further reduced via a combination of using an averaging filter and an outlier removal scheme. Finally, a refined frequency estimate is formed using a weighted phase average technique. The hybrid estimator outperforms other recently developed estimators and ...

Zhang, Zhuo — Cardiff University


Efficient Multipath Mitigation in Navigation Systems

The main objective of the thesis is the development of efficient multipath mitigation techniques for navigation systems. By efficient mitigation we refer to the use of asymptotic efficient estimators, and also to the minimization of their computational burden. In this thesis, the efficient estimators are derived from the Maximum Likelihood Principle in several important scenarios. The computational burden is reduced in two ways. One is through data compression techniques that yield receiver implementations of small complexity and small data sizes. The other consists of the efficient implementation of Newton-type methods for the computation of the Maximum Likelihood estimators. The first part of the thesis is dedicated to present the fundamentals of synchronization in a navigation receiver, and to the state of the art in multipath mitigation. Afterward, several results concerning the interpolation of a band limited signal in a finite ...

Selva, Jesus — Technical University of Catalonia (UPC)


Broadband angle of arrival estimation using polynomial matrix decompositions

This thesis is concerned with the problem of broadband angle of arrival (AoA) estimation for sensor arrays. There is a rich theory of narrowband solutions to the AoA problem, which typically involves the covariance matrix of the received data and matrix factorisations such as the eigenvalue decomposition (EVD) to reach optimality in various senses. For broadband arrays, such as found in sonar, acoustics or other applications where signals do not fulfil the narrowband assumption, working with phase shifts between different signals — as sufficient in the narrowband case — does not suffice and explicit lags need to be taken into account. The required space-time covariance matrix of the data now has a lag dimension, and classical solutions such as those based on the EVD are no longer directly applicable. There are a number of existing broadband AoA techniques, which are ...

Alrmah, Mohamed Abubaker — University of Strathclyde


Selected Topics In Direct Geolocation Of Radio Transmitters & Passive Targets

This dissertation is dedicated to the exploration of various direct positioning algorithms for radio transmitters and passive target geolocation. Contrary to the traditional ``two-step'' approach, the ``direct positioning'' approach states that the radio transmitter's position can be extracted directly from the raw samples of the radio transmitter signals collected by the system sensors, without explicitly going through an estimation of position-related parameters such as time-delay, angular or amplitude information. In this work, the concept of direct positioning is applied to various models and consistently outperforms the traditional two-step position estimators, while tightly attaining the theoretical performance bounds. In the sequel, we explore 3 models for radio transmitters and passive target geolocation. The first model discussed in chapter 3, harnesses the transmit signal diversity of MIMO Radar systems to enhance passive-target position estimation via direct estimation algorithms. The algorithms are developed ...

Bar-Shalom, Ofer — Tel-Aviv University

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