No / In this research work the improvement of AOA estimation accuracy by applying a decoupling matrix derived using the receiving mode approach has been investigated using data measured in an anechoic chamber. The receiver was a 4-element uniform circular array with quarter wavelength inter-element spacing deployed on a square metal plate. The performance of the angle of arrival estimation error has been observed for two groups of direction finding algorithms, namely phase comparison-based (interferometry) and covariance-based algorithms. Mutual coupling compensation on AOA was found to improve accuracy by approximately 50%.

This dissertation presents the investigation of biologically inspired direction finding (DF) and localization systems, 3D printing solution for RF components and systems, and fundamental aspects of antennas regarding bandwidth and power efficiency. Biologically inspired direction finding and localization systems are explored first. Inspired by the human binaural auditory system, an improved direction of arrival (DoA) estimation technique using two antennas with a lossy scatterer in between them to achieve additional magnitude cues is proposed. By exploiting the incident-angle- dependent magnitude and phase differences between the two antennas with specially designed scatterer, the DoA of an incident signal from two-dimensional (2-D) / three- dimensional (3-D) space can be estimated. Besides, compact DF systems with enhanced directional sensitivity using a scatterer of high permittivity in between adjacent closely spaced electrically-small antennas are examined. Inspired by the human monaural auditory system, a novel single-antenna DF technique is also proposed by exploiting the incident-angle-dependent spectra for a broadband RF signal only. In addition, a wideband superior DF system utilizing Luneburg lens and uniformly placed detectors on the equator of the lens is evaluated. The DoA is estimated using the amplitude distribution of the received signals at the detectors. Moreover, A portable inventory localization system utilizing hybrid RF (for direction, using previously introduced DF techniques) and ultrasound (for distance) signals is proposed and experimentally demonstrated. Next, a multilayer phased array system is designed and individual parts are printed to demonstrate the applicability of hybrid thermal wire-mesh embedding (for conductors) and thermoplastic extrusion (for dielectrics) techniques for additively manufacturing RF17integrated systems. Finally, fundamental aspects of antennas in terms of bandwidth limit for reactive matching and power efficiency for non-Foster matching are analyzed.

In certain applications involving direction of arrival (DOA) estimation the operator may have a-priori information on some of the DOAs. This information could refer to a target known to be present at a certain position or to a reflection. In this study, the authors investigate a methodology for array processing that exploits the information on the known DOAs for estimating the unknown DOAs as accurately as possible. Algorithms are presented that can efficiently handle the case of both correlated and uncorrelated sources when the receiver is a uniform linear array. The authors find a major improvement in estimator accuracy in feasible scenarios, and they compare the estimator performance to the corresponding theoretical stochastic Cramer-Rao bounds as well as to the performance of other methods capable of exploiting such prior knowledge. In addition, real data from an ultra-sound array is applied to the investigated estimators. / <p>QC 20130107</p>

In this thesis the direction of arrival estimation of wideband signals using frequency invariant beamforming method is examined. The difficulty with the direction of arrival estimation of wideband signals is that it is not possible to obtain a single covariance matrix valid for the whole frequency spectrum of the signal. There are various methods proposed in the literature to overcome this difficulty. The common aim of all the methods is to obtain a composite covariance matrix for the overall band of the signal. In this thesis, we concentrate on a method in [12]. This method is based on a beamforming technique that provides frequency invariant beams in the band of interest. Therefore there is no need for frequency decomposition as it is done with the other wideband methods. A comparison of the frequency invariant beamforming method with coherent signal subspace methods and narrow band methods is also given.

Since World War I, the area of acoustic undersea warfare has witnessed several research activities targeting the development of advanced systems to accurately detect and localize underwater moving targets. One of the main categories of these systems is the passive sound navigation and ranging (SONAR) that searches for the location of the ships and submarines by listening to the radiated noise produced by their propellers, machinery, and flow dynamics. The performance of the passive sonar highly depends on the particular array signal processing algorithms used in practice. Presently, one of the main challenges is to accurately estimate the target direction of arrival (DOA) in severe underwater environments. This thesis is proposed to enhance the DOA estimation in two distinct applications. This first application is to improve the spatial resolution of the uniform linear towed arrays. This is done by applying new spatial extrapolation techniques called 2D- and 3D- fast orthogonal search (FOS) for both uniform linear and rectangular arrays, respectively. The presented methods show better performance than the conventional methods with respect to signal to noise ratio (SNR), number of snapshots and angular separation. Moreover it reduces the computational complexity required by the spatial extrapolation methods based on linear prediction approach. The other application concerns with developing a new DOA estimation that provides better spatial spectrum than the one provided by conventional beamforming (CBF) when a nonuniform linear array of directional frequency analysis and recording (DIFAR) sonobuoys is employed. The introduced technique or the so called fourth order cumulant beamforming (FOCBF) and shows an outstanding performance compared to CBF especially in low SNR. Furthermore, a warping FOC-BF (WFOC-BF) method obtained by augmenting a warping beamforming technique with FOC-BF is proposed to reduce the required computational complexity by FOC-BF while preserving the same performance. / Thesis (Ph.D, Electrical & Computer Engineering) -- Queen's University, 2012-06-27 14:59:33.941

京都大学 / 0048 / 新制・課程博士 / 博士(工学) / 甲第19712号 / 工博第4167号 / 新制||工||1643(附属図書館) / 32748 / 京都大学大学院工学研究科電気工学専攻 / (主査)教授 篠原 真毅, 教授 土居 伸二, 准教授 小嶋 浩嗣 / 学位規則第4条第1項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DFAM

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This research investigates signal processing involving a single electromagnetic vector-sensor, with an emphasis on the problem regarding signal-selective narrowband direction-of-arrival (DOA) estimation in the presence of interference. The approach in this thesis relies on a high-resolution ESPRIT-based algorithm. Unlike spatially displaced arrays, the sensor cannot estimate the DOA of sources using phase differences between the array elements, as the elements are spatially co-located. However, the sensor measures the full electromagnetic field vectors, so the DOA can be estimated through the Poynting vector. Limited information is available in the open literature regarding signal-selective DOA estimation for a single electromagnetic vector-sensor. In this thesis, it is shown how the Uni-Vector-Sensor-ESPRIT (UVS-ESPRIT) algorithm that relies on a time-series invariance and was originally devised for deterministic harmonic sources can be applied to non-deterministic sources. Additionally, two algorithms, one based on cyclostationarity and the other based on fourth-order cumulants, are formulated based on the UVS-ESPRIT algorithm and are capable of selectively estimating the source DOA in the presence of interference based on the statistical properties of the sources. The cyclostationarity-based UVS-ESPRIT algorithm is capable of selectively estimating the signal-of-interest DOA when the sources have the same carrier frequency, and thus overlap in frequency. The cumulant-based UVS-ESPRIT algorithm devised for this sensor relies on the independent component analysis algorithm JADE and is capable of selectively estimating the signal-of-interest DOA through the fourth-order cumulants only, is robust to spatially colored noise, and is capable of estimating the DOA of more sources than sensor elements. / Master of Science / Electromagnetic vector-sensors are specialized sensors capable of capturing the full electromagnetic field vectors at a single point in space. Direction-of-arrival (DOA) estimation is the problem of estimating the spatial-angular parameters of one or more wavefronts impinging on an array. For a single electromagnetic vector-sensor, the array elements are not spatially displaced, but it is still possible to estimate the direction-of-arrival through the Poynting vector, which relates the electric and magnetic field vectors to the direction of propagation of an electromagnetic wave. Although direction-of-arrival estimation is a well-established area of research, there is limited discussion in the open literature regarding signal-selective DOA estimation in the presence of interference for a single electromagnetic vector-sensor. This research investigates this problem and discusses how the high-resolution Uni-Vector-Sensor-ESPRIT (UVS-ESPRIT) algorithm may be applied to non-deterministic sources. ESPRIT based algorithms capable of selectively estimating the source DOA are formulated based on the cyclostationarity and higher-order statistics of the sources, which are approaches known to be robust to interference. The approach based on higher-order statistics is also robust to spatially colored noise and is capable of estimating the DOA of more sources than sensor elements. The formulation of the UVS-ESPRIT for higher-order statistics relies on the application of the independent component analysis algorithm JADE, an unsupervised learning technique. Overall, this research investigates signal-selective direction-of-arrival estimation using an ESPRIT-based algorithm for a single electromagnetic vector-sensor.

Radar (RAdio Detection And Ranging) uses radio waves to detect the presence of a target and measure its position and other properties. This sensor has found many civilian and military applications due to advantages such as possible large surveillance areas and operation day and night and in all weather. The contributions of this thesis are within applied signal processing for radar in two somewhat separate research areas: 1) radar with array antennas and 2) radar with micro-Doppler measurements. Radar with array antennas: An array antenna consists of several small antennas in the same space as a single large antenna. Compared to a traditional single-antenna radar, an array antenna radar gives higher flexibility, higher capacity, several radar functions simultaneously and increased reliability, and makes new types of signal processing possible which give new functions and higher performance. The contributions on array antenna radar in this thesis are in three different problem areas. The first is High Resolution DOA (Direction Of Arrival) Estimation (HRDE) as applied to radar and using real measurement data. HRDE is useful in several applications, including radar applications, to give new functions and improve the performance. The second problem area is suppression of interference (clutter, direct path jamming and scattered jamming) which often is necessary in order to detect and localize the target. The thesis presents various results on interference signal properties, antenna geometry and subarray design, and on interference suppression methods. The third problem area is measurement techniques for which the thesis suggests two measurement designs, one for radar-like measurements and one for scattered signal measurements. Radar with micro-Doppler measurements: There is an increasing interest and need for safety, security and military surveillance at short distances. Tasks include detecting targets, such as humans, animals, cars, boats, small aircraft and consumer drones; classifying the target type and target activity; distinguishing between target individuals; and also predicting target intention. An approach is to employ micro-Doppler radar to perform these tasks. Micro-Doppler is created by the movement of internal parts of the target, like arms and legs of humans and animals, wheels of cars and rotors of drones. Using micro-Doppler, this thesis presents results on feature extraction for classification; on classification of targets types (humans, animals and man-made objects) and human gaits; and on information in micro-Doppler signatures for re-identification of the same human individual. It also demonstrates the ability to use different kinds of radars for micro-Doppler measurements. The main conclusion about micro-Doppler radar is that it should be possible to use for safety, security and military surveillance applications.

In this thesis a new approach is proposed for non-uniform linear arrays (NLA) which employs conventional subspace methods to improve the direction of arrival (DOA) estimation performance. Uniform linear arrays (ULA) are composed of evenly spaced sensor elements located on a straight line. ULA&#039 / s covariance matrix have a Vandermonde matrix structure, which is required by fast subspace DOA estimation algorithms. NLA differ from ULA only by some missing sensor elements. These missing elements cause some gaps in covariance matrix and Vandermonde structure is lost. Therefore fast subspace DOA algorithms can not be applied in this case. Linear programming methods and array interpolation methods can be used to solve this problem. However linear programming is computationally expensive and array interpolation is angular sector dependent and requires the same number of sensor in the virtual array. In this thesis, a covariance matrix augmentation method is developed by using the array interpolation technique and initial DOA estimates. An initial DOA estimate is obtained by Toeplitz completion of the covariance matrix. This initial DOA estimates eliminates the sector dependency and reduces the least square mapping error of array interpolation. A Wiener formulation is developed which allows more sensors in the virtual array than the real array. In addition, it leads to better estimates at low SNR. The new covariance matrix is used in the root-MUSIC algorithm to obtain a better DOA estimate. Several computer simulations are done and it is shown that the proposed approach improves the DOA estimation accuracy significantly compared to the same number of sensor ULA. This approach also increases the number of sources that can be identifed.