Compressive Sensing Based Candidate Detector and its Applications to Spectrum Sensing and Through-the-Wall Radar Imaging

Signal acquisition is a main topic in signal processing. The well-known Shannon-Nyquist theorem lies at the heart of any conventional analog to digital converters stating that any signal has to be sampled with a constant frequency which must be at least twice the highest frequency present in the signal in order to perfectly recover the signal. However, the Shannon-Nyquist theorem provides a worst-case rate bound for any bandlimited data. In this context, Compressive Sensing (CS) is a new framework in which data acquisition and data processing are merged. CS allows to compress the data while is sampled by exploiting the sparsity present in many common signals. In so doing, it provides an efficient way to reduce the number of measurements needed for perfect recovery of the signal. CS has exploded in recent years with thousands of technical publications and applications ...

Lagunas, Eva — Universitat Politecnica de Catalunya


Bayesian Compressed Sensing using Alpha-Stable Distributions

During the last decades, information is being gathered and processed at an explosive rate. This fact gives rise to a very important issue, that is, how to effectively and precisely describe the information content of a given source signal or an ensemble of source signals, such that it can be stored, processed or transmitted by taking into consideration the limitations and capabilities of the several digital devices. One of the fundamental principles of signal processing for decades is the Nyquist-Shannon sampling theorem, which states that the minimum number of samples needed to reconstruct a signal without error is dictated by its bandwidth. However, there are many cases in our everyday life in which sampling at the Nyquist rate results in too many data and thus, demanding an increased processing power, as well as storage requirements. A mathematical theory that emerged ...

Tzagkarakis, George — University of Crete


Advances in Detection and Classification for Through-the-Wall Radar Imaging

In this PhD thesis the problem of detection and classification of stationary targets in Through-the-Wall Radar Imaging is considered. A multiple-view framework is used in which a 3D scene of interest is imaged from a set of vantage points. By doing so, clutter and noise is strongly suppressed and target detectability increased. In target detection, centralized as well as decentralized frameworks for simultaneous image fusion and detection are examined. The practical case when no prior knowledge on image statistics is available and all inference must be drawn from the data at hand is specifically considered. An adaptive detection scheme is proposed which iteratively adapts in a non-stationary environment. Optimal configurations for this scheme are derived based on morphological operations which allow for automatic and reliable target detection. In a decentralized framework, local decisions are transmitted to a fusion center to ...

Debes, Christian — Technical University of Darmstad


Signal Design for Active Sensing and Communications

Man-made active sensing systems such as active radar and sonar have been a vital part of our civilization's advancement in navigation, defense, meteorology, and space exploration. Modern active sensing systems rely heavily on the significant progress in the science and technology of communications made within the last century. Not surprising, the fast growing communications technology has changed each and every aspect of our everyday lives. This thesis is concerned with signal design for improving the performance of active sensing and communication systems: The target detection and estimation performance of the active sensing systems can be considerably improved by a judicious design of the probing signals. Similarly, signal design has a crucial role in the implementation and efficiency of communication systems. Signal optimization for active sensing and communications usually deals with various measures of quality. This thesis focuses on several quality ...

Soltanalian, Mojtaba — Uppsala University


Advanced GPR data processing algorithms for detection of anti-personnel landmines

Ground Penetrating Radar (GPR) is seen as one of several promising technologies aimed to help mine detection. GPR is sensitive to any inhomogeneity in the ground. Therefore any APM regardless of the metal content can be detected. On the other hand, all the inhomogeneities, which do not represent mines, show up as a clutter in GPR images. Moreover, it is known that reflectivity of APM is often weaker than that of stones, pieces of shrapnel and barbed wire, etc. Altogether these factors cause GPR to produce unacceptably high false alarm rate whilst it reaches the 99.6% detection rate which is prescribed by an UN resolution as a standard for humanitarian demining. The main goal of the work presented in the thesis is reduction of the false alarm rate while keeping the 99.6% detection rate intact. To reach this goal a ...

Kovalenko, Vsevolod — Delft University of Technology


Adaptive target detection in radar imaging

This thesis addresses a target detection problem in radar imaging for which the co- variance matrix of an unknown Gaussian clutter background has block diagonal structure. This block diagonal structure is the consequence of a target lying along a boundary between two statistically independent clutter regions. We consider three di erent assumptions on knowledge of the clutter covariance structure: both clutter types totally unknown, one of the clutter types known except for its variance, and one of the clutter types completely known. Here we design adaptive detection algorithms using both the generalized likelihood ratio (GLR) and the invariance principles. There has been considerable recent interest in applying invariant hypothesis testing as an alternative to the GLR test. This interest has been motivated by several attractive theoretical properties of invariant tests including: exact robustness to variation of nuisance parameters, possible nite-sample ...

Kim, Hyung Soo — University of Michigan


Cooperative and Cognitive Communication Techniques for Wireless Networks

During the past years wireless communications have been exhibiting an increased growth rendering them the most common way for communication. The continuously increasing demand for wireless services resulted in limited availability of the wireless spectrum. To this end, Cognitive Radio (CR) techniques have been proposed in literature during the past years. The concept of CR approach is to utilize advanced radio and signal-processing technology along with novel spectrum allocation policies to enable new unlicensed wireless users to operate in the existing occupied spectrum areas without degrading the performance of the existing licensed ones. Moreover, the broadcast and fading nature of the wireless channel results in severe degradation on the performance of wireless transmissions. A solution to the problem is the use of multiple-antenna systems so as to achieve spatial diversity. However, in many cases, the communication devices' nature permit the ...

Tsinos, Christos — University of Patras


Statistical Signal Processing for Data Fusion

In this dissertation we focus on statistical signal processing for Data Fusion, with a particular focus on wireless sensor networks. Six topics are studied: (i) Data Fusion for classification under model uncertainty; (ii) Decision Fusion over coherent MIMO channels; (iii) Performance analysis of Maximum Ratio Combining in MIMO decision fusion; (iv) Decision Fusion over non-coherent MIMO channels; (v) Decision Fusion for distributed classification of multiple targets; (vi) Data Fusion for inverse localization problems, with application to wideband passive sonar platform estimation. The first topic of this thesis addresses the problem of lack of knowledge of the prior distribution in classification problems that operate on small data sets that may make the application of Bayes' rule questionable. Uniform or arbitrary priors may provide classification answers that, even in simple examples, may end up contradicting our common sense about the problem. Entropic ...

Ciuonzo, Domenico — Second University of Naples


Study and optimization of multi-antenna systems associated with multicarrier modulations

Since several years, multi-antenna systems are foreseen as a potential solution for increasing the throughput of future wireless communication systems. The aim of this thesis is to study and to improve the transmitter and receiver's techniques of these MIMO (Multiple Input Multiple Output) systems in the context of a multi-carrier transmission. On the one hand, the OFDM (Orthogonal Frequency Division Multiplex) modulation, which transform a frequency selective channel into multiple non frequency selective channels, is particularly well adapted to the conception of MIMO receivers with low complexity. On the other hand, two techniques allowing to improve the exploitation of frequential and/or temporal diversities are associated with OFDM, namely linear precoding (LP-OFDM) and CDMA in a MC-CDMA (Multicarrier Code division Multiplex Access) scheme. We have associated LP-OFDM and MC-CDMA with two MIMO techniques which require no channel state information at the ...

LE NIR, Vincent — INSA de Rennes


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


Nouvelles méthodes de traitement d’antenne en émission alliant diversité et formation de voie

This work deals with the use of an antenna array at the base station of a mobile communication system for transmission. In reception, solutions that exploit the antenna array are now well established. In transmission, however, the problem remains open. Two approaches are possible : exploit the array by using beamforming techniques or by using diversity techniques. These two approaches are based on opposite assumptions about the channels correlation, which implies a greater or smaller distance between antennas, depending on the environment. In practice, these assumptions are not verified. Here, we aim to deal with the problem as a whole for better exploiting the antenna array. This work treats the mono-user case, as well as the multi-user scenario. In the mono-user case, we propose a transmission scheme composed of a classical transmit diversity technique applied to virtual antennas, which are ...

Zanatta Filho, Danilo — Conservatoire National des Arts et Métiers


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


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


Advanced Multi-Dimensional Signal Processing for Wireless Systems

The thriving development of wireless communications calls for innovative and advanced signal processing techniques targeting at an enhanced performance in terms of reliability, throughput, robustness, efficiency, flexibility, etc.. This thesis addresses such a compelling demand and presents new and intriguing progress towards fulfilling it. We mainly concentrate on two advanced multi-dimensional signal processing challenges for wireless systems that have attracted tremendous research attention in recent years, multi-carrier Multiple-Input Multiple-Output (MIMO) systems and multi-dimensional harmonic retrieval. As the key technologies of wireless communications, the numerous benefits of MIMO and multi-carrier modulation, e.g., boosting the data rate and improving the link reliability, have long been identified and have ignited great research interest. In particular, the Orthogonal Frequency Division Multiplexing (OFDM)-based multi-user MIMO downlink with Space-Division Multiple Access (SDMA) combines the twofold advantages of MIMO and multi-carrier modulation. It is the essential element ...

Cheng, Yao — Ilmenau University of Technology


Competition, Coexistence, and Confidentiality in Multiuser Multi-antenna Wireless Networks

Competition for limited bandwidth, power, and time resources is an intrinsic aspect of multi-user wireless networks. There has been a recent move towards optimizing coexistence and confidentiality at the physical layer of multi-user wireless networks, mainly by exploiting the advanced capabilities of multiple-input multiple-out (MIMO) signal processing methods. Coexistence of disparate networks is made possible via interference mitigation and suppression, and is exemplified by the current interest in cognitive radio (CR) systems. On the other hand, MIMO communications that are secure at the physical layer without depending upon network-layer encryption are achieved by redirecting jamming or multi-user interference to unauthorized receivers, while minimizing that to legitimate receivers. In all cases, the accuracy of the channel state information (CSI) available at the transmitters plays a crucial role in determining the degree of interference mitigation and confidentiality that is achieved. This dissertation ...

Mukherjee, Amitav — University of California Irvine

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