## Signal processing of FMCW Synthetic Aperture Radar data (2006)

Analysis, Modelling, and Simulation of an Integrated Multisensor System for Maritime Border Control

In this dissertation a notional multi-sensor system acting in a maritime border control scenario for Homeland Security (HS) is analyzed, modelled, and simulated. The functions performed by the system are the detection, tracking, identification and classification of naval targets that enter a sea region, the evaluation of their threat level and the selection of a suitable reaction to them. The emulated system is composed of two platforms carrying multiple sensors: a land based platform, located on the coast, and an air platform, moving on an elliptic trajectory in front of the coast. The land based platform is equipped with a Vessel Traffic Service (VTS) radar, an infrared camera (IR) and a station belonging to an Automatic Identification System (AIS). The air platform carries an Airborne Early Warning Radar (AEWR) that can operate on a spotlight Synthetic Aperture Radar (SAR) mode, ...

Giompapa, Sofia — Universita di Pisa

Joint Sparsity-Driven Inversion and Model Error Correction for SAR Imaging

Image formation algorithms in a variety of applications have explicit or implicit dependence on a mathematical model of the observation process. Inaccuracies in the observation model may cause various degradations and artifacts in the reconstructed images. The application of interest in this thesis is synthetic aperture radar (SAR) imaging, which particularly suffers from motion-induced model errors. These types of errors result in phase errors in SAR data which cause defocusing of the reconstructed images. Particularly focusing on imaging of fields that admit a sparse representation, we propose a sparsity-driven method for joint SAR imaging and phase error correction. In this technique, phase error correction is performed during the image formation process. The problem is set up as an optimization problem in a nonquadratic regularization-based framework. The method involves an iterative algorithm each iteration of which consists of consecutive steps of ...

Önhon, N. Özben — Faculty of Engineering and Natural Sciences, Sabancı University

Broadband adaptive beamforming with low complexity and frequency invariant response

This thesis proposes different methods to reduce the computational complexity as well as increasing the adaptation rate of adaptive broadband beamformers. This is performed exemplarily for the generalised sidelobe canceller (GSC) structure. The GSC is an alternative implementation of the linearly constrained minimum variance beamformer, which can utilise well-known adaptive filtering algorithms, such as the least mean square (LMS) or the recursive least squares (RLS) to perform unconstrained adaptive optimisation. A direct DFT implementation, by which broadband signals are decomposed into frequency bins and processed by independent narrowband beamforming algorithms, is thought to be computationally optimum. However, this setup fail to converge to the time domain minimum mean square error (MMSE) if signal components are not aligned to frequency bins, resulting in a large worst case error. To mitigate this problem of the so-called independent frequency bin (IFB) processor, overlap-save ...

Koh, Choo Leng — University of Southampton

Multichannel SAR Interferometry based on Statistical Signal Processing

Interferometric SAR systems allow to reconstruct height profile of earth surfaces. The height reconstruction is based on phase unwrapping operation, which is an ill-posed problem since it admits infinite number of solutions. The phase unwrapping problem can be solved using the multichannel InSAR approach, based on the combination of different images of the scene obtained by slightly different positions. An effective way to combine the different interferograms is using statistical estimation theory. In particular the Maximum Likelihood and Maximum a Posteriori multichannel approach have proved to be effective and to be able to restore the uniqueness of the solution. In this thesis the statistical multichannel phase unwrapping is deeply analyzed. In particular, instruments and methods to use InSAR multichannel configuration on real data and in urban areas are provided. Moreover, a new fast and efficient multichannel phase unwrapping algorithm is ...

Ferraioli, Giampaolo — Universita di Napoli Parthenope

Ultra Wideband Communications: from Analog to Digital

The aim of this thesis is to investigate key issues encountered in the design of transmission schemes and receiving techniques for Ultra Wideband (UWB) communication systems. Based on different data rate applications, this work is divided into two parts, where energy efficient and robust physical layer solutions are proposed, respectively. Due to a huge bandwidth of UWB signals, a considerable amount of multipath arrivals with various path gains is resolvable at the receiver. For low data rate impulse radio UWB systems, suboptimal non-coherent detection is a simple way to effectively capture the multipath energy. Feasible techniques that increase the power efficiency and the interference robustness of non-coherent detection need to be investigated. For high data rate direct sequence UWB systems, a large number of multipath arrivals results in severe inter-/intra-symbol interference. Additionally, the system performance may also be deteriorated by ...

Song, Nuan — Ilmenau University of Technology

Theoretical aspects and real issues in an integrated multiradar system

In the last few years Homeland Security (HS) has gained a considerable interest in the research community. From a scientific point of view, it is a difficult task to provide a definition of this research area and to exactly draw up its boundaries. In fact, when we talk about the security and the surveillance, several problems and aspects must be considered. In particular, the following factors play a crucial role and define the complexity level of the considered application field: the number of potential threats can be high and uncertain; the threat detection and identification can be made more complicated by the use of camouflaging techniques; the monitored area is typically wide and it requires a large and heterogeneous sensor network; the surveillance operation is strongly related to the operational scenario, so that it is not possible to define a ...

Fortunati Stefano — University of Pisa

Tracking and Planning for Surveillance Applications

Vision and infrared sensors are very common in surveillance and security applications, and there are numerous examples where a critical infrastructure, e.g. a harbor, an airport, or a military camp, is monitored by video surveillance systems. There is a need for automatic processing of sensor data and intelligent control of the sensor in order to obtain efficient and high performance solutions that can support a human operator. This thesis considers two subparts of the complex sensor fusion system; namely target tracking and sensor control.The multiple target tracking problem using particle filtering is studied. In particular, applications where road constrained targets are tracked with an airborne video or infrared camera are considered. By utilizing the information about the road network map it is possible to enhance the target tracking and prediction performance. A dynamic model suitable for on-road target tracking with ...

Skoglar, Per — Linköping University, Department of Electrical Engineering

An ever-increasing demand for higher mobility, capacity and reliability, together with a definitive compromise with sustainability, are the hallmarks of mobile and wireless communications systems nowadays. Under these premises, smart antenna devices -capable of sensing the electromagnetic environment and suitably adapting its radiation features- are correspondingly called to play a crucial role. In this sense, today's wireless standards consider multiple-antenna techniques in order to exploit space diversity, spatial multiplexing and beamforming to achieve better levels of reliability and capacity. Such advantages, however, are obtained at the expense of increased system complexity which may be unaffordable in terms of size and energy efficiency. Consequently, some technical challenges remain to develop the adequate antenna technologies capable of supporting the aforementioned features in a limited physical space that the mobility demand dictates. The concept of time-modulated array (TMA) is a feasible multi-antenna technique ...

Maneiro-Catoria, Roberto — University of A Coruña

Heart rate variability : linear and nonlinear analysis with applications in human physiology

Cardiovascular diseases are a growing problem in today’s society. The World Health Organization (WHO) reported that these diseases make up about 30% of total global deaths and that heart diseases have no geographic, gender or socioeconomic boundaries. Therefore, detecting cardiac irregularities early-stage and a correct treatment are very important. However, this requires a good physiological understanding of the cardiovascular system. The heart is stimulated electrically by the brain via the autonomic nervous system, where sympathetic and vagal pathways are always interacting and modulating heart rate. Continuous monitoring of the heart activity is obtained by means of an ElectroCardioGram (ECG). Studying the fluctuations of heart beat intervals over time reveals a lot of information and is called heart rate variability (HRV) analysis. A reduction of HRV has been reported in several cardiological and noncardiological diseases. Moreover, HRV also has a prognostic ...

Vandeput, Steven — KU Leuven

Variational Sparse Bayesian Learning: Centralized and Distributed Processing

In this thesis we investigate centralized and distributed variants of sparse Bayesian learning (SBL), an effective probabilistic regression method used in machine learning. Since inference in an SBL model is not tractable in closed form, approximations are needed. We focus on the variational Bayesian approximation, as opposed to others used in the literature, for three reasons: First, it is a flexible general framework for approximate Bayesian inference that estimates probability densities including point estimates as a special case. Second, it has guaranteed convergence properties. And third, it is a deterministic approximation concept that is even applicable for high dimensional problems where non-deterministic sampling methods may be prohibitive. We resolve some inconsistencies in the literature involved in other SBL approximation techniques with regard to a proper Bayesian treatment and the incorporation of a very desired property, namely scale invariance. More specifically, ...

Buchgraber, Thomas — Graz University of Technology

In the thesis, various aspects of deconvolution of ultrasonic pulse-echo signals in nondestructive testing are treated. The deconvolution problem is formulated as estimation of a reflection sequence which is the impulse characteristic of the inspected object and the estimation is performed using either maximum a posteriori (MAP) or linear minimum mean square error (MMSE) estimators. A multivariable model is proposed for a certain multiple transducer setup allowing for frequency diversity, thereby improving the estimation accuracy. Using the MAP estimator three different material types were treated, with varying amount of sparsity in the reflection sequences. The Gaussian distribution is used for modelling materials containing a large number of small scatters. The Bernoulli--Gaussian distribution is used for sparse data obtained from layered structures and a genetic algorithm approach is proposed for optimizing the corresponding MAP criterion. Sequences with intermediate sparsity suitable of ...

Olofsson, Tomas — Uppsala University

Sigma Delta Modulation Of A Chaotic Signal

Sigma delta modulation has become a widespread method of analogue to digital conversion, however its operation has not been completely defined. The majority of the analysis carried out on the circuit has been from a linear standpoint, with non-linear analysis hinting at hidden complexities in the modulatorâ€™s operation. The sigma delta modulator itself is a non-linear system consisting, as it does, of a number of integrators and a one bit quantiser in a feedback loop. This configuration can be generalised as a non-linearity within a feedback path, which is a classic route to chaotic behaviour. This initially raises the prospect that a sigma delta modulator may be capable of chaotic modes of operation with a non-chaotic input. In fact, the problem does not arise and we show why not. To facilitate this investigation, a set of differential equations is formulated ...

Ushaw, Gary — University Of Edinburgh

Sparse Signal Recovery From Incomplete And Perturbed Data

Sparse signal recovery consists of algorithms that are able to recover undersampled high dimensional signals accurately. These algorithms require fewer measurements than traditional Shannon/Nyquist sampling theorem demands. Sparse signal recovery has found many applications including magnetic resonance imaging, electromagnetic inverse scattering, radar/sonar imaging, seismic data collection, sensor array processing and channel estimation. The focus of this thesis is on electromagentic inverse scattering problem and joint estimation of the frequency offset and the channel impulse response in OFDM. In the electromagnetic inverse scattering problem, the aim is to find the electromagnetic properties of unknown targets from measured scattered field. The reconstruction of closely placed point-like objects is investigated. The application of the greedy pursuit based sparse recovery methods, OMP and FTB-OMP, is proposed for increasing the reconstruction resolution. The performances of the proposed methods are compared against NESTA and MT-BCS methods. ...

Senyuva, Rifat Volkan — Bogazici 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

Signal Processing for Energy-Efficient Burst-Mode RF Transmitters

Modern wireless communication systems utilize complex modulated signals such as OFDM signals to achieve increased data rates and spectral efficiency. These signals are characterized by a high peak-to-average-power ratio (PAPR). Thus, highly linear transmitters are required to provide sufficient transmission signal linearity. Conventional linear PAs, such as Class A or Class AB, produce high efficiency only near or at the peak output power region. As a result, the average efficiency is quite low for high PAPR signals. For non-portable devices such as base stations or mobile devices like mobile phones, low PA efficiency means higher heat dissipation which is often a design criterion. In addition, in mobile devices, a direct consequence of the low PA efficiency is the reduced battery lifetime, especially when the mobile device is required to operate at quite different output power levels. This thesis addresses the ...

Chi, Shuli — Signal Processing and Speech Communication Laboratory

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